- Awareness. The trouble with filler words is that we are completely unaware that we’re using them. My filler word when I first started training was, “okay.” I probably said “okay” fifteen times every ten minutes. During my first week with ExecuTrain, I was video taped and told to watch for the “okay’s.” I was dumbfounded! I couldn’t believe how many times I used that word.
- Practice and persistence. Once I became aware of the problem, I started hearing it myself while it was happening. For the next few weeks, when I was teaching a class, I would make a mark on a sheet of paper every time I heard myself say, “okay.” Just doing that immediately reduced the number of times I used it and eventually eliminated it all together. Then I started marking other filler words until I had them all eliminated.
- Silence. Instead of saying Um, say nothing. It’s okay to take a moment to stop and think. What you don’t realize is how little time it takes your brain to process all the information it needs and come back with an intelligent response. When I was video taped in college during a teaching presentation, I had what I thought were several long pauses. I was embarrassed and thought my professor would take points off for them. When I watched the video, I was amazed at how little time actually passed while I was thinking of an appropriate answer to a question posed by someone from my audience.
- Substitution. If you need to look something up, say so. If you don’t know the answer to a question off the top of your head, instead of saying, “Uh,” say, “I’m not sure; let me look that up for you.” No one expects you to know everything about everything. In fact, most of us get annoyed with people who pretend to know everything!
Thursday, September 30, 2010
Filler words ('Uhhmmm') when presenting
Thesis and Dissertations
http://ir.lib.sfu.ca/handle/1892/112
https://circle.ubc.ca/handle/2429/24
http://resources.library.ubc.ca/841/
https://circle.ubc.ca/handle/2429/24
http://resources.library.ubc.ca/841/
Installing R and JGR in Ubuntu Intrepid
Installing R and JGR in Ubuntu Intrepid
Here’s an update to my previous instructions on getting R set up and working in Ubuntu. These work for Ubuntu Intrepid, but won’t work for Ubuntu Jaunty (due out next month) until you see “jaunty” in this list.R is a free, open source software package for performing statistical analyses. It is an alternative to commercial tools such as SPSS, SAS, and S. I recommend using the RSeek search engine to search for help and 3rd party libraries.
To install R, open the Terminal console and run these commands:
gpg --keyserver subkeys.pgp.net --recv-key E2A11821Then open up your apt-get sources list for editing:
gpg -a --export E2A11821 | sudo apt-key add -
sudo gedit /etc/apt/sources.listAdd this line to the bottom of the sources.list file:
deb http://rh-mirror.linux.iastate.edu/CRAN/bin/linux/ubuntu intrepid/Note the trailing slash at the end of “intrepid/”. Also you can replace “rh-mirror.linux.iastate.edu” with another mirror server of your choice. Save the file and go back to the Terminal.
Now type this in the terminal to update apt-get’s database before you install R:
sudo apt-get updateInstall R with this command:
sudo apt-get install r-base r-base-dev r-recommendedThen run “R” to start R, and “q()” to quit it.
To get JGR, the Java GUI interface working (requires you have java installed, see the sun-java6 package), run this on the command line:
sudo R CMD javareconf
Wednesday, September 29, 2010
Riboswitches
http://en.wikipedia.org/wiki/Riboswitch
Riboswitches are often conceptually divided into two parts: an aptamer and an expression platform. The aptamer directly binds the small molecule, and the expression platform undergoes structural changes in response to the changes in the aptamer. The expression platform is what regulates gene expression.
Expression platforms typically turn off gene expression in response to the small molecule, but some turn it on. The following riboswitch mechanisms have been experimentally demonstrated.
http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi.1000823
Transat—A Method for Detecting the Conserved Helices of Functional RNA Structures, Including Transient, Pseudo-Knotted and Alternative Structures
Nicholas J. P. Wiebe, Irmtraud M. Meyer
One sequence can have multiple RNA secondary structures, transient structures
Riboswitches are often conceptually divided into two parts: an aptamer and an expression platform. The aptamer directly binds the small molecule, and the expression platform undergoes structural changes in response to the changes in the aptamer. The expression platform is what regulates gene expression.
