https://addons.mozilla.org/en-US/firefox/addon/disconnect/
Google Disconnect
Facebook Disconnect
Stop major third parties from tracking the webpages you go to (built with WebMynd).
Saturday, December 31, 2011
Viber
http://www.viber.com/
http://lifehacker.com/5706423/viber-makes-free-iphone-calls-over-3g-and-wi+fi
https://addons.mozilla.org/en-US/firefox/addon/disconnect/
When you use Viber, your phone calls and text messages (sms) to any other Viber users are free! The sound quality is also much better than a regular call.
http://lifehacker.com/5706423/viber-makes-free-iphone-calls-over-3g-and-wi+fi
https://addons.mozilla.org/en-US/firefox/addon/disconnect/
When you use Viber, your phone calls and text messages (sms) to any other Viber users are free! The sound quality is also much better than a regular call.
Friday, December 30, 2011
50 Things Women Wish Men Knew
50 Things Women Wish Men Knew
By: Lisa Jones
http://www.menshealth.com/mhlists/what_women_want_from_men/What_She_Wishes_You_Knew_50.php?page=5
By: Lisa Jones
http://www.menshealth.com/mhlists/what_women_want_from_men/What_She_Wishes_You_Knew_50.php?page=5
Thursday, December 29, 2011
Words with a Q not followed by a U
qaid
quintar
quindar
qoph
qiviut
http://www.scrabble.org.au/words/ulessq.htm
Words with a Q not followed by a U
2-letter Words
QI
3-letter Words
QAT QIS SUQ
4-letter Words
QADI QAID QATS QOPH SUQS WAQF
5-letter Words
BURQA FAQIR NIQAB QADIS QAIDS QIBLA QOPHS QORMA TALAQ TRANQ UMIAQ WAQFS
6-letter Words
BURQAS BUQSHA FAQIRS NIQABS QABALA QANATS QASIDA QAWWAL QIBLAS QIGONG
QINDAR QINTAR QIVIUT QORMAS QWERTY SHEQEL TALAQS TRANQS UMIAQS YAQONA
7-letter Words
BUQSHAS INQILAB QABALAH QABALAS QASIDAS QAWWALI QAWWALS QIGONGS
QINDARS QINTARS QIVIUTS QWERTYS SHEQELS TSADDIQ TZADDIQ YAQONAS
8-Letter Words
INQILABS MBAQANGA MUQADDAM QABALAHS QAIMAQAM QALAMDAN
QAWWALIS QINDARKA QWERTIES SHEQALIM TSADDIQS TZADDIQS
9-letter Words
MBAQANGAS MUQADDAMS QABALISM QABALIST QAIMAQAMS QALAMDANS QINGHAOSU
TSADDIQIM TZADDIQIM
quintar
quindar
qoph
qiviut
http://www.scrabble.org.au/words/ulessq.htm
Words with a Q not followed by a U
2-letter Words
QI
3-letter Words
QAT QIS SUQ
4-letter Words
QADI QAID QATS QOPH SUQS WAQF
5-letter Words
BURQA FAQIR NIQAB QADIS QAIDS QIBLA QOPHS QORMA TALAQ TRANQ UMIAQ WAQFS
6-letter Words
BURQAS BUQSHA FAQIRS NIQABS QABALA QANATS QASIDA QAWWAL QIBLAS QIGONG
QINDAR QINTAR QIVIUT QORMAS QWERTY SHEQEL TALAQS TRANQS UMIAQS YAQONA
7-letter Words
BUQSHAS INQILAB QABALAH QABALAS QASIDAS QAWWALI QAWWALS QIGONGS
QINDARS QINTARS QIVIUTS QWERTYS SHEQELS TSADDIQ TZADDIQ YAQONAS
8-Letter Words
INQILABS MBAQANGA MUQADDAM QABALAHS QAIMAQAM QALAMDAN
QAWWALIS QINDARKA QWERTIES SHEQALIM TSADDIQS TZADDIQS
9-letter Words
MBAQANGAS MUQADDAMS QABALISM QABALIST QAIMAQAMS QALAMDANS QINGHAOSU
TSADDIQIM TZADDIQIM
Statistical analysis of co-expression properties of sets of genes in the mouse brain
Statistical analysis of co-expression properties of sets of genes in
the mouse brain
http://arxiv.org/abs/1111.6200
A cell-type based model explaining co-expression patterns of genes in the brain
Pascal Grange, Jason Bohland, Hemant Bokil, Sacha Nelson, Benjamin Okaty, Ken Sugino, Lydia Ng, Michael Hawrylycz, Partha P. Mitra
http://arxiv.org/abs/1111.6217
the mouse brain
http://arxiv.org/abs/1111.6200
A cell-type based model explaining co-expression patterns of genes in the brain
Pascal Grange, Jason Bohland, Hemant Bokil, Sacha Nelson, Benjamin Okaty, Ken Sugino, Lydia Ng, Michael Hawrylycz, Partha P. Mitra
http://arxiv.org/abs/1111.6217
Virtual Windows system + ITunes.
Virtual Windows system + ITunes.
I installed virtualbox 4 and set up a Windows XP. To use the USB drivers I installed the Oracle Expansion Pack. The Licence changes from OSE (Open Source Edition) to PUEL (Personal Use and Evaluation License).
Plugin the Ipod to your Ubuntu System. Start the VM with Windows and Itunes. Under "Devices" in the Virtual Box select your ipod nano. Windows and Itunes will find it.
I also shared my music-library with a virtualbox shared folder and mountet it under windows.
This works for me but I am unhappy with the situation too.
http://askubuntu.com/questions/26353/how-can-i-sync-with-an-ipod-nano-6g
Spotify
http://www.engadget.com/2011/05/04/spotify-launches-download-service-with-ipod-sync-puts-itunes-on/
PlayOnLinux (Wine frontend) > Multimedia > Spotify
http://www.makeuseof.com/tag/spotifys-free-version-working-linux/
VirtualBox windows on Ubuntu
http://www.blog.arun-prabha.com/2007/05/07/installing-virtualbox-and-windows-using-virtualbox-in-ubuntu/
I installed virtualbox 4 and set up a Windows XP. To use the USB drivers I installed the Oracle Expansion Pack. The Licence changes from OSE (Open Source Edition) to PUEL (Personal Use and Evaluation License).
Plugin the Ipod to your Ubuntu System. Start the VM with Windows and Itunes. Under "Devices" in the Virtual Box select your ipod nano. Windows and Itunes will find it.
I also shared my music-library with a virtualbox shared folder and mountet it under windows.
This works for me but I am unhappy with the situation too.
http://askubuntu.com/questions/26353/how-can-i-sync-with-an-ipod-nano-6g
Spotify
http://www.engadget.com/2011/05/04/spotify-launches-download-service-with-ipod-sync-puts-itunes-on/
PlayOnLinux (Wine frontend) > Multimedia > Spotify
http://www.makeuseof.com/tag/spotifys-free-version-working-linux/
VirtualBox windows on Ubuntu
http://www.blog.arun-prabha.com/2007/05/07/installing-virtualbox-and-windows-using-virtualbox-in-ubuntu/
Wednesday, December 28, 2011
A handle on neurodegenerative disease complexity
http://www.nature.com/nmeth/journal/v9/n1/full/nmeth.1847.html?WT.ec_id=NMETH-201201
Erika Pastrana
Nature Methods
doi:10.1038/nmeth.1847
Published online
28 December 2011
Combining experiments and calculations makes it possible to measure the prognostic value of toxic protein species in the cell.
It is still not clear though, whether these aggregates are toxic to the cell or whether they represent a way for the cell to cope with the misfolded mutant proteins. Mutant Htt proteins are continuously shifting from one conformation to another, and it is unclear which of the conformational states (or protein species) exist at a given time in the cell and to what extent each of them contributes to the cell's degeneration.
These are not easy questions to address, and as Steven Finkbeiner and his team at the University of California, San Francisco, noted, methods for such investigations have been lacking. To date, a lot of work has focused on looking at aggregation of purified proteins in a test tube. However, “the environment in which proteins fold and misfold inside cells is very different from the one in vitro,” says Finkbeiner. The group set out to develop new tools and methods that would enable labeling the different protein species of Htt that exist in situ and estimating the pathogenic contribution of each of them.
Erika Pastrana
Nature Methods
doi:10.1038/nmeth.1847
Published online
28 December 2011
Combining experiments and calculations makes it possible to measure the prognostic value of toxic protein species in the cell.
It is still not clear though, whether these aggregates are toxic to the cell or whether they represent a way for the cell to cope with the misfolded mutant proteins. Mutant Htt proteins are continuously shifting from one conformation to another, and it is unclear which of the conformational states (or protein species) exist at a given time in the cell and to what extent each of them contributes to the cell's degeneration.
These are not easy questions to address, and as Steven Finkbeiner and his team at the University of California, San Francisco, noted, methods for such investigations have been lacking. To date, a lot of work has focused on looking at aggregation of purified proteins in a test tube. However, “the environment in which proteins fold and misfold inside cells is very different from the one in vitro,” says Finkbeiner. The group set out to develop new tools and methods that would enable labeling the different protein species of Htt that exist in situ and estimating the pathogenic contribution of each of them.
Brain scarring may help explain obesity battle, study finds
http://www.montrealgazette.com/health/Brain+scarring+help+explain+obesity+battle+study+finds/5916860/story.html
Scientists are linking obesity with inflammation and scarring in the key brain area that controls weight, which could explain why it's so hard to lose weight and keep it off.
When researchers switched mice and rats genetically bred to become obese from low-fat chow to high-fat and highly palatable chow, they began showing signs of inflammation in the hypothalamus within 24 hours.
The hypothalamus takes signals from body fat and other tissues that tell the brain we need food or we've had enough. It also regulates how much fat we burn.
"We saw direct evidence of neuron injury and, ultimately, after months on the diet, a loss of neurons in this hypothalamic area that's vital for body weight control," said lead researcher Dr. Michael Schwartz, professor of medicine and director of the Diabetes and Obesity Center of Excellence at the University of Washington, Seattle.
Scientists are linking obesity with inflammation and scarring in the key brain area that controls weight, which could explain why it's so hard to lose weight and keep it off.
When researchers switched mice and rats genetically bred to become obese from low-fat chow to high-fat and highly palatable chow, they began showing signs of inflammation in the hypothalamus within 24 hours.
The hypothalamus takes signals from body fat and other tissues that tell the brain we need food or we've had enough. It also regulates how much fat we burn.
"We saw direct evidence of neuron injury and, ultimately, after months on the diet, a loss of neurons in this hypothalamic area that's vital for body weight control," said lead researcher Dr. Michael Schwartz, professor of medicine and director of the Diabetes and Obesity Center of Excellence at the University of Washington, Seattle.
Friday, December 23, 2011
Thursday, December 22, 2011
Wednesday, December 21, 2011
ANOVA
http://www.gardenersown.co.uk/Education/Lectures/R/anova.htm#anova
http://www.personality-project.org/r/r.anova.html
A special case of the linear model is the situation where the predictor variables are categorical. In psychological research this usually reflects experimental design where the independent variables are multiple levels of some experimental manipulation (e.g., drug administration, recall instructions, etc.)
The first 5 examples are adapted from the guide to S+ developed by TAs for Roger Ratcliff. For more detail on data entry consult that guide. The last three examples discuss how to reorganize the data from a standard data frame into one appropriate for within subject analyses. For this discussion, I assume that appropriate data files have been created in a text editor and saved in a subjects x variables table.
http://www.personality-project.org/r/r.anova.html
A special case of the linear model is the situation where the predictor variables are categorical. In psychological research this usually reflects experimental design where the independent variables are multiple levels of some experimental manipulation (e.g., drug administration, recall instructions, etc.)
The first 5 examples are adapted from the guide to S+ developed by TAs for Roger Ratcliff. For more detail on data entry consult that guide. The last three examples discuss how to reorganize the data from a standard data frame into one appropriate for within subject analyses. For this discussion, I assume that appropriate data files have been created in a text editor and saved in a subjects x variables table.
Tuesday, December 20, 2011
Microarray data analysis
http://discover.nci.nih.gov/microarrayAnalysis/Exploratory.Analysis.jsp
Exploratory Analysis
Pattern-Finding
Exploratory analysis aims to find patterns in the data that aren’t predicted by the experimenter’s current knowledge or pre-conceptions. Some typical goals are to identify groups of genes expression patterns across samples are closely related; or to find unknown subgroups among samples. A useful first step in all analyses is to identify outliers among samples – those that appear suspiciously far from others in their group. To address these questions, researchers have turned to methods such as cluster analysis, and principal components analysis, although these have often been used inappropriately.
The first widely publicized microarray studies aimed to find uncharacterised genes, which act at specific points during the cell cycle. Clustering is the natural first step in doing this. Unfortunately many people got the impression that clustering is the 'right' thing to do with microarray data; the confusion has been perpetuated, since many software packages have catered to this impression. The proper way to analyze data is the way that addresses the goal at which the study was aimed. Clustering is a useful exploratory technique for suggesting resemblances among groups of genes, but it’s not a way of identifying the differentially regulated genes in an experimental study.
Exploratory Analysis
Pattern-Finding
Exploratory analysis aims to find patterns in the data that aren’t predicted by the experimenter’s current knowledge or pre-conceptions. Some typical goals are to identify groups of genes expression patterns across samples are closely related; or to find unknown subgroups among samples. A useful first step in all analyses is to identify outliers among samples – those that appear suspiciously far from others in their group. To address these questions, researchers have turned to methods such as cluster analysis, and principal components analysis, although these have often been used inappropriately.
The first widely publicized microarray studies aimed to find uncharacterised genes, which act at specific points during the cell cycle. Clustering is the natural first step in doing this. Unfortunately many people got the impression that clustering is the 'right' thing to do with microarray data; the confusion has been perpetuated, since many software packages have catered to this impression. The proper way to analyze data is the way that addresses the goal at which the study was aimed. Clustering is a useful exploratory technique for suggesting resemblances among groups of genes, but it’s not a way of identifying the differentially regulated genes in an experimental study.
The Virtual Fly Brain Browser and Query Interface.
www.virtualflybrain.org
Bioinformatics. 2011 Dec 16. [Epub ahead of print]
The Virtual Fly Brain Browser and Query Interface.
Milyaev N, Osumi-Sutherland D, Reeve S, Burton N, Baldock RA, Armstrong JD.
Source
School of Informatics, University of Edinburgh, UK.
Abstract
MOTIVATION:
Sources of neuroscience data in Drosophila are diverse and disparate making integrated search and retrieval difficult. A major obstacle to this is the lack of a comprehensive and logically structured anatomical framework and an intuitive interface.
RESULTS:
We present an online resource that provides a convenient way to study and query fly brain anatomy, expression and genetic data. We extended the newly developed BrainName nomenclature for the adult fly brain into a logically structured ontology that relates a comprehensive set of published neuron classes to the brain regions they innervate. The Virtual Fly Brain interface allows users to explore the structure of the Drosophila brain by browsing 3D images of a brain with sub-regions displayed as coloured overlays. An integrated query mechanism allows complex searches of underlying anatomy, cells, expression and other data from community databases.
AVAILABILITY:
Virtual Fly Brain is freely available on-line at www.virtualflybrain.org.
Bioinformatics. 2011 Dec 16. [Epub ahead of print]
The Virtual Fly Brain Browser and Query Interface.
Milyaev N, Osumi-Sutherland D, Reeve S, Burton N, Baldock RA, Armstrong JD.
Source
School of Informatics, University of Edinburgh, UK.
Abstract
MOTIVATION:
Sources of neuroscience data in Drosophila are diverse and disparate making integrated search and retrieval difficult. A major obstacle to this is the lack of a comprehensive and logically structured anatomical framework and an intuitive interface.
RESULTS:
We present an online resource that provides a convenient way to study and query fly brain anatomy, expression and genetic data. We extended the newly developed BrainName nomenclature for the adult fly brain into a logically structured ontology that relates a comprehensive set of published neuron classes to the brain regions they innervate. The Virtual Fly Brain interface allows users to explore the structure of the Drosophila brain by browsing 3D images of a brain with sub-regions displayed as coloured overlays. An integrated query mechanism allows complex searches of underlying anatomy, cells, expression and other data from community databases.
AVAILABILITY:
Virtual Fly Brain is freely available on-line at www.virtualflybrain.org.
Monday, December 19, 2011
polypyrimidine tract
The polypyrimidine tract is a region of messenger RNA (mRNA) that promotes the assembly of the spliceosome, the protein complex specialized for carrying out RNA splicing during the process of post-transcriptional modification. The region is rich with pyrimidine nucleotides, especially uracil, and is usually 15-20 base pairs long, located about 5-40 base pairs before the 3' end of the intron to be spliced.[1]
http://en.wikipedia.org/wiki/Polypyrimidine_tract
http://en.wikipedia.org/wiki/Polypyrimidine_tract
Sunday, December 18, 2011
Recombinant Innovation - Drawing from oral histories, Hughes describes the origins, growth, and fall of the biotech pioneer Genentech.
