SymAtlas - Gene annotation for protein and function

http://symatlas.gnf.org/SymAtlas/
http://biogps.gnf.org/#goto=welcome

Bioinformatics videos

Walter + Eliza Hall Institute of Medical Research
http://www.wehi.edu.au/education/wehi-tv/?page=2

Flow cytometry - Day 1

Sept 7
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FCS - forward scatter
- increasing in size of cell == increasing FSC
- increasing in refractive index of cell == increasing FSC
- bright == large refractive index

SSC - side scatter
- increasing granularity (contents in cell) == increasing SSC

Cell types:
platelets (smallest) - erythrocytes (RBC) - lymphocytes (WBC, T cells, B cells, Natural killer cells, neutrophil)

CD3 and CD4 T cell receptors

FCS - Flow Cytometry Standard

Parameters:
- FSC
- SSC
- FITC - fluorescein isothicyanate fluorochrome
- PE fluorescence - phycoerythin fluorochrome

Gating:
- restricts analysis to one population eg. snap-to-gate, quadrant, polygon

Event:
- cell passing through a laser

Compensation correction for multicolor experiments

http://www.bdbiosciences.com/support/training/itf_launch.jsp

Find broken links on web sites

Xenu Link Sleuth
http://home.snafu.de/tilman/xenulink.html

Grad school requirements

Your program may require any or all of the following:
•
– Coursework
– Comprehensive or „qualifying‟ exams
– A research thesis or major project
– Public presentation and/or defense of thesis or project

•
– Masters students must complete all degree requirements
within 5 years of enrolment

Doctoral students:
Phase I: Pre-Candidacy
– Take all required courses
“Advance
– Pass a comprehensive exam
to
– Gain approval for a research proposal Candidacy”
Phase II: Candidacy
– Complete a research project (dissertation)
– Defend the thesis at a Doctoral Oral Examination
Doctoral Students:
– Should advance to candidacy within 2 years, and must within 3
– Should complete all degree requirements within 5 years of
enrollment and must within 6 years

http://www.grad.ubc.ca/current-students/newly-admitted/grad-orientation

GPS graduate pathways success
http://www.grad.ubc.ca/current-students/gps-graduate-pathways-success/gps-workshops-events

Find experts
http://webservices.publicaffairs.ubc.ca/clients/pa/apps/experts/public/index.php

GPU

http://www.biomedcentral.com/1471-2105/11/446/abstract

Fast and accurate protein substructure searching with simulated annealing and GPUs

Alex D Stivala email, Peter J Stuckey email and Anthony I Wirth email

BMC Bioinformatics 2010, 11:446doi:10.1186/1471-2105-11-446
Published: 3 September 2010


http://www.biomedcentral.com/1471-2105/11/447/abstract
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification algorithms
Guo Y, Graber A, McBurney RN, Balasubramanian R
BMC Bioinformatics 2010, 11:447 (3 September 2010)

New Genomic Marker for Tuberculosis May Help Identify Patients Who Will Develop the Disease

http://www.sciencedaily.com/releases/2010/08/100830073801.htm?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+sciencedaily+%28ScienceDaily%3A+Latest+Science+News%29

Matthew P. R. Berry, Christine M. Graham, Finlay W. McNab, Zhaohui Xu, Susannah A. A. Bloch, Tolu Oni, Katalin A. Wilkinson, Romain Banchereau, Jason Skinner, Robert J. Wilkinson, Charles Quinn, Derek Blankenship, Ranju Dhawan, John J. Cush, Asuncion Mejias, Octavio Ramilo, Onn M. Kon, Virginia Pascual, Jacques Banchereau, Damien Chaussabel, Anne O’Garra. An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis. Nature, 2010; 466 (7309): 973 DOI: 10.1038/nature09247

Videos in Gene Screen BC 2010

http://www.scivee.tv/node/16377/video

Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1. Nature Genetics, 2010; DOI: 10.1038/ng.652