Expression platforms typically turn off gene expression in response to the small molecule, but some turn it on. The following riboswitch mechanisms have been experimentally demonstrated.
http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi.1000823
Transat—A Method for Detecting the Conserved Helices of Functional RNA Structures, Including Transient, Pseudo-Knotted and Alternative Structures
Nicholas J. P. Wiebe, Irmtraud M. Meyer
- predict evolutionarily conserved helices that are likely to play a role in the co-transcriptional formation of the functional RNA structure(s) in vivo
- do not require a detailed knowledge of the in vivo environment, e.g. transcriptional speed, ion concentrations, interaction partners etc., and keep the number of free parameters and assumptions incorporated into the method to a minimum
- estimate reliability values for all predictions
- present a comprehensive performance evaluation
- have a performance which is robust with respect to sequence length
Motivation.
If a structural feature is functionally important, it is typically well conserved in groups of related RNAs, even if the level of primary sequence conservation may be low.One sequence can have multiple RNA secondary structures, transient structures
Sunday, September 26, 2010
The Nuclear-Retained Noncoding RNA MALAT1 Regulates Alternative Splicing by Modulating SR Splicing Factor Phosphorylation
http://www.sciencedaily.com/releases/2010/09/100923162412.htm?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+sciencedaily+(ScienceDaily%3A+Latest+Science+News)
http://www.cell.com/molecular-cell/retrieve/pii/S1097276510006210
Researchers report this month that MALAT1, a long non-coding RNA that is implicated in certain cancers, regulates pre-mRNA splicing -- a critical step in the earliest stage of protein production. Their study appears in the journal Molecular Cell.
http://www.cell.com/molecular-cell/retrieve/pii/S1097276510006210
Researchers report this month that MALAT1, a long non-coding RNA that is implicated in certain cancers, regulates pre-mRNA splicing -- a critical step in the earliest stage of protein production. Their study appears in the journal Molecular Cell.
Stack vs Heap memory space
http://en.wikipedia.org/wiki/Stack-based_memory_allocation
In most modern computer systems, each thread has a reserved region of memory referred to as its stack. When a function executes, it may add some of its state data to the top of the stack; when the function exits it is responsible for removing that data from the stack. At a minimum, a thread's stack is used to store the location of function calls in order to allow return statements to return to the correct location, but programmers may further choose to explicitly use the stack. If a region of memory lies on the thread's stack, that memory is said to have been allocated on the stack.
Because the data is added and removed in a last-in-first-out manner, stack allocation is very simple and typically faster than heap-based memory allocation (also known as dynamic memory allocation). Another feature is that memory on the stack is automatically, and very efficiently, reclaimed when the function exits, which can be convenient for the programmer if the data is no longer required. If however, the data needs to be kept in some form, then it must be copied from the stack before the function exits. Therefore, stack based allocation is suitable for temporary data or data which is no longer required after the creating function exits.
A disadvantage of stack-based memory allocation is that a thread's stack size can be as small as a few dozen kilobytes. Allocating more memory on the stack than is available can result in a crash due to stack overflow.
In most modern computer systems, each thread has a reserved region of memory referred to as its stack. When a function executes, it may add some of its state data to the top of the stack; when the function exits it is responsible for removing that data from the stack. At a minimum, a thread's stack is used to store the location of function calls in order to allow return statements to return to the correct location, but programmers may further choose to explicitly use the stack. If a region of memory lies on the thread's stack, that memory is said to have been allocated on the stack.
Because the data is added and removed in a last-in-first-out manner, stack allocation is very simple and typically faster than heap-based memory allocation (also known as dynamic memory allocation). Another feature is that memory on the stack is automatically, and very efficiently, reclaimed when the function exits, which can be convenient for the programmer if the data is no longer required. If however, the data needs to be kept in some form, then it must be copied from the stack before the function exits. Therefore, stack based allocation is suitable for temporary data or data which is no longer required after the creating function exits.