Recombinant Innovation
Gerald Barnett
Drawing from oral histories, Hughes describes the origins, growth, and fall of the biotech pioneer Genentech.
http://www.sciencemag.org/content/334/6062/1497.full
Genentech The Beginnings of Biotech by Sally Smith Hughes University of Chicago Press, Chicago, 2011. 229 pp. $25, £16. ISBN 9780226359182. Synthesis.
E-mail: gerald.barnett@gmail.com
Genentech was one of the early and most successful companies formed in the biotech revolution. Sally Smith Hughes's Genentech chronicles a progression of events from Stanley Cohen and Herbert Boyer's invention of recombinant DNA in 1973 through the company's initial public offering in 1980—including the efforts to raise money and the race to prove the technology by making a commercially valuable product (such as insulin and human growth hormone). Drawing on oral histories, Hughes supplements her narrative with a wealth of archival material from the University of California (UC) and Genentech.
Gerald Barnett
Drawing from oral histories, Hughes describes the origins, growth, and fall of the biotech pioneer Genentech.
http://www.sciencemag.org/content/334/6062/1497.full
Genentech The Beginnings of Biotech by Sally Smith Hughes University of Chicago Press, Chicago, 2011. 229 pp. $25, £16. ISBN 9780226359182. Synthesis.
E-mail: gerald.barnett@gmail.com
Genentech was one of the early and most successful companies formed in the biotech revolution. Sally Smith Hughes's Genentech chronicles a progression of events from Stanley Cohen and Herbert Boyer's invention of recombinant DNA in 1973 through the company's initial public offering in 1980—including the efforts to raise money and the race to prove the technology by making a commercially valuable product (such as insulin and human growth hormone). Drawing on oral histories, Hughes supplements her narrative with a wealth of archival material from the University of California (UC) and Genentech.
Friday, December 16, 2011
MIT Brain and Cognitive Sciences
HM's Brain
http://en.wikipedia.org/wiki/HM_%28patient%29
http://www.bbc.co.uk/programmes/p0099v8g
Listen to Sue Corkin on the BBC's Heath Watch talk about HM: A man known as HM provided the key to one of the mysteries of the human brain. Having lost his own memory through surgery for epilepsy, HM revealed how new memories are formed. Without a few unusual people, human behaviour would have remained a mystery - ordinary people whose extraordinary circumstances provided researchers with the exceptions that proved behavioural rules. (audio only)
http://bcs.mit.edu/newsevents/bcsvideos.html
October 14, 2011
Professor David Hubel and Professor Torsten Wiesel [more]
May 25, 2011
A conversation with Molly Potter [more]
May 3-5, 2011
Brains, Minds and Machines Symposium [more]
April 25, 2011
An afternoon with MIT's Brains on Brains [more]
March 28, 2011
A squeeze, a squeak, a glimpse of learning: From Boston.com: Studies find clues to babies' minds. [more]
March 21, 2011
From WBUR/ NPR: Listen to Guoping Feng discuss his new study that creates Autisic-like behavior in mice. [more]
January, 2011
Watch Institute Professor and BCS alumna Ann Graybiel discuss her career and achievements at MIT. [more]
November 15, 2010
Watch Pawan Sinha discuss "Acquiring visual function after delayed sight onset". [more]
November 9, 2010
Watch Rebecca Saxe discuss "How the brain thinks about the mind: a case study in the neural basis of abstract cognition". [more]
October 25, 2010
Watch Josh Tenenbaum discuss "How to grow a mind: statistics, structure and abstraction". [more]
October 2, 2010
From The Science Network: Watch Laura Schulz discuss her reseach which is focused on the learning mechanisms that build the infrastructure of human cognition in children and babies. [more]
August 30, 2010
Listen to Sue Corkin on the BBC's Heath Watch talk about HM: A man known as HM provided the key to one of the mysteries of the human brain. Having lost his own memory through surgery for epilepsy, HM revealed how new memories are formed. Without a few unusual people, human behaviour would have remained a mystery - ordinary people whose extraordinary circumstances provided researchers with the exceptions that proved behavioural rules. (audio only) [more]
July, 2010
Sebastian Seung: I am my connectome: TED Talks- Sebastian Seung is mapping a massively ambitious new model of the brain that focuses on the connections between each neuron. He calls it our "connectome," and it's as individual as our genome -- and understanding it could open a new way to understand our brains and our minds. [more]
April 27, 2010
Nancy Kanwisher: Face Perception: Nancy Kanwisher uses brain imaging and behavioral tests to study how different regions of the brain contribute to our perception of the visual world. In this talk, Nancy shares what her lab has discovered about how the adult brain perceives faces. [more]
April 27, 2010
Daniel Dilks: Scanning the Developing Child's Brain: At the Martinos Imaging Center, our researchers have the unique ability to explore the developing child's brain. In this talk, Daniel Dilks--a post-doc in the Kanwisher lab--describes the challenges involved with scanning children, how his team has learned to overcome these challenges, and what his team has learned so far about the developing child's brain. [more]
April 27, 2010
Rebecca Saxe: Theory of Mind : Rebecca Saxe studies how we think about other people's thoughts. In this talk, Rebecca outlines preliminary findings about face processing and the development of a Theory of Mind in young children. [more]
April 12, 2010
What are dreams?: From NOVA: Psychologists and brain scientists including Matt Wilson have new answers to an age-old question. [more]
http://en.wikipedia.org/wiki/HM_%28patient%29
http://www.bbc.co.uk/programmes/p0099v8g
Listen to Sue Corkin on the BBC's Heath Watch talk about HM: A man known as HM provided the key to one of the mysteries of the human brain. Having lost his own memory through surgery for epilepsy, HM revealed how new memories are formed. Without a few unusual people, human behaviour would have remained a mystery - ordinary people whose extraordinary circumstances provided researchers with the exceptions that proved behavioural rules. (audio only)
http://bcs.mit.edu/newsevents/bcsvideos.html
October 14, 2011
Professor David Hubel and Professor Torsten Wiesel [more]
May 25, 2011
A conversation with Molly Potter [more]
May 3-5, 2011
Brains, Minds and Machines Symposium [more]
April 25, 2011
An afternoon with MIT's Brains on Brains [more]
March 28, 2011
A squeeze, a squeak, a glimpse of learning: From Boston.com: Studies find clues to babies' minds. [more]
March 21, 2011
From WBUR/ NPR: Listen to Guoping Feng discuss his new study that creates Autisic-like behavior in mice. [more]
January, 2011
Watch Institute Professor and BCS alumna Ann Graybiel discuss her career and achievements at MIT. [more]
November 15, 2010
Watch Pawan Sinha discuss "Acquiring visual function after delayed sight onset". [more]
November 9, 2010
Watch Rebecca Saxe discuss "How the brain thinks about the mind: a case study in the neural basis of abstract cognition". [more]
October 25, 2010
Watch Josh Tenenbaum discuss "How to grow a mind: statistics, structure and abstraction". [more]
October 2, 2010
From The Science Network: Watch Laura Schulz discuss her reseach which is focused on the learning mechanisms that build the infrastructure of human cognition in children and babies. [more]
August 30, 2010
Listen to Sue Corkin on the BBC's Heath Watch talk about HM: A man known as HM provided the key to one of the mysteries of the human brain. Having lost his own memory through surgery for epilepsy, HM revealed how new memories are formed. Without a few unusual people, human behaviour would have remained a mystery - ordinary people whose extraordinary circumstances provided researchers with the exceptions that proved behavioural rules. (audio only) [more]
July, 2010
Sebastian Seung: I am my connectome: TED Talks- Sebastian Seung is mapping a massively ambitious new model of the brain that focuses on the connections between each neuron. He calls it our "connectome," and it's as individual as our genome -- and understanding it could open a new way to understand our brains and our minds. [more]
April 27, 2010
Nancy Kanwisher: Face Perception: Nancy Kanwisher uses brain imaging and behavioral tests to study how different regions of the brain contribute to our perception of the visual world. In this talk, Nancy shares what her lab has discovered about how the adult brain perceives faces. [more]
April 27, 2010
Daniel Dilks: Scanning the Developing Child's Brain: At the Martinos Imaging Center, our researchers have the unique ability to explore the developing child's brain. In this talk, Daniel Dilks--a post-doc in the Kanwisher lab--describes the challenges involved with scanning children, how his team has learned to overcome these challenges, and what his team has learned so far about the developing child's brain. [more]
April 27, 2010
Rebecca Saxe: Theory of Mind : Rebecca Saxe studies how we think about other people's thoughts. In this talk, Rebecca outlines preliminary findings about face processing and the development of a Theory of Mind in young children. [more]
April 12, 2010
What are dreams?: From NOVA: Psychologists and brain scientists including Matt Wilson have new answers to an age-old question. [more]
Seeing is Believing - Life Sciences Cafe Scientific
http://vimeo.com/33091531
Part 2 of "Seeing is Believing" the November 2011 edition of Cafe Scientifique, a public seminar series hosted by The Life Sciences Institute, University of British Columbia.
Part 2 of "Seeing is Believing" the November 2011 edition of Cafe Scientifique, a public seminar series hosted by The Life Sciences Institute, University of British Columbia.
Marriage
"Happy marriages begin when we marry the one we love, and they blossom when we love the one we married."
Thursday, December 15, 2011
Great teacher inspires
"The mediocre teacher tells. The good teacher explains. The superior teacher demonstrates. The great teacher inspires."
Wednesday, December 14, 2011
Mantel test
http://www.ats.ucla.edu/stat/r/faq/mantel_test.htm
A Mantel test measures the correlation between two matrices typically containing measures of distance. A Mantel test is one way of testing for spatial autocorrelation. Using functions in the ade4 library, we can perform a Mantel test in R. To download and load this library, enter install.packages("ade4") and then library(ade4). There are other Mantel test functions available in other R libraries and our choice of this library's should not be seen as an endorsement in any way.
A Mantel test measures the correlation between two matrices typically containing measures of distance. A Mantel test is one way of testing for spatial autocorrelation. Using functions in the ade4 library, we can perform a Mantel test in R. To download and load this library, enter install.packages("ade4") and then library(ade4). There are other Mantel test functions available in other R libraries and our choice of this library's should not be seen as an endorsement in any way.
imo - web-based service that allows users to hold text, voice, and video chats on multiple instant messaging protocols
https://imo.im/android
what is imo.im?
imo.im is a web-based service that allows users to hold text, voice, and video chats on multiple instant messaging protocols. Currently supported protocols include MSN, Skype, Yahoo Messenger, Google Talk, Facebook, AIM/ICQ, Jabber, MySpace, Hyves, VKontakte and Steam. The service is free and requires no user-registration or sign-up.
what is imo.im?
imo.im is a web-based service that allows users to hold text, voice, and video chats on multiple instant messaging protocols. Currently supported protocols include MSN, Skype, Yahoo Messenger, Google Talk, Facebook, AIM/ICQ, Jabber, MySpace, Hyves, VKontakte and Steam. The service is free and requires no user-registration or sign-up.
Take Shelter
http://www.imdb.com/title/tt1675192/
Plagued by a series of apocalyptic visions, a young husband and father questions whether to shelter his family from a coming storm, or from himself.
Plagued by a series of apocalyptic visions, a young husband and father questions whether to shelter his family from a coming storm, or from himself.
Tuesday, December 13, 2011
Automatic Individual Animal Identification from Photographs
http://compbio.cs.uic.edu/projects.html
http://code.google.com/p/stripespotter/wiki/Walkthrough
Welcome to Computational Population Biology at UIC
Professor Tanya Y. Berger-Wolf
In wild animal populations, collecting behavioral data about a species often entails identifying individual animals between sightings taken at different places and times. This is a primitive operation in ecological analysis that underlies broader aspects of animal behavior research. Electronic tracking devices embedded in animals are one ap proach to identifying individual animals, but can be prohibitively expensive and difficult to design for field conditions, and involve considerable cost and risk for larger an imals. Researchers are therefore left with no alternative other than to manually record data in the field us ing, for example, genetic markers in excrement, capture recapture techniques, or manual identification from photographs. Advances in hardware and the correspond ing drop in prices of digital cameras have resulted in an increase in the availability of digital photographs of wild animal sightings at high resolutions and qualities, making it an attractive candidate for fully-automatic or computer-assisted animal identification.
In collaboration with the Princeton Equid research group, we have developed StripeSpotter, a program to perform automatic individual animal identification of zebras and other striped animals. It is an ongoing project, and has currently been deployed at various nature conservancies in Kenya.
http://code.google.com/p/stripespotter/wiki/Walkthrough
Welcome to Computational Population Biology at UIC
Professor Tanya Y. Berger-Wolf
In wild animal populations, collecting behavioral data about a species often entails identifying individual animals between sightings taken at different places and times. This is a primitive operation in ecological analysis that underlies broader aspects of animal behavior research. Electronic tracking devices embedded in animals are one ap proach to identifying individual animals, but can be prohibitively expensive and difficult to design for field conditions, and involve considerable cost and risk for larger an imals. Researchers are therefore left with no alternative other than to manually record data in the field us ing, for example, genetic markers in excrement, capture recapture techniques, or manual identification from photographs. Advances in hardware and the correspond ing drop in prices of digital cameras have resulted in an increase in the availability of digital photographs of wild animal sightings at high resolutions and qualities, making it an attractive candidate for fully-automatic or computer-assisted animal identification.
In collaboration with the Princeton Equid research group, we have developed StripeSpotter, a program to perform automatic individual animal identification of zebras and other striped animals. It is an ongoing project, and has currently been deployed at various nature conservancies in Kenya.
Sunday, December 11, 2011
Akai Ito 赤い糸
http://doramax264.com/romance/akai-ito/
Title : Akai Ito
Alternative Title(s) : Red Thread of Destiny
Hardsubbed or Softsubbed: Hardsubbed
English Subtitles: Yes
Fansub: Other
Number of Episodes: 11
Date Aired (YYYY-MM-DD): 2008-Dec-06 to 2009-Feb-28
Wiki D- Addicts: http://wiki.d-addicts.com/Akai_Ito
Summary:
The story was one of the best-selling novels of 2007, it revolves around the “red thread of fate” connecting the young pair Mei and Atsushi and the trials they face.
(Red thread of fate: According to this myth, the gods tie an invisible red string around the little fingers of men and women who are destined to be soul mates. The two people connected by the red thread are destined lovers, regardless of time, place or circumstances. This magical cord may stretch or tangle, but never break.)
Title : Akai Ito
Alternative Title(s) : Red Thread of Destiny
Hardsubbed or Softsubbed: Hardsubbed
English Subtitles: Yes
Fansub: Other
Number of Episodes: 11
Date Aired (YYYY-MM-DD): 2008-Dec-06 to 2009-Feb-28
Wiki D- Addicts: http://wiki.d-addicts.com/Akai_Ito
Summary:
The story was one of the best-selling novels of 2007, it revolves around the “red thread of fate” connecting the young pair Mei and Atsushi and the trials they face.
(Red thread of fate: According to this myth, the gods tie an invisible red string around the little fingers of men and women who are destined to be soul mates. The two people connected by the red thread are destined lovers, regardless of time, place or circumstances. This magical cord may stretch or tangle, but never break.)
Waiting Alone (2004) 独自等待
http://www.imdb.com/title/tt0311041/
Waiting Alone (2004)
Du zi deng dai (original title)
Set in modern day Bejing, Waiting Alone is a coming-of-age story of Wen (Xia Yu), an antique shop owner and aspiring author who has just met the girl of his dreams. Waiting Alone shows us a China rarely seen in cinema, a China that is contemporary, hip and vibrant. Written by Easternlight Films
Director:
Dayyan Eng
Writer:
Dayyan Eng
Stars:
Yu Xia, Bingbing Li and Beibi Gong
Waiting Alone (2004)
Du zi deng dai (original title)
Set in modern day Bejing, Waiting Alone is a coming-of-age story of Wen (Xia Yu), an antique shop owner and aspiring author who has just met the girl of his dreams. Waiting Alone shows us a China rarely seen in cinema, a China that is contemporary, hip and vibrant. Written by Easternlight Films
Director:
Dayyan Eng
Writer:
Dayyan Eng
Stars:
Yu Xia, Bingbing Li and Beibi Gong
WHMIS (Workplace Hazardous Materials Information System)
http://www.ccohs.ca/oshanswers/legisl/whmis_classifi.html
What are WHMIS classes or classifications?