Verneri Anttila, Hreinn Stefansson, Mikko Kallela, Unda Todt, Gisela M Terwindt, M Stella Calafato, Dale R Nyholt, Antigone S Dimas, Tobias Freilinger, Bertram Müller-Myhsok, Ville Artto, Michael Inouye, Kirsi Alakurtti, Mari A Kaunisto, Eija Hämäläinen, Boukje de Vries, Anine H Stam, Claudia M Weller, Axel Heinze, Katja Heinze-Kuhn, Ingrid Goebel, Guntram Borck, Hartmut Göbel, Stacy Steinberg, Christiane Wolf, Asgeir Björnsson, Gretar Gudmundsson, Malene Kirchmann, Anne Hauge, Thomas Werge, Jean Schoenen, Johan G Eriksson, Knut Hagen, Lars Stovner, H-Erich Wichmann, Thomas Meitinger, Michael Alexander, Susanne Moebus, Stefan Schreiber, Yurii S Aulchenko, Monique M B Breteler, Andre G Uitterlinden, Albert Hofman, Cornelia M van Duijn, Päivi Tikka-Kleemola, Salli Vepsäläinen, Susanne Lucae, Federica Tozzi, Pierandrea Muglia, Jeffrey Barrett, Jaakko Kaprio, Markus Färkkilä, Leena Peltonen, Kari Stefansson, John-Anker Zwart, Michel D Ferrari, Jes Olesen, Mark Daly, Maija Wessman, Arn M J M van den Maagdenberg, Martin Dichgans, Christian Kubisch, Emmanouil T Dermitzakis, Rune R Frants, Aarno Palotie. Genome-wide association study of migraine implicates a common susceptibility variant on 8q22.1. Nature Genetics, 2010; DOI: 10.1038/ng.652

Ten Simple Rules for a Good Poster Presentation

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1876493/

Ten Simple Rules for a Good Poster Presentation
Thomas C Erren* and Philip E Bourne

Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics
Al-Shahib A, Misra R, Ahmod N, Fang M, Shah H, Gharbia S
BMC Bioinformatics 2010, 11:437 (26 August 2010)
http://www.biomedcentral.com/1471-2105/11/437/abstract

A towards-multidimensional screening approach to predict candidate genes of rheumatoid arthritis based on SNP, structural and functional annotations
Zhang L, Li W, Song L, Chen L
BMC Medical Genomics 2010, 3:38 (20 August 2010)
http://www.biomedcentral.com/1755-8794/3/38/abstract

Curating the innate immunity interactome
Lynn DJ, Chan C, Naseer M, Yau M, Lo R, Sribnaia A, Ring G, Que J, Wee K, Winsor GL, Laird MR, Breuer K, Foroushani AK, Brinkman FSL, Hancock REW
BMC Systems Biology 2010, 4:117 (20 August 2010)
http://www.biomedcentral.com/1752-0509/4/117/abstract

De novo assembly of short sequence reads
Konrad Paszkiewicz and David J. Studholme
Brief Bioinform published 19 August 2010, 10.1093/bib/bbq020
http://bib.oxfordjournals.org/cgi/content/abstract/bbq020v1

Perspectives on presentation and pedagogy in aid of bioinformatics education
Pier Luigi Buttigieg
Brief Bioinform published 19 August 2010, 10.1093/bib/bbq062
http://bib.oxfordjournals.org/cgi/content/abstract/bbq062v1

*omeSOM: a software for clustering and visualization of transcriptional and metabolite data mined from interspecific crosses of crop plants.
Milone DH, Stegmayer GS, Kamenetzky L, Lopez M, Lee J, Giovannoni JJ, Carrari F
BMC Bioinformatics 2010, 11:438 (26 August 2010)
http://www.biomedcentral.com/1471-2105/11/438/abstract

Predictive, preventive, personalized and participatory medicine: back to the future
Auffray C, Charron D, Hood L
Genome Medicine 2010, 2:57 (26 August 2010)
http://genomemedicine.com/content/2/8/57/abstract