A disadvantage of stack-based memory allocation is that a thread's stack size can be as small as a few dozen kilobytes. Allocating more memory on the stack than is available can result in a crash due to stack overflow.
microRNAs: Master Regulators as Potential Therapeutics in Cancer
microRNAs: Master Regulators as Potential Therapeutics in Cancer
Michela Garofalo and Carlo M. Croce
Department of Molecular Virology, Immunology and Medical Genetics and Comprehensive
Cancer Center, Ohio State University, Columbus, Ohio 43210;
email: michela.garofalo@osumc.edu, carlo.croce@osumc.edu
http://www.annualreviews.org/doi/abs/10.1146/annurev-pharmtox-010510-100517
Cell. 2009 Jan 23;136(2):215-33.
MicroRNAs: target recognition and regulatory functions.
Bartel DP.
http://www.ncbi.nlm.nih.gov/pubmed/19167326
http://download.cell.com/pdf/PIIS0092867409000087.pdf
Many miRNAs have been shown to function as oncogenes in the majority of cancers profiled to date (Table 1). miR-155 was one of the first described (30).
miR-155, miR-21, miR-221&222, miR-106b-93-25 cluster, miR-17-92 cluster
The tumor suppressor function of miR-15a/16-1 has also been addressed
in vivo.
The most promising therapeutic techniques tested to date are
(a) miRNA mimics and (b) anti-miRNA oligonucleotides (AMOs).
http://www.youtube.com/watch?v=oANi7PRqalM
TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs
Ming Lu1 Bing Shi1,2 Juan Wang1 Qun Cao1 Qinghua Cui1
http://www.biomedcentral.com/1471-2105/11/419
TargetSpy: a supervised machine learning approach for microRNA target prediction
Martin Sturm1 Michael Hackenberg2 David Langenberger3,4 Dmitrij Frishman1,4
http://www.biomedcentral.com/1471-2105/11/292
Michela Garofalo and Carlo M. Croce
Department of Molecular Virology, Immunology and Medical Genetics and Comprehensive
Cancer Center, Ohio State University, Columbus, Ohio 43210;
email: michela.garofalo@osumc.edu, carlo.croce@osumc.edu
http://www.annualreviews.org/doi/abs/10.1146/annurev-pharmtox-010510-100517
Cell. 2009 Jan 23;136(2):215-33.
MicroRNAs: target recognition and regulatory functions.
Bartel DP.
http://www.ncbi.nlm.nih.gov/pubmed/19167326
http://download.cell.com/pdf/PIIS0092867409000087.pdf
Many miRNAs have been shown to function as oncogenes in the majority of cancers profiled to date (Table 1). miR-155 was one of the first described (30).
miR-155, miR-21, miR-221&222, miR-106b-93-25 cluster, miR-17-92 cluster
The tumor suppressor function of miR-15a/16-1 has also been addressed
in vivo.
The most promising therapeutic techniques tested to date are
(a) miRNA mimics and (b) anti-miRNA oligonucleotides (AMOs).
http://www.youtube.com/watch?v=oANi7PRqalM
TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs
Ming Lu1 Bing Shi1,2 Juan Wang1 Qun Cao1 Qinghua Cui1
http://www.biomedcentral.com/1471-2105/11/419
TargetSpy: a supervised machine learning approach for microRNA target prediction
Martin Sturm1 Michael Hackenberg2 David Langenberger3,4 Dmitrij Frishman1,4
http://www.biomedcentral.com/1471-2105/11/292
Genomewide Association Studies and Assessment of the Risk of Disease
http://www.nejm.org/doi/full/10.1056/NEJMra0905980
Nearly 600 genomewide association studies covering 150 distinct diseases and traits have been published, with nearly 800 SNP–trait associations reported as significant (P<5×10−8)
Approximately 40% of trait-associated SNPs fall in intergenic regions, and another 40% are located in noncoding introns. These two findings have sharpened the focus on the potential roles of intronic, and particularly intergenic, regions in regulating gene expression. 1
Although intronic and intergenic SNPs are not overrepresented in associations as compared with randomly selected SNPs, they account for the great majority — more than 80% — of associated SNPs.