WHMIS (Workplace Hazardous Materials Information System) uses classifications to group chemicals with similar properties or hazards. The Controlled Products Regulations specifies the criteria used to place materials within each classification. There are six (6) classes although several classes have divisions or subdivisions. Each class has a specific symbol to help people identify the hazard quickly. The classes are:
Class A - Compressed Gas
Class B - Flammable and Combustible Material
Division 1: Flammable Gas
Division 2: Flammable Liquid
Division 3: Combustible Liquid
Division 4: Flammable Solid
Division 5: Flammable Aerosol
Division 6: Reactive Flammable Material
Class C - Oxidizing Material
Class D - Poisonous and Infectious Material
Division 1: Materials causing immediate and serious toxic effects
Subdivision A: Very toxic material
Subdivision B: Toxic material
Division 2: Materials causing other toxic effects
Subdivision A: Very toxic material
Subdivision B: Toxic material
Division 3: Biohazardous Infection Material
Class E - Corrosive material
Class F - Dangerously reactive material
What are WHMIS classes or classifications?
WHMIS (Workplace Hazardous Materials Information System) uses classifications to group chemicals with similar properties or hazards. The Controlled Products Regulations specifies the criteria used to place materials within each classification. There are six (6) classes although several classes have divisions or subdivisions. Each class has a specific symbol to help people identify the hazard quickly. The classes are:
Class A - Compressed Gas
Class B - Flammable and Combustible Material
Division 1: Flammable Gas
Division 2: Flammable Liquid
Division 3: Combustible Liquid
Division 4: Flammable Solid
Division 5: Flammable Aerosol
Division 6: Reactive Flammable Material
Class C - Oxidizing Material
Class D - Poisonous and Infectious Material
Division 1: Materials causing immediate and serious toxic effects
Subdivision A: Very toxic material
Subdivision B: Toxic material
Division 2: Materials causing other toxic effects
Subdivision A: Very toxic material
Subdivision B: Toxic material
Division 3: Biohazardous Infection Material
Class E - Corrosive material
Class F - Dangerously reactive material
Friday, December 9, 2011
R multiple plots in one PNG file
library(Cairo)
CairoPNG('foo.png', width=1200, res=72) # CairoPDF('foo.pdf') # use PDF for crispier images
par(mfrow=c(2,3))
for (i in c(1:6)) { plot(sample(100)) }
dev.off()
CairoPNG('foo.png', width=1200, res=72) # CairoPDF('foo.pdf') # use PDF for crispier images
par(mfrow=c(2,3))
for (i in c(1:6)) { plot(sample(100)) }
dev.off()
AUC ROC
# for plotting ROC curve
ROC <- function(ranks , n) {
#doesn't work for ties !
TF = rep(0,n)
TF[ranks] = 1;
fp=cumsum(as.numeric(!TF)/as.numeric(sum(!TF)))
tp=cumsum(TF/sum(TF))
return( list( fp = fp, tp = tp))
}
r <- ROC(c(1:5),10)
plot(r$fp, r$tp)
# calculating AUC score
AUC <- function(ranks, n) {
#ranks : ranks = c( 1,2,3);
#n = 5 ; total number
Npos =length(ranks)
Nneg = n - Npos
AUC = 1 - ( sum(ranks) - Npos*(Npos+1)/2 ) / (Npos * Nneg)
return(AUC)
}
ROC <- function(ranks , n) {
#doesn't work for ties !
TF = rep(0,n)
TF[ranks] = 1;
fp=cumsum(as.numeric(!TF)/as.numeric(sum(!TF)))
tp=cumsum(TF/sum(TF))
return( list( fp = fp, tp = tp))
}
r <- ROC(c(1:5),10)
plot(r$fp, r$tp)
# calculating AUC score
AUC <- function(ranks, n) {
#ranks : ranks = c( 1,2,3);
#n = 5 ; total number
Npos =length(ranks)
Nneg = n - Npos
AUC = 1 - ( sum(ranks) - Npos*(Npos+1)/2 ) / (Npos * Nneg)
return(AUC)
}
Can't get a lock on A-GPS (GPS) status on LG Optimus One P500H
Can't get a lock on A-GPS (GPS) status on LG Optimus One P500H (v10s Android 2.2.1) using the GPS Status Android App (ElipSim) https://market.android.com/details?id=com.eclipsim.gpsstatus2&hl=en
One way to fix this without patching is upgrading to GingerBread 2.3.3 from the LG mobile website
http://www.lg.com/ca_en/support/mc-support/mobile-phone-support.jsp Model LGP500H
Note: Will need to free up as much space on the phone to install properly
Windows USB Driver
http://algmcdn.lgmobile.com/dn/downloader.dev?fileKey=UW00120110909
Software Update
http://csmg.lgmobile.com:9002/client/app/B2CAppSetup.exe
Note: Need to have the updated Flash plugin to see download links
One way to fix this without patching is upgrading to GingerBread 2.3.3 from the LG mobile website
http://www.lg.com/ca_en/support/mc-support/mobile-phone-support.jsp Model LGP500H
Note: Will need to free up as much space on the phone to install properly
Windows USB Driver
http://algmcdn.lgmobile.com/dn/downloader.dev?fileKey=UW00120110909
Software Update
http://csmg.lgmobile.com:9002/client/app/B2CAppSetup.exe
Note: Need to have the updated Flash plugin to see download links
Thursday, December 8, 2011
Mouse gestures for browsers
https://addons.mozilla.org/en-us/firefox/search/?q=gestures&appver=3.6.24&platform=linux
Click and drag a right-corners, arrows to navigate without leaving your mouse
Click and drag a right-corners, arrows to navigate without leaving your mouse
Monday, December 5, 2011
Ubuntu tips: Move Window Control Buttons to the Right, Re-start System without Rebooting
http://www.techsupportalert.com/content/ubuntu-tips-and-tricks.htm
Move Window Control Buttons to the Right
If your Ubuntu system sets the Minimize, Maximize and Close buttons to the left in a window and you prefer to change them to the right, then follow these simple steps:
1. Move buttons to rightPress Alt+F2 to bring up "Run Application" window.
2. Type gconf-editor into the box, click "Run" to bring up Configuration Editor.
3. Browse to apps > metacity > general, look for "button_layout" on the right panel.
4. Change the value in the "button_layout" from close,minimize,maximize: to menu:minimize,maximize,close and press the Enter key.
10 Applications You Must Install On Ubuntu Lucid Lynx [Linux]
http://www.makeuseof.com/tag/10-applications-install-ubuntu-lucid-lynx/
Re-start System without Rebooting
If you press Ctrl+Alt+Delete, Ubuntu brings you a menu to shut down, restart, or suspend your system. But for some reason you might encounter that the system freezes, the mouse cursor can't move, neither pressing Ctrl+Alt+Delete can work.
Remember that there's a shortcut key Alt+PrintScreen+K that can bring you back to the log-in screen immediately without the need to reboot the system. That's a time saver.
As an alternative, you can also use Ctrl+Alt+Backspace to do the same after you've enabled the shortcut key by the following steps:
1. Go to System > Preferences > Keyboard.
2. Select the “Layouts” tab and click the “Options” button.
3. Select “Key sequence to kill the X server” and enable “Control + Alt + Backspace”.
Move Window Control Buttons to the Right
If your Ubuntu system sets the Minimize, Maximize and Close buttons to the left in a window and you prefer to change them to the right, then follow these simple steps:
1. Move buttons to rightPress Alt+F2 to bring up "Run Application" window.
2. Type gconf-editor into the box, click "Run" to bring up Configuration Editor.
3. Browse to apps > metacity > general, look for "button_layout" on the right panel.
4. Change the value in the "button_layout" from close,minimize,maximize: to menu:minimize,maximize,close and press the Enter key.
10 Applications You Must Install On Ubuntu Lucid Lynx [Linux]
http://www.makeuseof.com/tag/10-applications-install-ubuntu-lucid-lynx/
Re-start System without Rebooting
If you press Ctrl+Alt+Delete, Ubuntu brings you a menu to shut down, restart, or suspend your system. But for some reason you might encounter that the system freezes, the mouse cursor can't move, neither pressing Ctrl+Alt+Delete can work.
Remember that there's a shortcut key Alt+PrintScreen+K that can bring you back to the log-in screen immediately without the need to reboot the system. That's a time saver.
As an alternative, you can also use Ctrl+Alt+Backspace to do the same after you've enabled the shortcut key by the following steps:
1. Go to System > Preferences > Keyboard.
2. Select the “Layouts” tab and click the “Options” button.
3. Select “Key sequence to kill the X server” and enable “Control + Alt + Backspace”.
Saturday, December 3, 2011
smarterer.com - answer questions
smarterer.com
Answer questions.
Get your score.
Show what you know.
Smarterer ranks and scores your digital skills using crowd-sourced questions.
Answer questions.
Get your score.
Show what you know.
Smarterer ranks and scores your digital skills using crowd-sourced questions.
Friday, December 2, 2011
Product mix examples
http://www.solver.com/stepbystep.htm
Imagine that you manage a factory which produces four different types of wood paneling. Each type of paneling is made by gluing and pressing together a different mixture of pine and oak chips. The following table summarizes the required amount of gluing, pressing, and mixture of wood chips required to produce a pallet of 50 units of each type of paneling:
Let's assume that for the next production cycle, you have 5,800 quarts of glue; 730 hours of pressing capacity; 29,200 pounds of pine chips; and 60,500 pounds of oak chips available. Further, assume that each pallet of Tahoe, Pacific, Savannah, and Aspen panels can be sold for profits of $450, $1,150, $800, and $400, respectively.
Maximize 450 X1 + 1150 X2 + 800 X3 + 400 X4 (profit)
50 X1 + 50 X2 + 100 X3 + 50 X4 <= 5,800 (Glue)
5 X1 + 15 X2 + 10 X3 + 5 X4 <= 730 (Pressing)
500 X1 + 400 X2 + 300 X3 + 200 X4 <= 29,200 (Pine Chips)
500 X1 + 750 X2 + 250 X3 + 500 X4 <= 60,500 (Oak Chips)
X1, X2, X3, X4 >= 0 (non-negative)
Imagine that you manage a factory which produces four different types of wood paneling. Each type of paneling is made by gluing and pressing together a different mixture of pine and oak chips. The following table summarizes the required amount of gluing, pressing, and mixture of wood chips required to produce a pallet of 50 units of each type of paneling:
Let's assume that for the next production cycle, you have 5,800 quarts of glue; 730 hours of pressing capacity; 29,200 pounds of pine chips; and 60,500 pounds of oak chips available. Further, assume that each pallet of Tahoe, Pacific, Savannah, and Aspen panels can be sold for profits of $450, $1,150, $800, and $400, respectively.
Maximize 450 X1 + 1150 X2 + 800 X3 + 400 X4 (profit)
50 X1 + 50 X2 + 100 X3 + 50 X4 <= 5,800 (Glue)
5 X1 + 15 X2 + 10 X3 + 5 X4 <= 730 (Pressing)
500 X1 + 400 X2 + 300 X3 + 200 X4 <= 29,200 (Pine Chips)
500 X1 + 750 X2 + 250 X3 + 500 X4 <= 60,500 (Oak Chips)
X1, X2, X3, X4 >= 0 (non-negative)
Metropolis Hastings - sampling from a difficult distribution
In mathematics and physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. This sequence can be used to approximate the distribution (i.e., to generate a histogram), or to compute an integral (such as an expected value).
http://en.wikipedia.org/wiki/Metropolis%E2%80%93Hastings_algorithm
http://users.isr.ist.utl.pt/~rmcantin/teaching/demo.py
http://en.wikipedia.org/wiki/Metropolis%E2%80%93Hastings_algorithm
http://users.isr.ist.utl.pt/~rmcantin/teaching/demo.py
Puzzle finding shortest path
The first line has the number of rows in the nucleus (N), then the number of columns (M), then the length of Danny Dendrite's genome (X). Following that are N lines, each of which has M characters: an ‘o’ represents an empty square and an ‘x’ represents a filled square.
Print for him a path, consisting of a list of positions, starting anywhere in the nucleus, where:
- Each position is empty
- Each successive position is only 1 nm away from the one before it
- The path passes through each position in the nucleus at most once
- The number of positions visited is equal to the length of Danny Dendrite's genome (the starting and ending positions both count).
#
# P.T.
#
# https://dnanexus.com/careers/puzzles
#
#
import networkx # needs ver 1.6
import matplotlib.pyplot as plt
#input
rawData = """5 4 8
oxoo
xoxo
ooxo
xooo
oxox"""
def getNeighbours(row, col, maxRow, maxCol):
""">>> getNeighbours(1,1)
[[1, 0], [1, 2], [0, 1], [2, 1]]
"""
left = [row - 1, col]
right = [row + 1, col]
top = [row, col - 1]
bottom = [row, col + 1]
neighbours = [top, bottom, left, right]
if (top[1] < 0 or top[1] >= maxCol):
neighbours.remove(top)
if bottom[1] < 0 or bottom[1] >= maxCol:
neighbours.remove(bottom)
if left[0] < 0 or left[1] >= maxRow:
neighbours.remove(left)
if right[0] < 0 or right[0] >= maxRow:
neighbours.remove(right)
return neighbours
def isOk(node):
"""'o' isOk, 'x' is not"""
if (node == 'o'):
return True
else:
return False
# parse
#infile = [line.rstrip() for line in open('in').readlines()]
infile = [line.rstrip() for line in rawData.split('\n')]
[nrow, ncol, plen] = infile[0].split(' ')
nrow = int(nrow)
ncol = int(ncol)
plen = int(plen)
data = infile[1:]
# construct graph from input
G = networkx.Graph()
hash = '%s,%s'
print nrow, data, len(data)
assert len(data) == nrow
for row in range(nrow):
line = data[row]
assert len(line) == ncol
for col in range(ncol):
node = data[row][col]
#print 'node=', node, 'row=', row, 'col=', col
if (not isOk(node)):
continue
G.add_node(hash % (row,col))
neighbours = getNeighbours(row, col, nrow, ncol)
#print neighbours
for x,y in neighbours:
#print '?? x=', x, 'y=', y
if (not isOk(data[x][y])):
continue
#print 'x=', x, 'y=', y
G.add_edge(hash % (row,col), hash % (x,y))
print("Nodes\n%s" % G.nodes())
print("Edges\n%s" % G.edges())
# find shortest paths
paths = networkx.shortest_path(G)
for src in paths.keys():
for dest in paths[src].keys():
if len(paths[src][dest]) < plen:
continue
print("Path src=%s to dest=%s\n%s" % (src, dest, paths[src][dest]))
#print("Connected\n%s" % networkx.connected_components(G))
# visualize
networkx.draw(G)
plt.savefig("path.png")
Print for him a path, consisting of a list of positions, starting anywhere in the nucleus, where:
- Each position is empty
- Each successive position is only 1 nm away from the one before it
- The path passes through each position in the nucleus at most once
- The number of positions visited is equal to the length of Danny Dendrite's genome (the starting and ending positions both count).
#
# P.T.
#
# https://dnanexus.com/careers/puzzles
#
#
import networkx # needs ver 1.6
import matplotlib.pyplot as plt
#input
rawData = """5 4 8
oxoo
xoxo
ooxo
xooo
oxox"""
def getNeighbours(row, col, maxRow, maxCol):
""">>> getNeighbours(1,1)
[[1, 0], [1, 2], [0, 1], [2, 1]]
"""
left = [row - 1, col]
right = [row + 1, col]
top = [row, col - 1]
bottom = [row, col + 1]
neighbours = [top, bottom, left, right]
if (top[1] < 0 or top[1] >= maxCol):
neighbours.remove(top)
if bottom[1] < 0 or bottom[1] >= maxCol:
neighbours.remove(bottom)
if left[0] < 0 or left[1] >= maxRow:
neighbours.remove(left)
if right[0] < 0 or right[0] >= maxRow:
neighbours.remove(right)
return neighbours
def isOk(node):
"""'o' isOk, 'x' is not"""
if (node == 'o'):
return True
else:
return False
# parse
#infile = [line.rstrip() for line in open('in').readlines()]
infile = [line.rstrip() for line in rawData.split('\n')]
[nrow, ncol, plen] = infile[0].split(' ')
nrow = int(nrow)
ncol = int(ncol)
plen = int(plen)
data = infile[1:]
# construct graph from input
G = networkx.Graph()
hash = '%s,%s'
print nrow, data, len(data)
assert len(data) == nrow
for row in range(nrow):
line = data[row]
assert len(line) == ncol
for col in range(ncol):
node = data[row][col]
#print 'node=', node, 'row=', row, 'col=', col
if (not isOk(node)):
continue
G.add_node(hash % (row,col))
neighbours = getNeighbours(row, col, nrow, ncol)
#print neighbours
for x,y in neighbours:
#print '?? x=', x, 'y=', y
if (not isOk(data[x][y])):
continue
#print 'x=', x, 'y=', y
G.add_edge(hash % (row,col), hash % (x,y))
print("Nodes\n%s" % G.nodes())
print("Edges\n%s" % G.edges())
# find shortest paths
paths = networkx.shortest_path(G)
for src in paths.keys():
for dest in paths[src].keys():
if len(paths[src][dest]) < plen:
continue
print("Path src=%s to dest=%s\n%s" % (src, dest, paths[src][dest]))
#print("Connected\n%s" % networkx.connected_components(G))
# visualize
networkx.draw(G)
plt.savefig("path.png")
Polychaos dubium is a freshwater amoeboid and one of the larger species of protist.
