The Bader lab aims to develop a computational cell map that organizes all biological processes and their component interactions and molecules. This map can then be read to understand how biological processes work, what is the function of a gene, and what effects disease-associated or engineered mutations have. Cell maps from different organisms or cell types can be compared to identify important components. Three research tracks and one software infrastructure track are actively developing to reach this goal.

General references:

  1. Functional Genomics and Proteomics: Charting a Multidimensional Map of the Cell Bader GD, Heilbut A, Andrews B, Tyers M, Hughes T, Boone C Trends in Cell Biology Jul, 2003 13(7):344-56 - PubMed Abstract - PDF

  2. Pathway information for systems biology Cary MP, Bader GD, Sander C FEBS Lett. 2005 Mar 21;579(8):1815-20 - PubMed Abstract - PDF

Research Tracks

Genome to Network

We are developing computational methods to accurately predict the binding specificity of peptide recognition domains given the domain sequence and to predict biologically relevant protein-protein interactions given binding specificity. We are focusing on PDZ domains, recognizing hydrophobic C-termini, and WW and SH3 domains, recognizing proline rich motifs. Our questions are:

Team: David Gfeller, Shirley Hui, Chris Tan, Shobhit Jain, Xioajian Shao
Collaborators: Sachdev Sidhu, Charlie Boone, Tony Pawson, Marius Sudol, Chris Sander, Philip Kim
Funding: CIHR

References:

  1. A Specificity Map for the PDZ Domain Family. Raffi Tonikian, Yingnan Zhang, Stephen L. Sazinsky, Bridget Currell, Jung-Hua Yeh, Boris Reva, Heike A. Held, Brent A. Appleton, Marie Evangelista, Yan Wu, Xiaofeng Xin, Andrew C. Chan, Somasekar Seshagiri, Laurence A. Lasky, Chris Sander, Charles Boone, Gary D. Bader, Sachdev S. Sidhu PLoS Biology Vol. 6, No. 9, e239, 2008 - PubMed Abstract - PDF

  2. A Combined Experimental and Computational Strategy to Define Protein Interaction Networks for Peptide Recognition Modules Tong AH, Drees B, Nardelli G, Bader GD, Brannetti B, Castagnoli L, Evangelista M, Ferracuti S, Nelson B, Paoluzi S, Quondam M, Zucconi A, Hogue CW, Fields S, Boone C, Cesareni G Science 2002 Jan 11;295(5553):321-324 - PubMed Abstract - PDF - Science Perspective PDF

Active Cell Map

The 'active cell map' is the set of all interactions, complexes and pathways involving molecules in the cell and their activity under normal and diseased regulatory circumstances. We are developing novel computational methods to combine molecular network and profiles to uncover active cell map regions. Our questions are:

Team: Daniele Merico, Vuk Pavlovic, Ruth Isserlin, Oliver Stueker
Collaborators: Andrew Emili, Anthony Gramolini, Cynthia Guidos, Jayne Danska and others
Funding: CFI/MRI

References:

Integration of biological networks and gene expression data using Cytoscape Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B, Hanspers K, Isserlin R, Kelley R, Killcoyne S, Lotia S, Maere S, Morris J, Ono K, Pavlovic V, Pico AR, Vailaya A, Wang PL, Adler A, Conklin BR, Hood L, Kuiper M, Sander C, Schmulevich I, Schwikowski B, Warner GJ, Ideker T, Bader GD Nature Protocols 2007;2(10):2366-82 - PubMed Abstract - PDF

Multiple Perturbation Mapping

Buffering between biological processes, like the cell cycle and DNA damage repair systems, underlies cellular robustness to perturbations. Defects in one system affect dependent, but not buffered systems. Identifying these relationships is useful to delineate system boundaries in the cell. We aim to use quantitative genetic interactions to define pathways and complexes and infer their detailed buffering relationships. Our questions are:

Team: Anastasia Baryshnikova, Iain Wallace, Magali Michaut, Ron Ammar
Collaborators: Charlie Boone, Brenda Andrews, Guri Giaever, Corey Nislow
Funding: NSERC, Genome Canada Integrative Biology of Yeast

References:

  1. Global Mapping of the Yeast Genetic Interaction Network Tong AH, Lesage G, Bader GD, Ding H, Xu H, Xin X, Young J, Berriz GF, Brost RL, Chang M, Chen Y, Cheng X, Chua G, Friesen H, Goldberg DS, Haynes J, Humphries C, He G, Hussein S, Ke L, Krogan N, Li Z, Levinson JN, Lu H, Menard P, Munyana C, Parsons AB, Ryan O, Tonikian R, Roberts T, Sdicu AM, Shapiro J, Sheikh B, Suter B, Wong SL, Zhang LV, Zhu H, Burd CG, Munro S, Sander C, Rine J, Greenblatt J, Peter M, Bretscher A, Bell G, Roth FP, Brown GW, Andrews B, Bussey H, Boone C Science 2004 Feb 6;303(5659):808-813 - PubMed Abstract - PDF - Science Perspective PDF

  2. Systematic Genetic Analysis with Ordered Arrays of Yeast Deletion Mutants Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H, Andrews B, Tyers M, Boone C Science 2001 Dec 14;294(5550):2364-8 - PubMed Abstract - PDF

Software Infrastructure Track

More details on the Software page.

Pathway Commons

Pathway Commons is a collection of publicly available pathways from multiple organisms. It provides researchers with convenient access to a comprehensive collection of pathways from multiple sources represented in a common language (BioPAX). Pathways are stored in the cPath database software. URL: http://www.pathwaycommons.org Pathway Commons is developed in collaboration with Chris Sander's group at MSKCC.

Team: Rashad Badrawi, Igor Rodchenkov
Collaborators: Chris Sander (MSKCC).  Many additional Cytoscape, BioPAX and PSI-MI community members are important for this work.
Funding: NIH NHGRI, Genome Canada Technology Development

Cytoscape

Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data. URL: http://cytoscape.org/

Collaborators: Chris Sander (MSKCC), Trey Ideker (UCSD), Benno Schwikowski (Pasteur), David States (UMich), Annette Adler (Agilent), Yeyejide Adelye (Unilever), Bruce Conklin (UCSF), Lee Hood and Ilya Schmulevich (ISB).  Many additional Cytoscape community members are important for this work.
Funding: NIH, Genome Canada Technology Development

GeneMANIA

GeneMANIA is a gene function prediction tool. Given a set of genes, the system finds additional similar genes based on a large amount of functional genomics data. URL: http://www.genemania.org/

Team: Rashad Badrawi, Ovi Comes, Sylva Donaldson, Farzana Kazi, Christian Lopes, Jason Montojo, Harold Rodriguez, Khalid Zuberi
Collaborators: Quaid Morris (UofT)
Funding: Genome Canada Technology Development, NIH NHGRI

Full funding details at Funding

Research (last edited 2010-02-14 20:45:57 by GaryBader)

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