Given the lack of good representation of SNPs with a prevalence of less than 5% in current genomewide association arrays, a comprehensive catalogue of SNPs with a prevalence of 1 to 5% is being generated by the 1000 Genomes Project55 for potential inclusion in fine-mapping efforts and expanded genomewide association arrays. In the project's pilot effort, more than 11 million novel SNPs have been identified in what was initially low-depth coverage of 172 persons.
Annotation catalogues (maps of functions of variants), such as those related to transcription-factor binding (promoting gene expression) or to RNA interference (silencing genes), are currently in development and should facilitate the identification of functional variants underlying genomewide association signals.57
The importance of structural variation, including copy-number variants, inversions, and translocations, is an active area of investigation; several structural variants underlie genomewide association signals for autism, schizophrenia, Crohn's disease, and obesity.
For the prediction of complex diseases, genotypes at multiple SNPs are often combined into scores calculated according to the number of risk alleles carried, which is the approach that Kathiresan and colleagues used in predicting the risk of cardiovascular disease on the basis of nine SNPs associated with cholesterol levels
What is becoming clear from these early attempts at genetically based risk assessment is that currently known variants explain too little about the risk of disease occurrence to be of clinically useful predictive value.
Possible clinical uses of predictive scores — for example, in deciding which patients should be screened more intensively for breast cancer with the use of mammography69 or for statin-induced myopathy with the use of muscle enzyme assays70 — will require rigorous, preferably prospective, evaluation before being accepted into clinical practice.
The ability to assess risk for 120 conditions at the same time also raises the concern that predictive models will yield conflicting recommendations; if implemented, they could reduce a person's risk for development of one condition and exacerbate the risk for development of another.
Patients inquiring about genomewide association testing should be advised that at present the results of such testing have no value in predicting risk and are not clinically directive.
Much more remains to be learned about how variations in intronic and intergenic regions (where the vast majority of SNP–trait associations reside) influence gene expression, protein coding, and disease phenotypes.
The substantial challenges of incorporating such research into clinical care must be pursued if the potential of genomic medicine is to be realized.
Hardy J, Singleton A. Genomewide association studies and human disease. N Engl J Med 2009;360:1759-1768 Full Text | Web of Science | Medline http://www.ncbi.nlm.nih.gov/pubmed/19369657
http://www.sfu.ca/~chenn/2010.html
Nearly 600 genomewide association studies covering 150 distinct diseases and traits have been published, with nearly 800 SNP–trait associations reported as significant (P<5×10−8)
Approximately 40% of trait-associated SNPs fall in intergenic regions, and another 40% are located in noncoding introns. These two findings have sharpened the focus on the potential roles of intronic, and particularly intergenic, regions in regulating gene expression. 1
Although intronic and intergenic SNPs are not overrepresented in associations as compared with randomly selected SNPs, they account for the great majority — more than 80% — of associated SNPs.
Given the lack of good representation of SNPs with a prevalence of less than 5% in current genomewide association arrays, a comprehensive catalogue of SNPs with a prevalence of 1 to 5% is being generated by the 1000 Genomes Project55 for potential inclusion in fine-mapping efforts and expanded genomewide association arrays. In the project's pilot effort, more than 11 million novel SNPs have been identified in what was initially low-depth coverage of 172 persons.
Annotation catalogues (maps of functions of variants), such as those related to transcription-factor binding (promoting gene expression) or to RNA interference (silencing genes), are currently in development and should facilitate the identification of functional variants underlying genomewide association signals.57
The importance of structural variation, including copy-number variants, inversions, and translocations, is an active area of investigation; several structural variants underlie genomewide association signals for autism, schizophrenia, Crohn's disease, and obesity.