Polychaos dubium may have the largest genome known for any organism, consisting of 670 billion base pairs of DNA,[6] which is over 200 times larger than the human genome. The authors of one study, however, suggest treating that measurement with caution, because it was taken before the advent of modern genomic methods.[6]
http://en.wikipedia.org/wiki/Polychaos_dubium
http://en.wikipedia.org/wiki/Polychaos_dubium
NetworkX
http://networkx.lanl.gov/
>>> import networkx as nx
>>> G=nx.Graph()
>>> G.add_node("spam")
>>> G.add_edge(1,2)
>>> print(G.nodes())
[1, 2, 'spam']
>>> print(G.edges())
[(1, 2)]
>>> import networkx as nx
>>> G=nx.Graph()
>>> G.add_node("spam")
>>> G.add_edge(1,2)
>>> print(G.nodes())
[1, 2, 'spam']
>>> print(G.edges())
[(1, 2)]
Wednesday, November 30, 2011
nesting commands in xargs
cat links.txt | xargs -I {} sh -c "wget {} | tar czvf {}.tar.gz {}"
or write a for loop
or write xargs command in a separate script
cat links.txt | xargs -I {} myscript.sh {}
http://en.wikipedia.org/wiki/Xargs
http://www.andyd.net/2009/escaping-a-pipe-inside-xargs/
---getAndZip.sh----
URL=$1
FN=`basename $1`
echo URL = $1
echo FN = $FN
wget $URL
tar cvzf $FN.tar.gz $FN
rm $FN
or write a for loop
or write xargs command in a separate script
cat links.txt | xargs -I {} myscript.sh {}
http://en.wikipedia.org/wiki/Xargs
http://www.andyd.net/2009/escaping-a-pipe-inside-xargs/
---getAndZip.sh----
URL=$1
FN=`basename $1`
echo URL = $1
echo FN = $FN
wget $URL
tar cvzf $FN.tar.gz $FN
rm $FN
Monday, November 28, 2011
Android Dev - Silence camera click (needs a rooted phone)
1) Turn On USB Debugging
settings > applications > development
2) Install ADB Tools
http://developer.android.com/guide/developing/tools/adb.html
android-sdk-linux/tools$ ./android
Select 'Android SDK Platform-tools'
adb kill-server
sudo adb start-server
adb devices
http://groups.google.com/group/android-discuss/browse_thread/thread/f85a795644e65b59?pli=1
3) Remove the camera_click.ogg file from your phone.
http://androidforums.com/motorola-droid/30759-turn-off-camera-shutter-sound.html
You must be rooted to do this but you can do this using ADB Shell or Terminal Emulator. Make sure to change /system to RW first.
ADB shell
SU # this requires a rooted phone, else permission denied
mount -o remount,rw /dev/block/mtdblock4 /system
mv /system/media/audio/ui/camera_click.ogg /system/media/audio/ui/camera_click.ogg.old
Done!!! No more Clicking sound
There are a few programs on the market that allow you access the file on root as well through a GUI if your not comfortable using command lines.
settings > applications > development
2) Install ADB Tools
http://developer.android.com/guide/developing/tools/adb.html
android-sdk-linux/tools$ ./android
Select 'Android SDK Platform-tools'
adb kill-server
sudo adb start-server
adb devices
http://groups.google.com/group/android-discuss/browse_thread/thread/f85a795644e65b59?pli=1
3) Remove the camera_click.ogg file from your phone.
http://androidforums.com/motorola-droid/30759-turn-off-camera-shutter-sound.html
You must be rooted to do this but you can do this using ADB Shell or Terminal Emulator. Make sure to change /system to RW first.
ADB shell
SU # this requires a rooted phone, else permission denied
mount -o remount,rw /dev/block/mtdblock4 /system
mv /system/media/audio/ui/camera_click.ogg /system/media/audio/ui/camera_click.ogg.old
Done!!! No more Clicking sound
There are a few programs on the market that allow you access the file on root as well through a GUI if your not comfortable using command lines.
My Brain Notes
http://mybrainnotes.com/memory-brain-stress.html
The amygdala, stress, OCD, and PTSD:
Kindling and stress—how experience affects the brain:
The hippocampus, memory, and depression:
The term hippocampus is derived from the Greek word meaning "sea-horse," which might somehow describe the shape of each hippocampal nucleus,
The amygdala, stress, OCD, and PTSD:
Kindling and stress—how experience affects the brain:
The hippocampus, memory, and depression:
The term hippocampus is derived from the Greek word meaning "sea-horse," which might somehow describe the shape of each hippocampal nucleus,
Wilcoxon rank sum test
> wilcox.test(rnorm(10), rnorm(10, 2), conf.int = TRUE)
Wilcoxon rank sum test
data: rnorm(10) and rnorm(10, 2)
W = 7, p-value = 0.0004871
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
-2.9488832 -0.8543696
sample estimates:
difference in location
-2.002531
Wilcoxon rank sum test
data: rnorm(10) and rnorm(10, 2)
W = 7, p-value = 0.0004871
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
-2.9488832 -0.8543696
sample estimates:
difference in location
-2.002531
R group-by aggregate()
squishes down (by rows)
> x
x gene
Scarb1[2551] -0.005680804 LHX6
Slc41a3[73512484] -0.014839480 SLC41A3
Lhx6[635] -0.001436172 LHX6
Traf7[2527] -0.013320662 TRAF7
Pcyt1b[74641319] -0.027368717 PCYT1B
E330014M11Rik*[77280559] -0.016545674 E330014M11RIK*
> aggregate(x$x, list(x$gene), mean)
Group.1 x
1 E330014M11RIK* -0.016545674
2 LHX6 -0.003558488
3 PCYT1B -0.027368717
4 SLC41A3 -0.014839480
5 TRAF7 -0.013320662
> x
x gene
Scarb1[2551] -0.005680804 LHX6
Slc41a3[73512484] -0.014839480 SLC41A3
Lhx6[635] -0.001436172 LHX6
Traf7[2527] -0.013320662 TRAF7
Pcyt1b[74641319] -0.027368717 PCYT1B
E330014M11Rik*[77280559] -0.016545674 E330014M11RIK*
> aggregate(x$x, list(x$gene), mean)
Group.1 x
1 E330014M11RIK* -0.016545674
2 LHX6 -0.003558488
3 PCYT1B -0.027368717
4 SLC41A3 -0.014839480
5 TRAF7 -0.013320662
Change and acceptance
"The first step toward change is awareness. The second step is acceptance."
--Nathaniel Branden
--Nathaniel Branden
Sunday, November 27, 2011
Courage
"A timid person is frightened before a danger, a coward during the time, and a courageous person afterward."
--Jean Paul Richter
--Jean Paul Richter
Saturday, November 26, 2011
Walking beside
"Don't walk in front of me, I may not follow; don't walk behind me, I may not lead; walk beside me, and just be my friend."
--Albert Camus
--Albert Camus
Friday, November 25, 2011
ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression
ProfileChaser: searching microarray repositories based on genome-wide patterns of differential expression
Summary: We introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.
Availability: http://profilechaser.stanford.edu
Contact: abutte@stanford.edu
Summary: We introduce ProfileChaser, a web server that allows for querying the Gene Expression Omnibus based on genome-wide patterns of differential expression. Using a novel, content-based approach, ProfileChaser retrieves expression profiles that match the differentially regulated transcriptional programs in a user-supplied experiment. This analysis identifies statistical links to similar expression experiments from the vast array of publicly available data on diseases, drugs, phenotypes and other experimental conditions.
Availability: http://profilechaser.stanford.edu
Contact: abutte@stanford.edu
Run over
"Even if you are on the right track, you will get run over if you just sit there."
--Will Rogers
--Will Rogers
Thursday, November 24, 2011
Wednesday, November 23, 2011
Tuesday, November 22, 2011
Wintergreen winter green Gaultheria procumbens
Mitchella repens (Partridge Berry) vs Gaultheria procumbens (winter green)
Mitchella repens , or Partridge Berry,[1][2][3][4] or Squaw Vine, is the best known plant in the genus Mitchella. It is a creeping prostrate herbaceous woody shrub, occurring in North America and Japan, and belonging to the madder family (Rubiaceae).
Prefers well-drained shaded areas.
http://en.wikipedia.org/wiki/Mitchella_repens
http://en.wikipedia.org/wiki/Gaultheria_procumbens
I don't think I would start them indoors. I would start stratifying the seeds in the refregerator, so that mice won't eat tehm. Them I would put them in the ground before the end of winter, and let the seeds decide when to sprout. Wintergreen is native to your climate and it knows exactly when to sprout. The roots will grow exactly the right way for your soil.
http://answers.yahoo.com/question/index?qid=20090920165907AAaUhoa
www.nsl.fs.fed.us/wpsm/Gaultheria.pdf
http://www.herbs2000.com/herbs/herbs_wintergreen.htm
Mitchella repens , or Partridge Berry,[1][2][3][4] or Squaw Vine, is the best known plant in the genus Mitchella. It is a creeping prostrate herbaceous woody shrub, occurring in North America and Japan, and belonging to the madder family (Rubiaceae).
Prefers well-drained shaded areas.
http://en.wikipedia.org/wiki/Mitchella_repens
http://en.wikipedia.org/wiki/Gaultheria_procumbens
I don't think I would start them indoors. I would start stratifying the seeds in the refregerator, so that mice won't eat tehm. Them I would put them in the ground before the end of winter, and let the seeds decide when to sprout. Wintergreen is native to your climate and it knows exactly when to sprout. The roots will grow exactly the right way for your soil.
http://answers.yahoo.com/question/index?qid=20090920165907AAaUhoa
www.nsl.fs.fed.us/wpsm/Gaultheria.pdf
http://www.herbs2000.com/herbs/herbs_wintergreen.htm
UCLA Multimodal Connectivity Database
UCLA Multimodal Connectivity Database
Web-based brain network analysis and data sharing
http://jessebrown.webfactional.com/metrics
Web-based brain network analysis and data sharing
http://jessebrown.webfactional.com/metrics
Brainbow
http://en.wikipedia.org/wiki/Brainbow
Brainbow is a term used to describe the process by which individual neurons in the brain can be distinguished from neighboring neurons using fluorescent proteins. By randomly expressing different ratios of red, green, and blue derivatives of green fluorescent protein in individual neurons, it is possible to flag each neuron with a distinctive color. This process has been a major contribution to the field of connectomics, or the study of neural connections in the brain.
Brainbow is a term used to describe the process by which individual neurons in the brain can be distinguished from neighboring neurons using fluorescent proteins. By randomly expressing different ratios of red, green, and blue derivatives of green fluorescent protein in individual neurons, it is possible to flag each neuron with a distinctive color. This process has been a major contribution to the field of connectomics, or the study of neural connections in the brain.
Monday, November 21, 2011
Principal Component Analysis and Gene Ontology reviews
http://bib.oxfordjournals.org/content/12/6/714.abstract?etoc
Principal component analysis based methods in bioinformatics studies
http://bib.oxfordjournals.org/content/12/6/723.abstract?etoc
The what, where, how and why of gene ontology—a primer for bioinformaticians
Principal component analysis based methods in bioinformatics studies
http://bib.oxfordjournals.org/content/12/6/723.abstract?etoc
The what, where, how and why of gene ontology—a primer for bioinformaticians
Never give in
"Never give in - never, never, never, never, in nothing great or small, large or petty, never give in except to convictions of honour and good sense. Never yield to force; never yield to the apparently overwhelming might of the enemy."
--Winston Churchill
http://en.wikipedia.org/wiki/Winston_Churchill
Sir Winston Leonard Spencer-Churchill, KG, OM, CH, TD, PC, DL, FRS, Hon. RA (30 November 1874 – 24 January 1965) was a predominantly Conservative British politician and statesman known for his leadership of the United Kingdom during the Second World War. He is widely regarded as one of the greatest wartime leaders of the century and served as Prime Minister twice (1940–45 and 1951–55). A noted statesman and orator, Churchill was also an officer in the British Army, a historian, a writer, and an artist. He is the only British prime minister to have received the Nobel Prize in Literature, and was the first person to be made an Honorary Citizen of the United States.
--Winston Churchill
http://en.wikipedia.org/wiki/Winston_Churchill
Sir Winston Leonard Spencer-Churchill, KG, OM, CH, TD, PC, DL, FRS, Hon. RA (30 November 1874 – 24 January 1965) was a predominantly Conservative British politician and statesman known for his leadership of the United Kingdom during the Second World War. He is widely regarded as one of the greatest wartime leaders of the century and served as Prime Minister twice (1940–45 and 1951–55). A noted statesman and orator, Churchill was also an officer in the British Army, a historian, a writer, and an artist. He is the only British prime minister to have received the Nobel Prize in Literature, and was the first person to be made an Honorary Citizen of the United States.
Friday, November 18, 2011
teach and discover
"You cannot teach a man anything; you can only help him discover it in himself."
--Galileo
--Galileo
Gene expression: The dynamics of the brain transcriptome revealed
Gene expression: The dynamics of the brain transcriptome revealed
The tight regulation of gene expression in space and time is key to understanding how the complexity and variation within and between organisms can arise from a relatively simple DNA blueprint. Until now, few studies had been able to characterize the temporal dynamics of gene transcription in the human brain with the depth reported in two recent papers published in Nature.
http://www.nature.com.proxy.lib.sfu.ca/nrn/journal/v12/n12/full/nrn3145.html?WT.ec_id=NRN-201112
The tight regulation of gene expression in space and time is key to understanding how the complexity and variation within and between organisms can arise from a relatively simple DNA blueprint. Until now, few studies had been able to characterize the temporal dynamics of gene transcription in the human brain with the depth reported in two recent papers published in Nature.
http://www.nature.com.proxy.lib.sfu.ca/nrn/journal/v12/n12/full/nrn3145.html?WT.ec_id=NRN-201112
Thursday, November 17, 2011
gmail notify in ubuntu (gm-notify)
http://www.addictivetips.com/ubuntu-linux-tips/gm-notify-displays-gmail-notifications-in-ubuntu-with-bubble-messages/
$ sudo add-apt-repository ppa:gm-notify-maintainers/ppa
$ sudo apt-get update ; sudo apt-get install gm-notify
$ gm-notify.py
$ sudo add-apt-repository ppa:gm-notify-maintainers/ppa
$ sudo apt-get update ; sudo apt-get install gm-notify
$ gm-notify.py
Ubuntu screenlets
$ sudo apt-get install screenlets
Applications > Accessories > Screenlets
$ sudo add-apt-repository ppa:screenlets-dev/ppa
$ sudo apt-get update
googlecalendar-screenlet
http://gnome-look.org/content/show.php?content=125346
Applications > Accessories > Screenlets
$ sudo add-apt-repository ppa:screenlets-dev/ppa
$ sudo apt-get update
googlecalendar-screenlet
http://gnome-look.org/content/show.php?content=125346
Wednesday, November 16, 2011
Adjust par margins par('mar') to that axis labels fit inside the window
Adjust par margins to that axis labels fit inside the window
http://ww2.coastal.edu/kingw/statistics/R-tutorials/graphs.html
We could make the font smaller, but I'm stubborn. I don't wanna! The data labels are printed in the margins of the plotting area, and we can see what those are by querying the "mar" settings...
> par("mar")
[1] 5.1 4.1 4.1 2.1
I don't know the units (and the help page does not give up this info--apparently, it is top secret), but these are respectively the bottom, left, top, and right margin sizes. What we need to do is shift the graph up in the plotting window to make room for the data labels on the x-axis...
> par(mar=c(6.4,4.1,2.7,2.1))
> barplot(data.table, beside=T, axis.lty=1, las=2)
> title(main="Passengers by Class:Titanic")
> title(ylab="Number of Passengers")
-----
data(cars)
heatmap.2(as.matrix(cars), cexCol=1, margins=c(5,5))
http://ww2.coastal.edu/kingw/statistics/R-tutorials/graphs.html
We could make the font smaller, but I'm stubborn. I don't wanna! The data labels are printed in the margins of the plotting area, and we can see what those are by querying the "mar" settings...
> par("mar")
[1] 5.1 4.1 4.1 2.1
I don't know the units (and the help page does not give up this info--apparently, it is top secret), but these are respectively the bottom, left, top, and right margin sizes. What we need to do is shift the graph up in the plotting window to make room for the data labels on the x-axis...
