Cytoscape Wiki
Abstracts
Patricia Babbitt (QB3/UCSF, San Francisco) "Network Analysis Reveals New Relationships among Divergent Proteins Missed by Tree-based Approaches"
Gary Bader (University of Toronto) "BioPAX, cPath, and PDZ-based Protein Interaction Prediction"
- Cellular biological systems, such as cell signaling networks which mediate cellular information transfer and logic, are implemented by precisely controlled specific molecular interactions. For example protein post-translational modifications or change of interacting molecule location can turn on or off an interaction. Evolutionary genome sequence changes or the presence of certain SNPs can also create or destroy molecular interactions. Can we use information about how these interactions are created and controlled to accurately predict biologically relevant network links? Can we find out how interactions are rewired to cause disease? To answer these questions, we require large amounts of cell map information (networks and pathways), algorithms and tools for visualization and analysis. I will discuss our efforts to develop software systems for cellular biological network analysis and the application of some of these tools to predict protein-protein interactions involving human PDZ domains.
Mirit Aladjem (National Cancer Inst., NIH) "Molecular Interaction Maps of Biological Signalling Networks"
Ilya Shmulevich (ISB, Seattle) "Data Integration and Genetic Network Modeling"
Benno Schwikowski (Institute Pasteur, Paris) "Mass Spec Informatics: Towards Dense Protein Expression Networks"
- Global measurements of protein abundance will be a critical ingredient for dynamic models of molecular interaction networks. Liquid chromatography, coupled to mass spectrometry (LC-MS), represents the current platform of choice for such global measurements. In single experiments, the minimum time required to identify single proteins, and the maximum time available for one experiment limit the number of identified proteins in a single experiment. This number is estimated to be too low by 2-3 orders of magnitude if one wants to be able to cover the human proteome. Here, we present an alternative approach that relies on linking information across independent experiments to identify and quantify peptides. The approach relies on the alignment of multiple LC-MS experiments. We show basic ideas, experimental validation, and a side product that systematically uncovers quality issues with this type of experiments.
Trey Ideker (UCSD, San Diego) "Protein Network Comparative Genomics"