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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.
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:
- Can we accurately predict biologically relevant interactions from a genome?
- How do genome sequence changes affect the molecular network in the cell?
- Can we predict how well model pathways or phenotypes will translate to human?
- Can we design new networks de novo?
Team: David Gfeller, Shirley Hui, Chris Tan Collaborators: Sachdev Sidhu, Charlie Boone, Tony Pawson, Marius Sudol, Chris Sander Funding: CIHR
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:
- What processes are active in a given tissue?
- What processes are active in disease, but not in non-disease tissues?
Team: Daniele Merico, Vuk Pavlovic, Ruth Isserlin Collaborators: Andrew Emili, Anthony Gramolini Funding: CFI/MRI
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:
- How are systems organized hierarchically within the cell?
- How important is a set of genes for a biological system?
Team: Anastasia Baryshnikova, Iain Wallace, Laetitia Morrison Collaborators: Charlie Boone, Brenda Andrews, Guri Giaever, Corey Nislow Funding: NSERC, Genome Canada Integrative Biology of Yeast
Software Infrastructure Track
More details on the Software page.
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.
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/
Team: Rashad Badrawi, Ovi Comes, Khalid Zuberi, Jason Montojo, Christian Lopes, Sylva Donaldson Collaborators: Chris Sander (MSKCC), Quaid Morris (UofT), 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 other Cytoscape, BioPAX and PSI-MI community members are important for this work. Funding: NIH NHGRI, Genome Canada Technology Development
Full funding details at Funding