> par(mar=c(6.4,4.1,2.7,2.1))
> barplot(data.table, beside=T, axis.lty=1, las=2)
> title(main="Passengers by Class:Titanic")
> title(ylab="Number of Passengers")
-----
data(cars)
heatmap.2(as.matrix(cars), cexCol=1, margins=c(5,5))
Popup menu gets stuck on screen in ubuntu
menu boxes stuck on screen
http://ubuntuforums.org/showthread.php?t=1602120
System > Preferences > Appearance > Visual Effects > Normal
http://ubuntuforums.org/showthread.php?t=1602120
System > Preferences > Appearance > Visual Effects > Normal
Animated desktop wallpaper
http://tech.shantanugoel.com/projects/linux/shantz-xwinwrap
http://www.ubuntu-unleashed.com/2008/04/howto-loop-movie-or-video-as-desktop.html
Shantz xwinrap
$ nice -n 15 xwinwrap -ni -o 0.20 -fs -s -sp -st -b -nf -- /usr/lib/xscreensaver/glmatrix -root -window-id WID
$ nice -n 15 xwinwrap -ni -o 0.20 -fs -s -sp -st -b -nf -- /usr/lib/xscreensaver/glslideshow -root -window-id WID
$ xwinwrap -ni -fs -s -st -sp -b -nf -- mplayer -wid WID -nosound "Steal This Film II.Xvid.avi" -loop 0
Same videos
http://www.youtube.com/watch?v=s34d6GIqXxQ&feature=related
http://www.youtube.com/watch?v=kJGjueu-s0U&feature=related
Ubuntu themes
LaGaDesk 102 Suite 1.0.0
https://www.ultimateeditionoz.com/forum/viewtopic.php?t=1342&p=9855
http://www.ubuntu-unleashed.com/2008/04/howto-loop-movie-or-video-as-desktop.html
Shantz xwinrap
$ nice -n 15 xwinwrap -ni -o 0.20 -fs -s -sp -st -b -nf -- /usr/lib/xscreensaver/glmatrix -root -window-id WID
$ nice -n 15 xwinwrap -ni -o 0.20 -fs -s -sp -st -b -nf -- /usr/lib/xscreensaver/glslideshow -root -window-id WID
$ xwinwrap -ni -fs -s -st -sp -b -nf -- mplayer -wid WID -nosound "Steal This Film II.Xvid.avi" -loop 0
Same videos
http://www.youtube.com/watch?v=s34d6GIqXxQ&feature=related
http://www.youtube.com/watch?v=kJGjueu-s0U&feature=related
Ubuntu themes
LaGaDesk 102 Suite 1.0.0
https://www.ultimateeditionoz.com/forum/viewtopic.php?t=1342&p=9855
Epigenetic Regulation of Motor Neuron Cell Death through DNA Methylation
Epigenetic Regulation of Motor Neuron Cell Death through DNA Methylation
DNA methylation is an epigenetic mechanism for gene silencing engaged by DNA methyltransferase (Dnmt)-catalyzed methyl group transfer to cytosine residues in gene-regulatory regions. It is unknown whether aberrant DNA methylation can cause neurodegeneration. We tested the hypothesis that Dnmts can mediate neuronal cell death. Enforced expression of Dnmt3a induced degeneration of cultured NSC34 cells. During apoptosis of NSC34 cells induced by camptothecin, levels of Dnmt1 and Dnmt3a increased fivefold and twofold, respectively, and 5-methylcytosine accumulated in nuclei. Truncation mutation of the Dnmt3a catalytic domain and Dnmt3a RNAi blocked apoptosis of cultured neurons. Inhibition of Dnmt catalytic activity with RG108 and procainamide protected cultured neurons from excessive DNA methylation and apoptosis. In vivo, Dnmt1 and Dnmt3a are expressed differentially during mouse brain and spinal cord maturation and in adulthood when Dnmt3a is abundant in synapses and mitochondria. Dnmt1 and Dnmt3a are expressed in motor neurons of adult mouse spinal cord, and, during their apoptosis induced by sciatic nerve avulsion, nuclear and cytoplasmic 5-methylcytosine immunoreactivity, Dnmt3a protein levels and Dnmt enzyme activity increased preapoptotically. Inhibition of Dnmts with RG108 blocked completely the increase in 5-methycytosine and the apoptosis of motor neurons in mice. In human amyotrophic lateral sclerosis (ALS), motor neurons showed changes in Dnmt1, Dnmt3a, and 5-methylcytosine similar to experimental models. Thus, motor neurons can engage epigenetic mechanisms to drive apoptosis, involving Dnmt upregulation and increased DNA methylation. These cellular mechanisms could be relevant to human ALS pathobiology and disease treatment.
DNA methylation is an epigenetic mechanism for gene silencing engaged by DNA methyltransferase (Dnmt)-catalyzed methyl group transfer to cytosine residues in gene-regulatory regions. It is unknown whether aberrant DNA methylation can cause neurodegeneration. We tested the hypothesis that Dnmts can mediate neuronal cell death. Enforced expression of Dnmt3a induced degeneration of cultured NSC34 cells. During apoptosis of NSC34 cells induced by camptothecin, levels of Dnmt1 and Dnmt3a increased fivefold and twofold, respectively, and 5-methylcytosine accumulated in nuclei. Truncation mutation of the Dnmt3a catalytic domain and Dnmt3a RNAi blocked apoptosis of cultured neurons. Inhibition of Dnmt catalytic activity with RG108 and procainamide protected cultured neurons from excessive DNA methylation and apoptosis. In vivo, Dnmt1 and Dnmt3a are expressed differentially during mouse brain and spinal cord maturation and in adulthood when Dnmt3a is abundant in synapses and mitochondria. Dnmt1 and Dnmt3a are expressed in motor neurons of adult mouse spinal cord, and, during their apoptosis induced by sciatic nerve avulsion, nuclear and cytoplasmic 5-methylcytosine immunoreactivity, Dnmt3a protein levels and Dnmt enzyme activity increased preapoptotically. Inhibition of Dnmts with RG108 blocked completely the increase in 5-methycytosine and the apoptosis of motor neurons in mice. In human amyotrophic lateral sclerosis (ALS), motor neurons showed changes in Dnmt1, Dnmt3a, and 5-methylcytosine similar to experimental models. Thus, motor neurons can engage epigenetic mechanisms to drive apoptosis, involving Dnmt upregulation and increased DNA methylation. These cellular mechanisms could be relevant to human ALS pathobiology and disease treatment.
Sensitive Heart
"God's heart is the most sensitive and tender of all. No act goes unnoticed, no matter how insignificant or small."
--Richard J Foster
--Richard J Foster
Tuesday, November 15, 2011
The road to fraud starts with a single step
http://www.nature.com/news/the-road-to-fraud-starts-with-a-single-step-1.9321?WT.ec_id=NEWS-20111115
Diederik Stapel, a social psychologist and author of many published papers, has resigned his position at Tilburg University in the Netherlands after admitting to fabricating data in his research (see Nature 479, 15; 2011).
Such cases of outright fraud in science are distressing for many reasons. For example, they damage the careers of students and collaborators, and raise doubts about all papers by the same author. Most importantly, they damage public trust in science and in scientists. In this case, trust in social psychologists, and the work we do, has been undermined.
To understand fraud in science, the useful lesson is the significance of that first tiny step. Every minor transgression — dropping an inconvenient data point, or failing to give credit where it is due — creates a threat to self-image. The perpetrators are forced to ask themselves: am I really that sort of person? Then, to avoid the discomfort of this threat, they rationalize and justify their way out, until their behaviour feels comfortable and right. This makes the next transgression seem not only easier, but even morally correct.
Diederik Stapel, a social psychologist and author of many published papers, has resigned his position at Tilburg University in the Netherlands after admitting to fabricating data in his research (see Nature 479, 15; 2011).
Such cases of outright fraud in science are distressing for many reasons. For example, they damage the careers of students and collaborators, and raise doubts about all papers by the same author. Most importantly, they damage public trust in science and in scientists. In this case, trust in social psychologists, and the work we do, has been undermined.
To understand fraud in science, the useful lesson is the significance of that first tiny step. Every minor transgression — dropping an inconvenient data point, or failing to give credit where it is due — creates a threat to self-image. The perpetrators are forced to ask themselves: am I really that sort of person? Then, to avoid the discomfort of this threat, they rationalize and justify their way out, until their behaviour feels comfortable and right. This makes the next transgression seem not only easier, but even morally correct.
Music and words
"Music expresses that which cannot be put into words and that which cannot remain silent."
--Victor Hugo
In France, Hugo's literary fame comes first from his poetry but also rests upon his novels and his dramatic achievements. Among many volumes of poetry, Les Contemplations and La Légende des siècles stand particularly high in critical esteem, and Hugo is sometimes identified as the greatest French poet. Outside France, his best-known works are the novels Les Misérables and Notre-Dame de Paris (also known in English as The Hunchback of Notre-Dame).
http://en.wikipedia.org/wiki/Victor_Hugo
--Victor Hugo
In France, Hugo's literary fame comes first from his poetry but also rests upon his novels and his dramatic achievements. Among many volumes of poetry, Les Contemplations and La Légende des siècles stand particularly high in critical esteem, and Hugo is sometimes identified as the greatest French poet. Outside France, his best-known works are the novels Les Misérables and Notre-Dame de Paris (also known in English as The Hunchback of Notre-Dame).
http://en.wikipedia.org/wiki/Victor_Hugo
‘Computational pathologist’ (C-Path) diagnoses different grades of breast cancer
named C-Path, for computational pathologist — developed a new list of features that best predicted patient outcome. Instead of focusing on the tumour cells themselves, C-Path determined that the most predictive features were found in the cells surrounding the tumour, in a region called the stroma. The results were published today in Science Translational Medicine (Beck, A. H. et al. Science Trans. Med. 3, 108ra113 (2011)).
http://www.nature.com/news/the-computer-will-see-you-now-1.9324?WT.ec_id=NEWS-20111115
http://www.nature.com/news/the-computer-will-see-you-now-1.9324?WT.ec_id=NEWS-20111115
Monday, November 14, 2011
Serotype - cell surface antigens
Serotype or serovar refers to distinct variations within a subspecies of bacteria or viruses. These microorganisms, viruses, or cells are classified together based on their cell surface antigens. Determining serotypes, the process of serotyping, can be based on a variety of factors, including virulence, lipopolysaccharides (LPS) in Gram-negative bacteria, presence of an exotoxin (such as pertussis toxin in Bordetella pertussis), plasmids, phages, genetic profile (such as determined by polymerase chain reaction), or other characteristics which differentiate two members of the same species,[1][2] allowing the epidemiologic classification of organisms to the sub-species level.[1][3] A group of serovars with common antigens is called a serogroup.
http://en.wikipedia.org/wiki/Serotype
http://en.wikipedia.org/wiki/Serotype
WGCNA: an R package for weighted correlation network analysis
WGCNA: an R package for weighted correlation network analysis
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA/
Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial.
The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings.
http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA/
Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial.
The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings.
Sunday, November 13, 2011
Ideas and spontaneous
Quote from Steve Jobs: There is a temptation in our networked age to think that ideas can be developed by email and iChat. That is crazy. Creativity comes from spontaneous meetings, from random discussions. You run into someone, you ask what they are doing, you say Wow and soon you are cooking up all sorts of ideas. Unquote
Thursday, November 10, 2011
Life sciences: Biomarkers on the brain * Alla Katsnelson
Life sciences: Biomarkers on the brain
* Alla Katsnelson
Nature
http://www.nature.com/naturejobs/2011/111103/full/nj7371-139a.html?WT.ec_id=NATUREjobs-20111103
joint clinical and research residency in neurochemistry at Sahlgrenska University Hospital at the University of Gothenburg in Sweden
“Biomarkers are really in vivo measurements of the pathology of the disease, so it's an opportunity to investigate the disease mechanisms on a patient level,”
protein biomarkers in the cerebrospinal fluid (CSF)
In the past few years, interest in the discovery and validation of biomarkers for Alzheimer's disease has grown rapidly in both academia and industry. The surge is driven by a growing awareness that disease pathology takes root a decade or more before symptoms of cognitive decline become apparent. The most effective therapies will have to be administered early on, before symptoms are evident — and well validated biological measures will be needed for both diagnosis and prognosis.
Alzheimer's Disease Neuroimaging Initiative (ADNI), is a public–private partnership with researchers at almost 60 institutions in the United States and Canada.
Data-analysis skills are in high demand across biomarker research. Increasingly, researchers are investigating panels of biomarkers rather than single proteins, and studies can involve hundreds or thousands of subjects, each with samples taken at several points over many years.
“Bioinformatics, biostatistics, database handling — those are the most critical skills.”
From lab to therapy
One area of the industry that is hiring, notes Soares, is translational medicine, in which biomarkers are commonly used to help gauge the effectiveness and specificity of a drug candidate as it moves from bench to bedside. Vacancies exist at most pharmaceutical companies, and are generally open to people with MDs, PhDs and pharmacology doctorates, says Soares. Rather than generating biomarker data, these jobs are “more about strategy — how you use the biomarkers to make decisions”.
* Alla Katsnelson
Nature
http://www.nature.com/naturejobs/2011/111103/full/nj7371-139a.html?WT.ec_id=NATUREjobs-20111103
joint clinical and research residency in neurochemistry at Sahlgrenska University Hospital at the University of Gothenburg in Sweden
“Biomarkers are really in vivo measurements of the pathology of the disease, so it's an opportunity to investigate the disease mechanisms on a patient level,”
protein biomarkers in the cerebrospinal fluid (CSF)
In the past few years, interest in the discovery and validation of biomarkers for Alzheimer's disease has grown rapidly in both academia and industry. The surge is driven by a growing awareness that disease pathology takes root a decade or more before symptoms of cognitive decline become apparent. The most effective therapies will have to be administered early on, before symptoms are evident — and well validated biological measures will be needed for both diagnosis and prognosis.
Alzheimer's Disease Neuroimaging Initiative (ADNI), is a public–private partnership with researchers at almost 60 institutions in the United States and Canada.
Data-analysis skills are in high demand across biomarker research. Increasingly, researchers are investigating panels of biomarkers rather than single proteins, and studies can involve hundreds or thousands of subjects, each with samples taken at several points over many years.
“Bioinformatics, biostatistics, database handling — those are the most critical skills.”
From lab to therapy
One area of the industry that is hiring, notes Soares, is translational medicine, in which biomarkers are commonly used to help gauge the effectiveness and specificity of a drug candidate as it moves from bench to bedside. Vacancies exist at most pharmaceutical companies, and are generally open to people with MDs, PhDs and pharmacology doctorates, says Soares. Rather than generating biomarker data, these jobs are “more about strategy — how you use the biomarkers to make decisions”.
Wednesday, November 9, 2011
Mind and rust
"Iron rusts from disuse, stagnant water loses its purity, and in cold weather becomes frozen, even so does inaction sap the vigor of the mind."
--Leonardo da Vinci
--Leonardo da Vinci
Co-expression vs coregulation
From co-expression to co-regulation: how many microarray experiments do we need?
www.ncbi.nlm.nih.gov/pubmed/15239833
The primary thrust of this paper is to provide guidance to
researchers who wish to use cluster analysis of gene expres-
sion data to identify co-regulated genes.
We define co-
expressed genes as genes that share similar expression pat-
terns as discovered by cluster analysis, and we define co-reg-
ulated genes as genes that are regulated by at least one
common known transcription factor.
www.ncbi.nlm.nih.gov/pubmed/15239833
The primary thrust of this paper is to provide guidance to
researchers who wish to use cluster analysis of gene expres-
sion data to identify co-regulated genes.
We define co-
expressed genes as genes that share similar expression pat-
terns as discovered by cluster analysis, and we define co-reg-
ulated genes as genes that are regulated by at least one
common known transcription factor.
Canadian Association for Neuroscience
http://www.can-acn.org/graduate-student-positions
The Association welcomes Canada's investment of up to 100 million dollars in the Canada Brain Research Fund
The purpose of the Canadian Association for Neuroscience shall be:
1- To promote communication among neuroscientists throughout Canada.
2- To represent the interests of Canadian neuroscientists at national and international levels.
3- To promote research in all disciplines contributing to the understanding of the nervous system.
4- To contribute to the advancement of education in the Neurosciences.
5- To provide for and assist in the dissemination to the general public of the results of current Neuroscience research and its significance in relation to health and disease.
6- To raise funds and to provide income for the above purposes.
(CAN-ACN By-laws, Article 6)
The Association welcomes Canada's investment of up to 100 million dollars in the Canada Brain Research Fund
The purpose of the Canadian Association for Neuroscience shall be:
1- To promote communication among neuroscientists throughout Canada.
2- To represent the interests of Canadian neuroscientists at national and international levels.
3- To promote research in all disciplines contributing to the understanding of the nervous system.
