BOL: Category: All

Welch Lab

Mon, 15 Jul 2013 18:21:13 -0500

They are based in the Department of Genetics at the University of Cambridge.

The research covers diverse areas of evolutionary biology, and molecular evolution in particular. It combines theoretical and empirical approaches, and particularly evolutionary inference from genome sequence data.

Links @ http://www.gen.cam.ac.uk/research/welch/GroupPage/Home.html

Jayaram Lab

Sun, 14 Jul 2013 14:04:37 -0500

Responsible (a) for developing Chemgenome, Bhageerath & Sanjeevini methods & softwares for genome annotation, protein tertiary structure prediction & computer aided drug design respectively, (b) for setting up a multi-teraflop supercomputing facility for Bioinformatics & Computational Biology at IIT Delhi, and (c) for making the hardware and software freely accessible at (www.scfbio-iitd.res.in) to the global scientific user community.

Faculty facilitator/Founder Director for two start-up companies (Leadinvent incubated at IIT, Delhi from 2006-2009 & Novoinformatics, under incubation at IIT Delhi since 2011).

Research Interest
Genome Analysis, Protein Structure Prediction and Drug Design.

Link @ http://www.scfbio-iitd.res.in/

The Upton (VBRC) lab

Sun, 14 Jul 2013 13:25:41 -0500

This Bioinformatics Resource (Virology.ca, the Canadian half of the now defunct VBRC) focuses on large DNA viruses:
Poxviruses
African Swine Fever Viruses
Iridoviruses
Baculoviruses

Research Area

Custom searches of the viral databases
Building new tools .
The genome annotation

Link @ http://athena.bioc.uvic.ca/

BC Cancer Agency Genome Sciences Centre

Sun, 14 Jul 2013 13:21:27 -0500

Research Area

Genome analysis, genome visualization, mutation detection, molecular docking, comparative genomics, cancer informatics

Link @ http://www.bcgsc.ca

Donnelly Centre of Cellular & Biomolecular Research (CCBR), Bader Lab

Sun, 14 Jul 2013 13:06:33 -0500

We study the organization and evolution of biological systems using computational biology and bioinformatics techniques. We seek to accurately predict links, such as specific molecular interactions, in eukaryotic cell signaling systems using comprehensive genomics data like genome sequence and transcript profiles. We are interested to find how these links are rewired by mutations to cause disease. This work is supported through the development of open-source biological pathway and network databases and visualization and analysis software.
Predicting biologically relevant protein interactions
Cellular network evolution
Detection of cell type and stage active biological processes using molecular profiles
Biological pathway and network databases and analysis tools

Link @ http://baderlab.org/