Bioinformatics Organization - Bioinformatics.Org Computing large-scale distance matrices on GPU [2012] | Ahmed Shamsul Arefin, Ph.D. Computing Large-scale Distance Matrices on GPU Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato Centre for Bioinformatics, Biomarker Discovery & Information-Based Medicine (CIBM) School of Electrical Engineering and Computer Science The University of Newcastle, Australia Callaghan, NSW 2308, Australia Email: Ahmed.Arefin, Carlos.Riveros, Regina.Berretta, Pablo.Moscato @newcastle.edu.au Abstract —A distance matrix is simply an n two-dimensional arra y tha t con tain s pai rwi se dis tan ces of a set of poi nts in a metric space. increases, th e co mp ut at io n of di st an ce ma tr ix be co mes ve ry sl ow or incomputable on traditional general purpose computers. The cal cul ati on of dis tan ce mat ric es is a com ple te dat a intensive operation that acts as a preliminary step to many com put ati ona l met hod s, suc h as fea tur e set ana lys is, gen e expr essi on data sets analy sis, dif fere nt time series data sets analy sis etc. row s and m of points in d (1) for any x,y,z x y
Educational services - Bioinformatics.Org Wiki From Bioinformatics.Org Wiki Introduction The Bioinformatics Organization offers professional development courses for continuing scientific education. A screenshot of a live lecture held online Click here for a sample lecture (reduced resolution) on dChip. For online courses, the Bioinformatics Organization uses a system for streaming the multimedia of live lectures. Full A/V streaming from the instructor's computer to the students' computers Ability to show the instructor's desktop on the students' computers Ability to share PowerPoint slides and to use graphical "call-outs" with the students IM-style text chat between students and the instructor Computer science topics Our courses in computer science use laboratory scenarios and data to introduce biologists to fundamental computing topics. Computer Language Series Data Visualization Series Machine Learning Series CS121 Introduction to Machine Learning Biology topics Sequence Analysis Series Microarray Data Analysis Series Genomics Series Step 1
Providers by Location There are hundreds of companies and institutes devoted to the study of the genetic code (genome), which are making tremendous strides in understanding the mechanisms of life (including individual people) at the most fundamental of levels. I’ve listed the ones that I can find at – hopefully helping future biologists and computer scientists see what they might do as a genome scientist, young researchers find jobs, start-up companies find customers, collaborators and investors, and the rest of us learn what’s going on in this fascinating field, or at least find hope in our rapidly advancing understanding of cancer and other complex diseases. Now I’m beginning profile them as I read what’s written on their websites and categorize them as to what they hope to do or provide. I’m starting with Ambry Genetics. Ambry Genetics – : Hello and thanks for stopping by! Three Bioinformatics Tools that Any Scientist Can Learn Today Summary About the author:
Humanizing Bioinformatics I was invited last week to give a talk at this year's meeting of the Graduate School Structure and Function of Biological Macromolecules, Bioinformatics and Modeling (SFMBBM). It ended up being a day with great talks, by some bright PhD students and postdocs. There were 2 keynotes (one by Prof Bert Poolman from Groningen (NL) and one by myself), and a panel discussion on what the future holds for people nearing the end of their PhDs. My talk was titled "Humanizing Bioinformatics" and received quite well (at least some people still laughed at my jokes (if you can call them that); even at the end). I put the slides up on slideshare, but I thought I'd explain things here as well, because those slides will probably not convey the complete story. Let's ruin the plot by mentioning it here: we need data visualization to counteract the alienation that's happening between bioinformaticians and bright data miners on the one hand, and the user/clinician/biologist on the other. What's the question?
Collection of published “guides” for bioinformaticians | opiniomics Recently there has been a proliferation of “guides” for bioinformaticians published in academic journals, so I wanted to start a list here. If I have missed any, suggest them in the comments and I will add them. Loman N and Watson M (2013) So you want to be a computational biologist? I am sure there are one or two more out there ;-) Like this: Like Loading... Ten Simple Rules for Reproducible Computational Research Citation: Sandve GK, Nekrutenko A, Taylor J, Hovig E (2013) Ten Simple Rules for Reproducible Computational Research. PLoS Comput Biol 9(10): e1003285. doi:10.1371/journal.pcbi.1003285 Editor: Philip E. Bourne, University of California San Diego, United States of America Published: October 24, 2013 Copyright: © 2013 Sandve et al. Funding: The authors' laboratories are supported by US National Institutes of Health grants HG005133, HG004909, and HG006620 and US National Science Foundation grant DBI 0850103. Competing interests: The authors have declared that no competing interests exist. Replication is the cornerstone of a cumulative science [1]. We want to emphasize that reproducibility is not only a moral responsibility with respect to the scientific field, but that a lack of reproducibility can also be a burden for you as an individual researcher. As a minimal requirement, you should at least be able to reproduce the results yourself. Rule 2: Avoid Manual Data Manipulation Steps References