4- To contribute to the advancement of education in the Neurosciences.
5- To provide for and assist in the dissemination to the general public of the results of current Neuroscience research and its significance in relation to health and disease.
6- To raise funds and to provide income for the above purposes.
(CAN-ACN By-laws, Article 6)
A role for insulator elements in the regulation of gene expression response to hypoxia
A role for insulator elements in the regulation of
gene expression response to hypoxia
http://nar.oxfordjournals.org/content/early/2011/11/07/nar.gkr842.abstract?keytype=ref&ijkey=KuQt2Hy5oAv7jK8
Maria Tiana1,2, Diego Villar1, Eva Perez-Guijarro1, Laura Gomez-Maldonado1,
Eduardo Molto , Ana Fernandez-Minan , Jose Luis Gomez-Skarmeta4,
Lluıs Montoliu and Luis del Peso *
In vertebrates, several regulatory
elements including CTCF binding motifs (36–38),
repetitive elements, [such as ALUs (39), SINE B2 (29)
and SINE B1 (30)] and scaffold/matrix-attachment
regions [S/MARs; (40,41)], have been shown to function
as insulators (25,42).
Thus, the insula-
tor activity described herein could be mediated by S/MAR
elements.
Elnitski bidirectional promoters’ prediction track
gene expression response to hypoxia
http://nar.oxfordjournals.org/content/early/2011/11/07/nar.gkr842.abstract?keytype=ref&ijkey=KuQt2Hy5oAv7jK8
Maria Tiana1,2, Diego Villar1, Eva Perez-Guijarro1, Laura Gomez-Maldonado1,
Eduardo Molto , Ana Fernandez-Minan , Jose Luis Gomez-Skarmeta4,
Lluıs Montoliu and Luis del Peso *
In vertebrates, several regulatory
elements including CTCF binding motifs (36–38),
repetitive elements, [such as ALUs (39), SINE B2 (29)
and SINE B1 (30)] and scaffold/matrix-attachment
regions [S/MARs; (40,41)], have been shown to function
as insulators (25,42).
Thus, the insula-
tor activity described herein could be mediated by S/MAR
elements.
Elnitski bidirectional promoters’ prediction track
Tuesday, November 8, 2011
Allen Institute for Brain Science YouTube Channel
http://www.youtube.com/user/AllenInstitute#p/u
Tom Daniel
University of Washington
Sensorimotor control of movement: Even the circuits of little brains accomplish complex tasks
Michale Fee
Massachusetts Institute of Technology
Prime movers of the brain: Localizing neural circuits that drive complex motor behaviors
Itzhak Fried
University of California, Los Angeles; Tel-Aviv University, Israel
Neurons as will and representation: Recordings from the human brain
Nathaniel Heintz
The Rockefeller University; Howard Hughes Medical Institute
Genetic dissection of the mouse brain: Toward a 21st century brain pharmacology
Leah Krubitzer
University of California, Davis
How does evolution build a complex brain?
Markus Meister
Harvard University
Neural computation in the retina
Dharmendra S. Modha
IBM Research, Almaden
Cognitive computing: Neuroscience, supercomputing, nanotechnology
Sacha B. Nelson
Brandeis University
Defining the mammalian neurome
Richard Palmiter
University of Washington; Howard Hughes Medical Institute
Deciphering a neural circuit controlling anorexia in the mouse
Tomaso Poggio
Massachusetts Institute of Technology
The computational magic of the ventral stream: A theory
Sharad Ramanathan
Harvard University
Discovering circuits that control fate choices in embryonic stem cells
R. Clay Reid
Harvard Medical School
Functional and structural imaging of cortical circuits
Eric Schadt
Pacific Biosciences
A systems framework for understanding the complexity of living systems
Idan Segev
The Hebrew University, Jerusalem
Design principles for dendritic inhibition
Terry Sejnowski
Salk Institute; University of California, San Diego; Howard Hughes Medical Institute
A new view of the neuropil
Pamela Sklar
Mount Sinai School of Medicine
Genomics and psychiatry
Michael P. Stryker
University of California, San Francisco
Rewiring the cortex
Giulio Tononi
University of Wisconsin, Madison
Sleep function and synaptic homeostasis
Hongkui Zeng
Allen Institute for Brain Science
Genetic approaches for brain circuit dissection and connectivity mapping
http://www.alleninstitute.org/events/symposium/index.html
Tom Daniel
University of Washington
Sensorimotor control of movement: Even the circuits of little brains accomplish complex tasks
Michale Fee
Massachusetts Institute of Technology
Prime movers of the brain: Localizing neural circuits that drive complex motor behaviors
Itzhak Fried
University of California, Los Angeles; Tel-Aviv University, Israel
Neurons as will and representation: Recordings from the human brain
Nathaniel Heintz
The Rockefeller University; Howard Hughes Medical Institute
Genetic dissection of the mouse brain: Toward a 21st century brain pharmacology
Leah Krubitzer
University of California, Davis
How does evolution build a complex brain?
Markus Meister
Harvard University
Neural computation in the retina
Dharmendra S. Modha
IBM Research, Almaden
Cognitive computing: Neuroscience, supercomputing, nanotechnology
Sacha B. Nelson
Brandeis University
Defining the mammalian neurome
Richard Palmiter
University of Washington; Howard Hughes Medical Institute
Deciphering a neural circuit controlling anorexia in the mouse
Tomaso Poggio
Massachusetts Institute of Technology
The computational magic of the ventral stream: A theory
Sharad Ramanathan
Harvard University
Discovering circuits that control fate choices in embryonic stem cells
R. Clay Reid
Harvard Medical School
Functional and structural imaging of cortical circuits
Eric Schadt
Pacific Biosciences
A systems framework for understanding the complexity of living systems
Idan Segev
The Hebrew University, Jerusalem
Design principles for dendritic inhibition
Terry Sejnowski
Salk Institute; University of California, San Diego; Howard Hughes Medical Institute
A new view of the neuropil
Pamela Sklar
Mount Sinai School of Medicine
Genomics and psychiatry
Michael P. Stryker
University of California, San Francisco
Rewiring the cortex
Giulio Tononi
University of Wisconsin, Madison
Sleep function and synaptic homeostasis
Hongkui Zeng
Allen Institute for Brain Science
Genetic approaches for brain circuit dissection and connectivity mapping
http://www.alleninstitute.org/events/symposium/index.html
Jay Bradner: Open-source cancer research
http://www.ted.com/talks/jay_bradner_open_source_cancer_research.html
And so please consider this a work in progress, but I'd like to tell you today a story about a very rare cancer called midline carcinoma, about the protein target, the undruggable protein target that causes this cancer, called BRD4, and about a molecule developed at my lab at Dana Farber Cancer Institute called JQ1, which we affectionately named for Jun Qi, the chemist that made this molecule. Now BRD4 is an interesting protein.
And so please consider this a work in progress, but I'd like to tell you today a story about a very rare cancer called midline carcinoma, about the protein target, the undruggable protein target that causes this cancer, called BRD4, and about a molecule developed at my lab at Dana Farber Cancer Institute called JQ1, which we affectionately named for Jun Qi, the chemist that made this molecule. Now BRD4 is an interesting protein.
Saturday, November 5, 2011
Navit for Android, the completely free and offline Navigation system for Android
Navit for Android, the completely free and offline Navigation system for Android
Navit for Android is an open source (GPL) car navigation system.
It will display your position on a map (in bird-view mode or as a 3D "visualization") from GPS sensor data, and can provide precise route calculation, touch screen functionality and supports Points of Interest (POI).
Unlike other navigation systems, Navit maps are dynamically generated in real time from vector data.
Navit is completly offline and works without an internet connection.
Features:
*) Navigate to target from google maps
*) works offline
*) spoken directions in many languages
*) uptodate OSM maps
https://market.android.com/details?id=org.navitproject.navit&hl=en
http://wiki.openstreetmap.org/wiki/Android
Navit for Android is an open source (GPL) car navigation system.
It will display your position on a map (in bird-view mode or as a 3D "visualization") from GPS sensor data, and can provide precise route calculation, touch screen functionality and supports Points of Interest (POI).
Unlike other navigation systems, Navit maps are dynamically generated in real time from vector data.
Navit is completly offline and works without an internet connection.
Features:
*) Navigate to target from google maps
*) works offline
*) spoken directions in many languages
*) uptodate OSM maps
https://market.android.com/details?id=org.navitproject.navit&hl=en
http://wiki.openstreetmap.org/wiki/Android
Curiosity and spark
"Awaken people's curiosity. It is enough to open minds, do not overload them. Put there just a spark."
--Anatole France
--Anatole France
Friday, November 4, 2011
Google updates search engine for fresher results
Google has overhauled the way it serves up results in response to search queries.
The update is designed to work out whether a person wants up-to-date results or historical data.
The US firm estimated the alterations to its core algorithm would make a difference to about 35% of searches.
http://www.bbc.co.uk/news/technology-15590285
The update is designed to work out whether a person wants up-to-date results or historical data.
The US firm estimated the alterations to its core algorithm would make a difference to about 35% of searches.
http://www.bbc.co.uk/news/technology-15590285
Thursday, November 3, 2011
‘Rich club’ of 12 rule the human brain
http://www.jpost.com/Health/Article.aspx?id=244150
http://www.jneurosci.org/content/31/44/15775
“If we wanted to look for consciousness in the brain, I would bet on it turning out to be this rich club,” he said.
Best connected of all is the precuneus, an area at the back of the brain. Van den Heuvel says its function is not well understood, but thinks that it acts as an "integrator region" collating high-level information from all over the brain.
The “rich club” comprises of six pairs of identical regions, with one of each pair in each hemisphere of the brain and the best connected of all is the precuneus, an area at the back of the brain.
http://www.jneurosci.org/content/31/44/15775
“If we wanted to look for consciousness in the brain, I would bet on it turning out to be this rich club,” he said.
Best connected of all is the precuneus, an area at the back of the brain. Van den Heuvel says its function is not well understood, but thinks that it acts as an "integrator region" collating high-level information from all over the brain.
The “rich club” comprises of six pairs of identical regions, with one of each pair in each hemisphere of the brain and the best connected of all is the precuneus, an area at the back of the brain.
CPSC 310 Software Engineering: A practical introduction (2011 Winter Term 1)
http://www.ugrad.cs.ubc.ca/~cs310/
Introduction to Software Development: Specification, design, implementation and maintenance of large, multi-module software systems. Principles, techniques, methodologies and tools for computer aided software engineering (CASE); human-computer interfaces, reactive systems, hardware-software interfaces and distributed applications.
When you complete this course, you should be able to:
* Explain the technical and interpersonal challenges of software development
* Communicate technical matters with programmers, managers, and clients effectively
* Perform the activities of software development effectively, using up-to-date methodologies or tools
Introduction to Software Development: Specification, design, implementation and maintenance of large, multi-module software systems. Principles, techniques, methodologies and tools for computer aided software engineering (CASE); human-computer interfaces, reactive systems, hardware-software interfaces and distributed applications.
When you complete this course, you should be able to:
* Explain the technical and interpersonal challenges of software development
* Communicate technical matters with programmers, managers, and clients effectively
* Perform the activities of software development effectively, using up-to-date methodologies or tools
Nature Special issue on neuroscience: The autism enigma
Special issue on neuroscience: The autism enigma
http://www.nature.com/news/2011/111102/full/479021a.html
http://www.nature.com/nature/journal/v479/n7371/full/479033a.html
Changing perceptions: The power of autism
Scientists, too, should do more than simply study autistic deficits. By emphasizing the abilities and strengths of people with autism, deciphering how autistics learn and succeed in natural settings, and avoiding language that frames autism as a defect to be corrected, they can help shape the entire discussion.
http://www.nature.com/news/2011/111102/full/479021a.html
http://www.nature.com/nature/journal/v479/n7371/full/479033a.html
Changing perceptions: The power of autism
Scientists, too, should do more than simply study autistic deficits. By emphasizing the abilities and strengths of people with autism, deciphering how autistics learn and succeed in natural settings, and avoiding language that frames autism as a defect to be corrected, they can help shape the entire discussion.
Wednesday, November 2, 2011
PDF CDF
http://en.wikipedia.org/wiki/Hypergeometric_distribution
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of k successes in n draws from a finite population without replacement. (cf. the binomial distribution, which describes the probability of k successes in n draws with replacement.)
Hypergeometric calculator
http://stattrek.com/tables/hypergeometric.aspx
http://www.six-sigma-material.com/Hypergeometric-Distribution.html
Assumptions
# Discrete distribution.
# Population, N, is finite and a known value.
# Two outcomes - call them SUCCESS (S) and FAILURE (F).
# Number of successes in the population is known, S.
# Used when sample size,n, is greater than or equal to 5% of N.
# Trials are done without replacement, dependent.
http://www.mathworks.com/help/toolbox/stats/hygecdf.html
hygecdf - Hypergeometric cumulative distribution function
Example
Suppose you have a lot of 100 floppy disks and you know that 20 of them are defective. What is the probability of drawing 0 through 5 defective floppy disks if you select 10 at random?
In Matlab:
p = hygepdf(0:5,100,20,10)
p =
0.0951 0.2679 0.3182 0.2092 0.0841 0.0215
In R:
> library('stats')
> dhyper(0:5,20,80,10)
[1] 0.09511627 0.26793316 0.31817063 0.20920809 0.08410730 0.02153147
> phyper(0:5,20,80,10) # CDF, at most 5
[1] 0.09511627 0.36304943 0.68122006 0.89042815 0.97453545 0.99606692
> 1-phyper(5,20,80,10) # at least 6
[1] 0.003933076
http://www.youtube.com/watch?v=1xQ4r2gcW3c
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of k successes in n draws from a finite population without replacement. (cf. the binomial distribution, which describes the probability of k successes in n draws with replacement.)
Hypergeometric calculator
http://stattrek.com/tables/hypergeometric.aspx
http://www.six-sigma-material.com/Hypergeometric-Distribution.html
Assumptions
# Discrete distribution.
# Population, N, is finite and a known value.
# Two outcomes - call them SUCCESS (S) and FAILURE (F).
# Number of successes in the population is known, S.
# Used when sample size,n, is greater than or equal to 5% of N.
# Trials are done without replacement, dependent.
http://www.mathworks.com/help/toolbox/stats/hygecdf.html
hygecdf - Hypergeometric cumulative distribution function
Example
Suppose you have a lot of 100 floppy disks and you know that 20 of them are defective. What is the probability of drawing 0 through 5 defective floppy disks if you select 10 at random?
In Matlab:
p = hygepdf(0:5,100,20,10)
p =
0.0951 0.2679 0.3182 0.2092 0.0841 0.0215
In R:
> library('stats')
> dhyper(0:5,20,80,10)
[1] 0.09511627 0.26793316 0.31817063 0.20920809 0.08410730 0.02153147
> phyper(0:5,20,80,10) # CDF, at most 5
[1] 0.09511627 0.36304943 0.68122006 0.89042815 0.97453545 0.99606692
> 1-phyper(5,20,80,10) # at least 6
[1] 0.003933076
http://www.youtube.com/watch?v=1xQ4r2gcW3c
Picking advisors and committee members
RNA-editing Exome vs Transcriptome
http://milospjanic.blogspot.com/2011/08/widespread-sequence-differences-between.html
Editing events were more common in 3ÚTR exons then in other exons.
Exome - DNA, protein-coding mutations, mendelian disease
Transcriptome - mRNA, alternative splicing, expression
Editing events were more common in 3ÚTR exons then in other exons.
Exome - DNA, protein-coding mutations, mendelian disease
Transcriptome - mRNA, alternative splicing, expression
Libreoffice over OpenOffice
LibreOffice is like OpenOffice. Only OpenOffice was acquired by Oracle and later released under Apache Software Foundation and lags a bit in terms of features. For example, LibreOffice has the insert table / chart / video icon in the middle, lines seem to be straighter, but it still has the same problem of missing second-level bullet points when opening .PPT ...
http://joesteiger.com/2011/03/23/install-libreoffice-ubuntu-10-10/
# NOTE: This will uninstall openoffice because libreoffice does not play with it!
sudo apt-get purge openoffice*.*
sudo add-apt-repository ppa:libreoffice/ppa
sudo apt-get update
sudo apt-get install libreoffice libreoffice-gnome language-support-en
http://joesteiger.com/2011/03/23/install-libreoffice-ubuntu-10-10/
# NOTE: This will uninstall openoffice because libreoffice does not play with it!
sudo apt-get purge openoffice*.*
sudo add-apt-repository ppa:libreoffice/ppa
sudo apt-get update
sudo apt-get install libreoffice libreoffice-gnome language-support-en
Human brain and Complexity
“If the human brain were so simple that we could understand it, we would be so simple that we couldn't.”