For the prediction of complex diseases, genotypes at multiple SNPs are often combined into scores calculated according to the number of risk alleles carried, which is the approach that Kathiresan and colleagues used in predicting the risk of cardiovascular disease on the basis of nine SNPs associated with cholesterol levels
What is becoming clear from these early attempts at genetically based risk assessment is that currently known variants explain too little about the risk of disease occurrence to be of clinically useful predictive value.
Possible clinical uses of predictive scores — for example, in deciding which patients should be screened more intensively for breast cancer with the use of mammography69 or for statin-induced myopathy with the use of muscle enzyme assays70 — will require rigorous, preferably prospective, evaluation before being accepted into clinical practice.
The ability to assess risk for 120 conditions at the same time also raises the concern that predictive models will yield conflicting recommendations; if implemented, they could reduce a person's risk for development of one condition and exacerbate the risk for development of another.
Patients inquiring about genomewide association testing should be advised that at present the results of such testing have no value in predicting risk and are not clinically directive.
Much more remains to be learned about how variations in intronic and intergenic regions (where the vast majority of SNP–trait associations reside) influence gene expression, protein coding, and disease phenotypes.
The substantial challenges of incorporating such research into clinical care must be pursued if the potential of genomic medicine is to be realized.
Hardy J, Singleton A. Genomewide association studies and human disease. N Engl J Med 2009;360:1759-1768 Full Text | Web of Science | Medline http://www.ncbi.nlm.nih.gov/pubmed/19369657
http://www.sfu.ca/~chenn/2010.html
6 comments
Glad to know that at least 6 ppl had read my posts ^_^.
In the blog, go to Design and there's the comments tab. Another cool thing is the Stats tab. I was pretty amazed that most users use IE on Windows from Russia! Welcome! приветствовать
In the blog, go to Design and there's the comments tab. Another cool thing is the Stats tab. I was pretty amazed that most users use IE on Windows from Russia! Welcome! приветствовать
Logarithmic transformation
http://www.statsdirect.com/help/data_preparation/log_trans.htm
Effects of log transformation:
* Variance stabilisation.
* Increasing slopes in x in relation to another variable are linearized.
* Positively skewed distributions of x are normalized.
The function named Log (natural) calculates the natural (Naperian, log to the base e) logarithm of the data you select.
The function named Log (base 10) calculates the common (log to the base 10) logarithm of the data you select.
Effects of log transformation:
* Variance stabilisation.
* Increasing slopes in x in relation to another variable are linearized.
* Positively skewed distributions of x are normalized.
The function named Log (natural) calculates the natural (Naperian, log to the base e) logarithm of the data you select.
The function named Log (base 10) calculates the common (log to the base 10) logarithm of the data you select.
Saturday, September 25, 2010
Eye bags
http://www.getridofthings.com/get-rid-of-bags-under-eyes.htm
http://facialexercisesguide.com/19/eye-bags-how-to-get-rid-of-bags-under-eyes/
cause: genetics, water retention under the eyes due to dehydration or being tired
Using a cold compress for 10 - 15 minutes, one to two times daily, will help get rid of the bags under your eyes for a short period
Out of all the bizarre folk remedies, application of frozen or chilled green tea bags may be one of the few that can actually get rid of bags under eyes.
You may need to address your water retention to get rid of the bags under your eyes.
http://facialexercisesguide.com/19/eye-bags-how-to-get-rid-of-bags-under-eyes/
cause: genetics, water retention under the eyes due to dehydration or being tired
Using a cold compress for 10 - 15 minutes, one to two times daily, will help get rid of the bags under your eyes for a short period
Out of all the bizarre folk remedies, application of frozen or chilled green tea bags may be one of the few that can actually get rid of bags under eyes.
You may need to address your water retention to get rid of the bags under your eyes.