Engineering of N. benthamiana L. plants for production of N-acetylgalactosamine-glycosylated proteins - towards development of a plant-based platform for production of protein therapeutics with mucin type O-glycosylation
Daskalova SM, Radder JE, Cichacz ZA, Olsen SH, Tsaprailis G, Mason H, Lopez LC
BMC Biotechnology 2010, 10:62 (24 August 2010)
http://www.biomedcentral.com/1472-6750/10/62/abstract

"Predicting protein complexes by data integration of different types of interactions", Powell Patrick Cheng Tan, Daryanaz Dargahi, Frederic Pio
DOI: 10.1504/IJCBDD.2010.034464
http://www.inderscience.com/search/index.php?action=record&rec_id=34464&prevQuery=&ps=10&m=or

Ensembles, CodonTest, Volumetric Analysis

http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000911
Evidence of Functional Protein Dynamics from X-Ray Crystallographic Ensembles

There is a well-recognized gap between the dynamical motions of proteins required to execute function and the experimental techniques capable of capturing that motion at the atomic level. We show that much experimental detail of dynamical motion is already present in X-ray crystallographic data, which arises from being solved by different research groups using different methodologies under different crystallization conditions, which then capture an ensemble of structures whose variations can be quantified on a residue-by-residue level using local density correlations. We contrast the amino acid displacements below and above the protein dynamical transition temperature, TD∼215K, of hen egg white lysozyme by comparing the X-ray ensemble to MD ensembles as a function of temperature. We show that measuring structural variations across an ensemble of X-ray derived models captures the activation of conformational states that are of functional importance just above TD and they remain virtually identical to structural motions measured at 300K. It provides a novel analysis of large X-ray ensemble data that is useful for the broader structural biology community.

Jonathan E. Kohn1, Pavel V. Afonine2, Jory Z. Ruscio1, Paul D. Adams1,2, Teresa Head-Gordon1,2*

1 Department of Bioengineering, University of California, Berkeley, Berkeley, California, United States of America, 2 Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America


http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000885
Wayne Delport1, Konrad Scheffler2, Gordon Botha2, Mike B. Gravenor3, Spencer V. Muse4, Sergei L. Kosakovsky Pond5*

1 Department of Pathology, University of California, San Diego, La Jolla, California, United States of America, 2 Computer Science Division, Department of Mathematical Sciences, Stellenbosch University, Stellenbosch, South Africa, 3 School of Medicine, University of Swansea, Swansea, United Kingdom, 4 Department of Statistics, North Carolina State University, Raleigh, North Carolina, United States of America, 5 Department of Medicine, University of California, San Diego, La Jolla, California, United States of America


VASP: A Volumetric Analysis of Surface Properties Yields Insights into Protein-Ligand Binding Specificity
Brian Y. Chen1,2, Barry Honig1,2*

1 Department of Biochemistry and Molecular Biophysics, Center for Computational Biology and Bioinformatics, Columbia University, New York, New York, United States of America, 2 Howard Hughes Medical Institute, Columbia University, New York, New York, United States of America
Many algorithms that compare protein structures can reveal similarities that suggest related biological functions, even at great evolutionary distances. Proteins with related function often exhibit differences in binding specificity, but few algorithms identify structural variations that effect specificity. To address this problem, we describe the Volumetric Analysis of Surface Properties (VASP), a novel volumetric analysis tool for the comparison of binding sites in aligned protein structures. VASP uses solid volumes to represent protein shape and the shape of surface cavities, clefts and tunnels that are defined with other methods. Our approach, inspired by techniques from constructive solid geometry, enables the isolation of volumetrically conserved and variable regions within three dimensionally superposed volumes. We applied VASP to compute a comparative volumetric analysis of the ligand binding sites formed by members of the steroidogenic acute regulatory protein (StAR)-related lipid transfer (START) domains and the serine proteases. Within both families, VASP isolated individual amino acids that create structural differences between ligand binding cavities that are known to influence differences in binding specificity. Also, VASP isolated cavity subregions that differ between ligand binding cavities which are essential for differences in binding specificity. As such, VASP should prove a valuable tool in the study of protein-ligand binding specificity.

Bioinformatics Standards for Flow Cytometry

http://flowcyt.sourceforge.net/