—Emerson Pugh (in The Biological Origin of Human Values)
—Emerson Pugh (in The Biological Origin of Human Values)
Prejudice and Humanity
"I have no color prejudices nor caste prejudices nor creed prejudices. All I care to know is that a man is a human being, and that is enough for me; he can't be any worse."
--Mark Twain
--Mark Twain
Tuesday, November 1, 2011
Generate Factor Levels
> gl(2, 8, labels = c("Control", "Treat"))
[1] Control Control Control Control Control Control Control Control Treat
[10] Treat Treat Treat Treat Treat Treat Treat
Levels: Control Treat
> ?gl
> gl(2, 1, 20)
[1] 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
Levels: 1 2
[1] Control Control Control Control Control Control Control Control Treat
[10] Treat Treat Treat Treat Treat Treat Treat
Levels: Control Treat
> ?gl
> gl(2, 1, 20)
[1] 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2
Levels: 1 2
Neurons
http://psychology.about.com/od/biopsychology/f/neuron01.htm
Unlike other body cells, neurons stop reproducing shortly after birth. Because of this, some parts of the brain have more neurons at birth than later in life because neurons die but are not replaced. While neurons do not reproduce, research has shown that new connections between neurons form throughout life.
It is estimated that there are 10 to 50 times more glial cells than there are neurons in the brain.
Neurotransmitters
Acetylcholine: Associated with memory, muscle contractions, and learning. A lack of acetylcholine in the brain is associated with Alzheimer’s disease.
Endorphins: Associated with emotions and pain perception. The body releases endorphins in response to fear or trauma. These chemical messengers are similar to opiate drugs such as morphine, but are significantly stronger.
Dopamine: Associated with thought and pleasurable feelings. Parkinson’s disease is one illness associated with deficits in dopamine, while schizophrenia is strongly linked to excessive amounts of this chemical messenger.
Unlike other body cells, neurons stop reproducing shortly after birth. Because of this, some parts of the brain have more neurons at birth than later in life because neurons die but are not replaced. While neurons do not reproduce, research has shown that new connections between neurons form throughout life.
It is estimated that there are 10 to 50 times more glial cells than there are neurons in the brain.
Neurotransmitters
Acetylcholine: Associated with memory, muscle contractions, and learning. A lack of acetylcholine in the brain is associated with Alzheimer’s disease.
Endorphins: Associated with emotions and pain perception. The body releases endorphins in response to fear or trauma. These chemical messengers are similar to opiate drugs such as morphine, but are significantly stronger.
Dopamine: Associated with thought and pleasurable feelings. Parkinson’s disease is one illness associated with deficits in dopamine, while schizophrenia is strongly linked to excessive amounts of this chemical messenger.
Monday, October 31, 2011
Using the T-Coffee package to build multiple sequence alignments of protein, RNA, DNA sequences and 3D structures
http://www.nature.com/nprot/journal/v6/n11/full/nprot.2011.393.html?WT.ec_id=NPROT-201111
T-Coffee (Tree-based consistency objective function for alignment evaluation) is a versatile multiple sequence alignment (MSA) method suitable for aligning most types of biological sequences. The main strength of T-Coffee is its ability to combine third party aligners and to integrate structural (or homology) information when building MSAs. The series of protocols presented here show how the package can be used to multiply align proteins, RNA and DNA sequences. The protein section shows how users can select the most suitable T-Coffee mode for their data set. Detailed protocols include T-Coffee, the default mode, M-Coffee, a meta version able to combine several third party aligners into one, PSI (position-specific iterated)-Coffee, the homology extended mode suitable for remote homologs and Expresso, the structure-based multiple aligner. We then also show how the T-RMSD (tree based on root mean square deviation) option can be used to produce a functionally informative structure-based clustering. RNA alignment procedures are described for using R-Coffee, a mode able to use predicted RNA secondary structures when aligning RNA sequences. DNA alignments are illustrated with Pro-Coffee, a multiple aligner specific of promoter regions. We also present some of the many reformatting utilities bundled with T-Coffee. The package is an open-source freeware available from http://www.tcoffee.org/.
T-Coffee (Tree-based consistency objective function for alignment evaluation) is a versatile multiple sequence alignment (MSA) method suitable for aligning most types of biological sequences. The main strength of T-Coffee is its ability to combine third party aligners and to integrate structural (or homology) information when building MSAs. The series of protocols presented here show how the package can be used to multiply align proteins, RNA and DNA sequences. The protein section shows how users can select the most suitable T-Coffee mode for their data set. Detailed protocols include T-Coffee, the default mode, M-Coffee, a meta version able to combine several third party aligners into one, PSI (position-specific iterated)-Coffee, the homology extended mode suitable for remote homologs and Expresso, the structure-based multiple aligner. We then also show how the T-RMSD (tree based on root mean square deviation) option can be used to produce a functionally informative structure-based clustering. RNA alignment procedures are described for using R-Coffee, a mode able to use predicted RNA secondary structures when aligning RNA sequences. DNA alignments are illustrated with Pro-Coffee, a multiple aligner specific of promoter regions. We also present some of the many reformatting utilities bundled with T-Coffee. The package is an open-source freeware available from http://www.tcoffee.org/.
Sunday, October 30, 2011
Unsupervised Feature Learning and Deep Learning
http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=ufldl
Course Description
Machine learning has seen numerous successes, but applying learning algorithms today often means spending a long time hand-engineering the input feature representation. This is true for many problems in vision, audio, NLP, robotics, and other areas. In this course, you'll learn about methods for unsupervised feature learning and deep learning, which automatically learn a good representation of the input from unlabeled data. You'll also pick up the "hands-on," practical skills and tricks-of-the-trade needed to get these algorithms to work well.
Basic knowledge of machine learning (supervised learning) is assumed, though we'll quickly review logistic regression and gradient descent.
I. INTRODUCTION
II. LOGISTIC REGRESSION
Representation(1.5x)
Batch gradient descent(1.2x)(1.5x)
Gradient descent in practice(1.2x)(1.5x)
Stochastic gradient descent
Exponentially weighted average
Shuffling data
Exercise 1: Implementation
III. NEURAL NETWORKS
Representation
Architecture
Examples and intuitions #1(1.2x)
Examples and intuitions #2
Parameter learning
Gradient checking
Random initialization
Vectorized implementation
Activation function derivative
V. APPLICATION TO CLASSIFICATION
IV. UNSUPERVISED FEATURE LEARNING and SELF-TAUGHT LEARNING
V. APPLICATION TO CLASSIFICATION
VI. DEEP LEARNING WITH AUTOENCODERS
VII. SPARSE REPRESENTATIONS
VIII. WHITENING
IX. INDEPENDENT COMPONENTS ANALYSIS (ICA)
X. SLOW FEATURE ANALYSIS (SFA)
XI. RESTRICTED BOLTZMANN MACHINES (RBM)
XII. DEEP BELIEF NETWORKS (DBN)
Course Description
Machine learning has seen numerous successes, but applying learning algorithms today often means spending a long time hand-engineering the input feature representation. This is true for many problems in vision, audio, NLP, robotics, and other areas. In this course, you'll learn about methods for unsupervised feature learning and deep learning, which automatically learn a good representation of the input from unlabeled data. You'll also pick up the "hands-on," practical skills and tricks-of-the-trade needed to get these algorithms to work well.
Basic knowledge of machine learning (supervised learning) is assumed, though we'll quickly review logistic regression and gradient descent.
I. INTRODUCTION
II. LOGISTIC REGRESSION
Representation(1.5x)
Batch gradient descent(1.2x)(1.5x)
Gradient descent in practice(1.2x)(1.5x)
Stochastic gradient descent
Exponentially weighted average
Shuffling data
Exercise 1: Implementation
III. NEURAL NETWORKS
Representation
Architecture
Examples and intuitions #1(1.2x)
Examples and intuitions #2
Parameter learning
Gradient checking
Random initialization
Vectorized implementation
Activation function derivative
V. APPLICATION TO CLASSIFICATION
IV. UNSUPERVISED FEATURE LEARNING and SELF-TAUGHT LEARNING
V. APPLICATION TO CLASSIFICATION
VI. DEEP LEARNING WITH AUTOENCODERS
VII. SPARSE REPRESENTATIONS
VIII. WHITENING
IX. INDEPENDENT COMPONENTS ANALYSIS (ICA)
X. SLOW FEATURE ANALYSIS (SFA)
XI. RESTRICTED BOLTZMANN MACHINES (RBM)
XII. DEEP BELIEF NETWORKS (DBN)
Confidence
http://www.nlp-secrets.com/nlp-confidence.php
Adopt an open posture. No crossed legs or folded arms.
Make your neck tall and shoulders relaxed, as if you were trying to see over a wall that was very slightly taller than your eye level. Like a meerkat who is looking for a predator. You know what I mean.
Speak clearly and with volume, remember what you're saying is worth hearing.
Don't take yourself too seriously, humour is the most universal language and can help prevent conflict with alpha-male and attention-envy types.
Don't be judgemental to others - but let yourself be open to judgement from others. This relaxes people around you, and helps bring down the barriers between you.
http://www.theprovince.com/Speak+loudly+speak+clearly/3217061/story.html
Coming across as confident is often a result of two things -- body language and tone of voice. No doubt you already know about sitting up straight and making eye contact to show confidence, therefore I am going to focus on how your tone of voice can get you that next job.
Your tone of voice has a big effect on how people are going to both perceive you and respond to you. In fact, your tone of voice is more important than the words you choose; it says to people, "This is how I am really feeling."
-Practise speaking in a slightly lower octave; deeper voices have more credibility than higher-pitched voices.
-Pause before saying a meaningful word or idea you are sharing to emphasize its importance.
-Pronounce every word; don't mumble.
-Record your voice and listen to it.
http://cstudies.ubc.ca/academic-english-support-program/courses.html
Adopt an open posture. No crossed legs or folded arms.
Make your neck tall and shoulders relaxed, as if you were trying to see over a wall that was very slightly taller than your eye level. Like a meerkat who is looking for a predator. You know what I mean.
Speak clearly and with volume, remember what you're saying is worth hearing.
Don't take yourself too seriously, humour is the most universal language and can help prevent conflict with alpha-male and attention-envy types.
Don't be judgemental to others - but let yourself be open to judgement from others. This relaxes people around you, and helps bring down the barriers between you.
http://www.theprovince.com/Speak+loudly+speak+clearly/3217061/story.html
Coming across as confident is often a result of two things -- body language and tone of voice. No doubt you already know about sitting up straight and making eye contact to show confidence, therefore I am going to focus on how your tone of voice can get you that next job.
Your tone of voice has a big effect on how people are going to both perceive you and respond to you. In fact, your tone of voice is more important than the words you choose; it says to people, "This is how I am really feeling."
-Practise speaking in a slightly lower octave; deeper voices have more credibility than higher-pitched voices.
-Pause before saying a meaningful word or idea you are sharing to emphasize its importance.
-Pronounce every word; don't mumble.
-Record your voice and listen to it.
http://cstudies.ubc.ca/academic-english-support-program/courses.html
e-Books should be free
http://www.booksshouldbefree.com/
Free Audio Books from the public domain
Download a free audiobook in mp3, iPod, or iTunes format
Free Audio Books from the public domain
Download a free audiobook in mp3, iPod, or iTunes format
Friday, October 28, 2011
ToppGene Suite - gene list enrichment analysis and candidate gene prioritization
http://toppgene.cchmc.org/
* ToppFun: Transcriptome, ontology, phenotype, proteome, and pharmacome annotations based gene list functional enrichment analysis
Detect functional enrichment of your gene list based on Transcriptome, Proteome, Regulome (TFBS and miRNA), Ontologies (GO, Pathway), Phenotype (human disease and mouse phenotype), Pharmacome (Drug-Gene associations), literature co-citation, and other features.
* ToppGene: Candidate gene prioritization
Prioritize or rank candidate genes based on functional similarity to training gene list.
* ToppNet: Relative importance of candidate genes in networks
Prioritize or rank candidate genes based on topological features in protein-protein interaction network.
* ToppGenet: Prioritization of neighboring genes in protein-protein interaction network
Identify and prioritize the neighboring genes of the seeds in protein-protein interaction network based on functional similarity to the "seed" list (ToppGene) or topological features in protein-protein interaction network (ToppNet).
* ToppFun: Transcriptome, ontology, phenotype, proteome, and pharmacome annotations based gene list functional enrichment analysis
Detect functional enrichment of your gene list based on Transcriptome, Proteome, Regulome (TFBS and miRNA), Ontologies (GO, Pathway), Phenotype (human disease and mouse phenotype), Pharmacome (Drug-Gene associations), literature co-citation, and other features.
* ToppGene: Candidate gene prioritization
Prioritize or rank candidate genes based on functional similarity to training gene list.
* ToppNet: Relative importance of candidate genes in networks
Prioritize or rank candidate genes based on topological features in protein-protein interaction network.
* ToppGenet: Prioritization of neighboring genes in protein-protein interaction network
Identify and prioritize the neighboring genes of the seeds in protein-protein interaction network based on functional similarity to the "seed" list (ToppGene) or topological features in protein-protein interaction network (ToppNet).
Ten Simple Rules for Teaching Bioinformatics at the High School Level
Ten Simple Rules for Teaching Bioinformatics at the High School Level
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002243
Checklist
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002243
Checklist
- Am I energized to be enthusiastic about this class?
- Is the classroom arranged properly for the day's activities?
- Is my name, course title, and number on the chalkboard?
- Do I have an ice-breaker planned?
- Do I have a way to start leaming names?
- Do I have a way to gather information on student backgrounds, interests, expectations for the course, questions, concerns?
- Is the syllabus complete and clear?
- Have I outlined how students will be evaluated?
- Do I have announcements of needed information ready?
- Do I have a way of gathering student feedback?
- When the class is over; will students want to come back? Will you want to come back?
Ten Simple Rules for Getting involved in your scientific community
Ten Simple Rules for Getting involved in your scientific community
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002232
Activities such as organizing conferences and workshops, answering questions and discussing scientific ideas online, contributing to a scientific blog, or participating in open source software projects are typically thought of as outside classic research activity. Having scientists involved in those activities, however, is very important for the community to be dynamic and to promote fruitful discussions and collaborations.
encourage your colleagues to play an active role in the scientific community
want to maintain a balance with the activities directly related to your research projects
remember that you are not alone
If you know why you are doing it and if you enjoy it, you will take the time to do it, and you will do it well
http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002232
Activities such as organizing conferences and workshops, answering questions and discussing scientific ideas online, contributing to a scientific blog, or participating in open source software projects are typically thought of as outside classic research activity. Having scientists involved in those activities, however, is very important for the community to be dynamic and to promote fruitful discussions and collaborations.
encourage your colleagues to play an active role in the scientific community
want to maintain a balance with the activities directly related to your research projects
remember that you are not alone
If you know why you are doing it and if you enjoy it, you will take the time to do it, and you will do it well
Wednesday, October 26, 2011
Quanta Plus -- XML Editor for Ubuntu
Quanta Plus -- XML Editor for Ubuntu
# select all descendants of node parent
/parent/*//
http://www.tizag.com/xmlTutorial/xpathdescendant.php
$ sudo apt-get install python-4suite-xml
$ 4xpath --string book.xml /catalog/book/author
Result (XPath string):
======================
Gambardella, Matthew
http://www.whitebeam.org/library/guide/TechNotes/xpathtestbed.rhtm
Simply Python code
http://stackoverflow.com/questions/8692/how-to-use-xpath-in-python
import libxml2
doc = libxml2.parseFile('foo.xml')
for url in doc.xpathEval('//@Url'):
print url.content
# select all descendants of node parent
/parent/*//
http://www.tizag.com/xmlTutorial/xpathdescendant.php
$ sudo apt-get install python-4suite-xml
$ 4xpath --string book.xml /catalog/book/author
Result (XPath string):
======================
Gambardella, Matthew
http://www.whitebeam.org/library/guide/TechNotes/xpathtestbed.rhtm
Simply Python code
http://stackoverflow.com/questions/8692/how-to-use-xpath-in-python
import libxml2
doc = libxml2.parseFile('foo.xml')
for url in doc.xpathEval('//@Url'):
print url.content
Tuesday, October 25, 2011
Peter Norvig - The Unreasonable Effectiveness of Data
http://www.youtube.com/watch?v=yvDCzhbjYWs
Collect data, use probability (Baye's Rule) to write some simple code / model, and let the data do all the work.
good vs bad data, over-time, you might pickup your own data?
word sense disambiguation
spelling correction
translation
Collect data, use probability (Baye's Rule) to write some simple code / model, and let the data do all the work.
good vs bad data, over-time, you might pickup your own data?
word sense disambiguation
spelling correction
translation
Brown Bag Lunch
This discussion was sparked by a question: "ideas for a short (e.g. 45min) brown bag lunch type session, aiming to share information about a particular piece of work ongoing within a large (newly formed) team,in a way that encourages discussion and thought about potential internal synergies, during the lunch break."