Friday, September 24, 2010
Rails Cheat Sheet
Rails file structure notes
* Gemfile - which libraries are to be installed and used, the ‘gem’ collections
group :development do
gem "rspec-rails", ">= 2.0.0.beta.22"
end
* config/routes.rb - when a new view has been added, named routes
match '/help', :to => 'pages#help' # about_path => '/about', about_url => 'http://localhost:3000/about'
o root :to => 'pages#home' # This code maps the root URL / to /pages/home
* app/controllers/pages_controller.rb - when a new page has been added, Ruby code here
def help
@title = "Help"
end
* app/views/pages/help.html.erb - view
* app/views/layouts/application.html.erb - the master html where to reference header and footer partials
<%= render 'layouts/header' %> # reference _header.html.erb partial
* public/stylesheets/custom.css - public stylesheets
nav ul li {
list-style-type: disc;
display: inline-block;
padding: 0.2em 0;
}
* public/images/logo.png - where images are stored
* app/views/layouts/_header.html.erb - partials, ie header, footer, CSS
<%= link_to 'Help', help_path %>
# use help_path named route
<%= stylesheet_link_tag 'custom', :media => 'screen' %> # use custom.css
* $ rails generate controller Users new - create a Users controller with action new
create app/controllers/users_controller.rb
route get "users/new"
* $ rails generate model User name:string email:string - generate model, same as above, model names are singular and controller names are plural
* spec/controllers/users_controller_spec.rb - tests Users controller
it "should be successful" do
get '/signup' response.should be_success
response.should have_selector('title', :content => "Sign up")
end
* $ rspec spec/ - run tests
* db/migrate/_create_users.rb - User model (database)
o class CreateUsers < ActiveRecord::Migration def self.up create_table :users do |t| t.string :name
* $ rake db:migrate - migrate up, applies changes in db/*/*.rb model files and calls self.up to create a file called db/development.sqlite3
* $ rake db:rollback - tear down, ie. calls self.down
* $ rails console --sandbox - loads console with read-only access to DB
>> foo = User.create(:name => "Foo", :email => "foo@bar.com")
=> #
>> user.errors.full_messages - display error message for object user in rails console
=> ["Name can't be blank"]
* $ tail -f log/development.log - console DB logs
* app/models/user.rb - Model attribute validate
validates :name, :presence => true
* $ rails generate migration add_email_uniqueness_index - adding structure to an existing model, which creates db/migrate/_add_email_uniqueness_index.rb
* Gemfile - which libraries are to be installed and used, the ‘gem’ collections
group :development do
gem "rspec-rails", ">= 2.0.0.beta.22"
end
* config/routes.rb - when a new view has been added, named routes
match '/help', :to => 'pages#help' # about_path => '/about', about_url => 'http://localhost:3000/about'
o root :to => 'pages#home' # This code maps the root URL / to /pages/home
* app/controllers/pages_controller.rb - when a new page has been added, Ruby code here
def help
@title = "Help"
end
* app/views/pages/help.html.erb - view
* app/views/layouts/application.html.erb - the master html where to reference header and footer partials
<%= render 'layouts/header' %> # reference _header.html.erb partial
* public/stylesheets/custom.css - public stylesheets
nav ul li {
list-style-type: disc;
display: inline-block;
padding: 0.2em 0;
}
* public/images/logo.png - where images are stored
* app/views/layouts/_header.html.erb - partials, ie header, footer, CSS
<%= link_to 'Help', help_path %>
# use help_path named route
<%= stylesheet_link_tag 'custom', :media => 'screen' %> # use custom.css
* $ rails generate controller Users new - create a Users controller with action new
create app/controllers/users_controller.rb
route get "users/new"
* $ rails generate model User name:string email:string - generate model, same as above, model names are singular and controller names are plural
* spec/controllers/users_controller_spec.rb - tests Users controller
it "should be successful" do
get '/signup' response.should be_success
response.should have_selector('title', :content => "Sign up")
end
* $ rspec spec/ - run tests
* db/migrate/
o class CreateUsers < ActiveRecord::Migration def self.up create_table :users do |t| t.string :name
=> #
>> user.errors.full_messages - display error message for object user in rails console
=> ["Name can't be blank"]
validates :name, :presence => true
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