* Called ‘Brown Bag’ because people often bring their food in one, the term refers to informal discussions around a topic (eg ongoing research, first ideas for a project) at lunch time, with lunch brought (or sometimes provided). In an organization, some lunchtime meetings are catered, while in others you're expected to bring your own lunch. For organizers, a nice way to set the expectation that no lunch will be served is to call it a 'brown bag'. That way, participants will bring their own. The equivalent in South Asia might be a 'tiffin box' lunch!).
http://wiki.km4dev.org/wiki/index.php/Brown_Bag_Lunches
* Called ‘Brown Bag’ because people often bring their food in one, the term refers to informal discussions around a topic (eg ongoing research, first ideas for a project) at lunch time, with lunch brought (or sometimes provided). In an organization, some lunchtime meetings are catered, while in others you're expected to bring your own lunch. For organizers, a nice way to set the expectation that no lunch will be served is to call it a 'brown bag'. That way, participants will bring their own. The equivalent in South Asia might be a 'tiffin box' lunch!).
http://wiki.km4dev.org/wiki/index.php/Brown_Bag_Lunches
Differentially Expressed Genes in Major Depression Reside on the Periphery of Resilient Gene Coexpression Networks
However, we found that the small-world connectivity characteristics of coexpression networks are resilient to the effects of depression (and of other neuropsychiatric diseases), and that the related pathology is not mediated by network disintegration via attack on hub nodes.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166821/?tool=pubmed
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3166821/?tool=pubmed
Monday, October 24, 2011
Free Android Apps
Tripso
Complete up to date travel guides for over 8000 destinations Triposo is the most comprehensive guide available.
Triposo apps don’t need an internet connection, even the detailed maps are all stored on your device.
WhatsApp - WhatsApp Messenger is a cross-platform mobile messaging app which allows you to exchange messages without having to pay for SMS
http://www.whatsapp.com/download/
Call Meter NG - Keep track of your mobile voice / data / text bills
http://www.appbrain.com/app/de.ub0r.de.android.callMeterNG
Offline Browser - save webpage
123clip
save webpage
Deionized
Google shopper
Nauseous
Angry Bird
http://lgp500.wordpress.com/2011/05/24/top-8-best-android-must-have-apps/
http://shrewdgeek.com/2011/10/17/10-must-have-applications-for-lg-optimus-one-p500/
Custom Rom - CyanogenMod 7.1.0 (Android 2.3.7)
http://forum.xda-developers.com/showthread.php?t=946354
For Optimus One running official 2.3.3, root using SuperOneClick.
Why install custom ROM?
http://www.androidpolice.com/2010/05/01/custom-roms-for-android-explained-and-why-you-want-them/
Super Manager - File manager, Remove stock applications
Benefits of rooting
http://sachinchavan.in/2010/12/how-to-root-android-lg-optimus-one-p500-india/
Titanium Backup
ClockworkMod ROM Manager
http://www.appbrain.com/app/com.koushikdutta.rommanager
GingerBreak (works on LG OPTIMUS ONE V 2.2.2)
http://www.manast.com/2011/04/30/how-to-root-lg-optimus-one-p500-using-gingerbreak/
Z4Root (use Permanent Root) (or use GingerBreak-v1.20.apk)
http://rainulf.ca/androidtag.html (for Telus, P500H, Android firmware v2.2 NOT 2.2.1)
- Enable USB debugging from Menu->Settings->Applications->Development->USB Debugging.
- Make sure the versions / firmware eg. V10B are correct (To find out, go to Settings, then About Phone)
http://lgoptimusonep500.blogspot.com/2010/12/rooting-lg-optimus-one-p500.html
Telus V10S stock:
http://forum.xda-developers.com/showthread.php?t=844483
http://forum.xda-developers.com/showthread.php?t=1001713
http://androidforums.com/getitnowmarketing/330813-all-one-recovery-thread.html
How to Root LG Optimus One
http://androidos.in/2010/12/how-to-root-lg-optimus-one-remove-unwanted-apps/
Opera Mini
https://market.android.com/details?id=com.opera.mini.android&hl=en
Adobe Reader
Bluetooth File Transfer
https://market.android.com/details?id=it.medieval.blueftp
MoboPlayer
https://market.android.com/details?id=com.clov4r.android.nil
Advanced Task Killer (Free)
https://market.android.com/details?id=com.rechild.advancedtaskkiller
Barcode Scanner
https://market.android.com/details?id=com.google.zxing.client.android
Dolphin Browser™ HD (Play Flash)
https://market.android.com/details?id=mobi.mgeek.TunnyBrowser&feature=related_apps#?t=W251bGwsMSwxLDEwOSwibW9iaS5tZ2Vlay5UdW5ueUJyb3dzZXIiXQ..
Skyfire - (Play Flash) Skyfire Browser makes your mobile web experience richer, smarter and more fun!
Skyfire is the world’s smartest & most social mobile browser!
https://market.android.com/details?id=com.skyfire.browser&hl=en
AdFree Android - removes all ads
https://market.android.com/details?id=com.bigtincan.android.adfree&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5iaWd0aW5jYW4uYW5kcm9pZC5hZGZyZWUiXQ..
Android System Info - Explore all features of your android device!
https://market.android.com/details?id=com.electricsheep.asi&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5lbGVjdHJpY3NoZWVwLmFzaSJd
App 2 SD Free (move app to SD) - Are you running out of application storage?
https://market.android.com/details?id=com.a0soft.gphone.app2sd&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5hMHNvZnQuZ3Bob25lLmFwcDJzZCJd
Easy Uninstaller - Simplist & fastest uninstall tool for android.
https://market.android.com/details?id=mobi.infolife.uninstaller&feature=search_result#?t=W251bGwsMSwxLDEsIm1vYmkuaW5mb2xpZmUudW5pbnN0YWxsZXIiXQ..
Spare Parts Plus! - Allows you to enable and change some hidden settings of your Android device.
https://market.android.com/details?id=com.androidapps.spare_parts&feature=related_apps
RockPlayer - RockPlayer is high performance, almost all formats media player with a lot of functions
https://market.android.com/details?id=com.redirectin.rockplayer.android.unified.lite&hl=en
Complete up to date travel guides for over 8000 destinations Triposo is the most comprehensive guide available.
Triposo apps don’t need an internet connection, even the detailed maps are all stored on your device.
WhatsApp - WhatsApp Messenger is a cross-platform mobile messaging app which allows you to exchange messages without having to pay for SMS
http://www.whatsapp.com/download/
Call Meter NG - Keep track of your mobile voice / data / text bills
http://www.appbrain.com/app/de.ub0r.de.android.callMeterNG
Offline Browser - save webpage
123clip
save webpage
Deionized
Google shopper
Nauseous
Angry Bird
http://lgp500.wordpress.com/2011/05/24/top-8-best-android-must-have-apps/
http://shrewdgeek.com/2011/10/17/10-must-have-applications-for-lg-optimus-one-p500/
Custom Rom - CyanogenMod 7.1.0 (Android 2.3.7)
http://forum.xda-developers.com/showthread.php?t=946354
For Optimus One running official 2.3.3, root using SuperOneClick.
Why install custom ROM?
http://www.androidpolice.com/2010/05/01/custom-roms-for-android-explained-and-why-you-want-them/
Super Manager - File manager, Remove stock applications
Benefits of rooting
http://sachinchavan.in/2010/12/how-to-root-android-lg-optimus-one-p500-india/
Titanium Backup
ClockworkMod ROM Manager
http://www.appbrain.com/app/com.koushikdutta.rommanager
GingerBreak (works on LG OPTIMUS ONE V 2.2.2)
http://www.manast.com/2011/04/30/how-to-root-lg-optimus-one-p500-using-gingerbreak/
Z4Root (use Permanent Root) (or use GingerBreak-v1.20.apk)
http://rainulf.ca/androidtag.html (for Telus, P500H, Android firmware v2.2 NOT 2.2.1)
- Enable USB debugging from Menu->Settings->Applications->Development->USB Debugging.
- Make sure the versions / firmware eg. V10B are correct (To find out, go to Settings, then About Phone)
http://lgoptimusonep500.blogspot.com/2010/12/rooting-lg-optimus-one-p500.html
Telus V10S stock:
http://forum.xda-developers.com/showthread.php?t=844483
http://forum.xda-developers.com/showthread.php?t=1001713
http://androidforums.com/getitnowmarketing/330813-all-one-recovery-thread.html
How to Root LG Optimus One
http://androidos.in/2010/12/how-to-root-lg-optimus-one-remove-unwanted-apps/
Opera Mini
https://market.android.com/details?id=com.opera.mini.android&hl=en
Adobe Reader
Bluetooth File Transfer
https://market.android.com/details?id=it.medieval.blueftp
MoboPlayer
https://market.android.com/details?id=com.clov4r.android.nil
Advanced Task Killer (Free)
https://market.android.com/details?id=com.rechild.advancedtaskkiller
Barcode Scanner
https://market.android.com/details?id=com.google.zxing.client.android
Dolphin Browser™ HD (Play Flash)
https://market.android.com/details?id=mobi.mgeek.TunnyBrowser&feature=related_apps#?t=W251bGwsMSwxLDEwOSwibW9iaS5tZ2Vlay5UdW5ueUJyb3dzZXIiXQ..
Skyfire - (Play Flash) Skyfire Browser makes your mobile web experience richer, smarter and more fun!
Skyfire is the world’s smartest & most social mobile browser!
https://market.android.com/details?id=com.skyfire.browser&hl=en
AdFree Android - removes all ads
https://market.android.com/details?id=com.bigtincan.android.adfree&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5iaWd0aW5jYW4uYW5kcm9pZC5hZGZyZWUiXQ..
Android System Info - Explore all features of your android device!
https://market.android.com/details?id=com.electricsheep.asi&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5lbGVjdHJpY3NoZWVwLmFzaSJd
App 2 SD Free (move app to SD) - Are you running out of application storage?
https://market.android.com/details?id=com.a0soft.gphone.app2sd&feature=search_result#?t=W251bGwsMSwxLDEsImNvbS5hMHNvZnQuZ3Bob25lLmFwcDJzZCJd
Easy Uninstaller - Simplist & fastest uninstall tool for android.
https://market.android.com/details?id=mobi.infolife.uninstaller&feature=search_result#?t=W251bGwsMSwxLDEsIm1vYmkuaW5mb2xpZmUudW5pbnN0YWxsZXIiXQ..
Spare Parts Plus! - Allows you to enable and change some hidden settings of your Android device.
https://market.android.com/details?id=com.androidapps.spare_parts&feature=related_apps
RockPlayer - RockPlayer is high performance, almost all formats media player with a lot of functions
https://market.android.com/details?id=com.redirectin.rockplayer.android.unified.lite&hl=en
Ectopic expression
Ectopic expression is the expression of a gene in an abnormal place in an organism. This can be caused by a disease, or it can be artificially produced as a way to help determine what the function of that gene is.
http://en.wikipedia.org/wiki/Ectopic_expression
Similar gene expression profiles do not imply similar tissue functions
Although similarities in gene expression among tissues are commonly inferred to reflect functional constraints, this has never been formally tested. Furthermore, it is unclear which evolutionary processes are responsible for the observed similarities. When examining genome-wide expression data in mouse, we found that patterns of expression similarity between tissues extend to genes that are unlikely to function in the tissues. Thus, ectopic expression can seem coordinated across tissues. This indicates that knowledge of gene expression patterns per se is insufficient to infer gene function. Ectopic expression is possibly explained as expression leakage, caused by spreading of chromatin modifications or the transcription apparatus into neighboring genes.
http://www.sciencedirect.com/science/article/pii/S0168952506000254
http://en.wikipedia.org/wiki/Ectopic_expression
Similar gene expression profiles do not imply similar tissue functions
Although similarities in gene expression among tissues are commonly inferred to reflect functional constraints, this has never been formally tested. Furthermore, it is unclear which evolutionary processes are responsible for the observed similarities. When examining genome-wide expression data in mouse, we found that patterns of expression similarity between tissues extend to genes that are unlikely to function in the tissues. Thus, ectopic expression can seem coordinated across tissues. This indicates that knowledge of gene expression patterns per se is insufficient to infer gene function. Ectopic expression is possibly explained as expression leakage, caused by spreading of chromatin modifications or the transcription apparatus into neighboring genes.
http://www.sciencedirect.com/science/article/pii/S0168952506000254
Sunday, October 23, 2011
Normalize music volume recursively with mp3gain
$ find -name "*.mp3" -print0 | xargs -0 mp3gain -r
xargs -0 - correctly handles files with spaces
xargs -0 - correctly handles files with spaces
Saturday, October 22, 2011
Call landline
Call landline
http://www.androidauthority.com/top-best-free-calls-android-phones-voip-19829/
Fring
Skype
http://www.androidauthority.com/top-best-free-calls-android-phones-voip-19829/
Fring
Skype
Gene set enrichment analysis made simple (GSEA) MADE SIMPLE
GENE SET ENRICHMENT ANALYSIS MADE SIMPLE
Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.
There are currently two major types of procedure for incorporating biological knowledge into
differential expression analysis. We will refer to these as the over-representation and the aggregate
score approaches.
Over-representation analysis can be summarized as follows: First, form a list of candidate
genes using the marginal approach. Then, for each gene set, we create a two-by-two table compar-
ing the number of candidate genes that are members of the category to those that are not members.
The significance of over-representation can be assessed, for example, using the hypergeometric
distribution or its binomial approximation.
A limitation of the over-representation approach is that it ignores all the genes that did not
make the list of candidate genes.
The aggregate score approach (eg. GSEA), does not have this limitation. The basic idea
is to assign scores to each gene set based on all the gene-specific scores for that gene set.
In this paper we compare GSEA to the one sample z-test and χ2 -test
http://www.bepress.com/jhubiostat/paper185/
that 7 or so genes is
sufficient to uniquely determine a gene set, -- Jesse
Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.
There are currently two major types of procedure for incorporating biological knowledge into
differential expression analysis. We will refer to these as the over-representation and the aggregate
score approaches.
Over-representation analysis can be summarized as follows: First, form a list of candidate
genes using the marginal approach. Then, for each gene set, we create a two-by-two table compar-
ing the number of candidate genes that are members of the category to those that are not members.
The significance of over-representation can be assessed, for example, using the hypergeometric
distribution or its binomial approximation.
A limitation of the over-representation approach is that it ignores all the genes that did not
make the list of candidate genes.
The aggregate score approach (eg. GSEA), does not have this limitation. The basic idea
is to assign scores to each gene set based on all the gene-specific scores for that gene set.
In this paper we compare GSEA to the one sample z-test and χ2 -test
http://www.bepress.com/jhubiostat/paper185/
that 7 or so genes is
sufficient to uniquely determine a gene set, -- Jesse
Hypergeometric (draws w/o replacement) and Binomial / Bernoulli (draws with replacement) distributions
In probability theory and statistics, the binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p. Such a success/failure experiment is also called a Bernoulli experiment or Bernoulli trial; when n = 1, the binomial distribution is a Bernoulli distribution. The Binomial distribution is an n times repeated Bernoulli trial. The binomial distribution is the basis for the popular binomial test of statistical significance.
The binomial distribution is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N. If the sampling is carried out without replacement, the draws are not independent and so the resulting distribution is a hypergeometric distribution, not a binomial one. However, for N much larger than n, the binomial distribution is a good approximation, and widely used.
http://en.wikipedia.org/wiki/Binomial_distribution
http://en.wikipedia.org/wiki/Hypergeometric_distribution
http://stattrek.com/online-calculator/hypergeometric.aspx
Draw 5 cards from the deck, what are the chances that 4 are red?
> tot <- 52; m <- 26; n <- tot-m; k <- 5; q <- 4; dhyper(q,m,n,k)
[1] 0.1495598
> tot <- 52; m <- 26; n <- tot-m; k <- 5; q <- 4; phyper(q,m,n,k)
[1] 0.9746899
The binomial distribution is frequently used to model the number of successes in a sample of size n drawn with replacement from a population of size N. If the sampling is carried out without replacement, the draws are not independent and so the resulting distribution is a hypergeometric distribution, not a binomial one. However, for N much larger than n, the binomial distribution is a good approximation, and widely used.
http://en.wikipedia.org/wiki/Binomial_distribution
http://en.wikipedia.org/wiki/Hypergeometric_distribution
http://stattrek.com/online-calculator/hypergeometric.aspx
Draw 5 cards from the deck, what are the chances that 4 are red?
> tot <- 52; m <- 26; n <- tot-m; k <- 5; q <- 4; dhyper(q,m,n,k)
[1] 0.1495598
> tot <- 52; m <- 26; n <- tot-m; k <- 5; q <- 4; phyper(q,m,n,k)
[1] 0.9746899
Subscribe to:
Posts (Atom)