Pathways, Networks and Systems Session Introduction

1. Pathways, Networks and Systems SessionIntroduction Vincent Schächter Alfonso Valencia ISMB’05 – Detroit, MI

2. Biological networks and systems : context • (Partial) catalog of functional elements available : genes, proteins, RNAs • High-throughput measurement technologies • Elements of mechanisms : protein-protein interactions, protein-DNA interactions, biochemical reactions… • Information on cellular states : mRNA expression, protein expression, phenotype, microscopy & imaging, metabolite concentrations, metabolite fluxes… • Increasing realization of the limits of functional understanding at the level of individual genes / proteins ISMB’05 – Detroit, MI

3. Motivations for the study of biological networks and systems • Help structure, represent and interpret experimental data on interactions and states • Integrate different types of experimental data • Relate mechanisms to states • Build a detailed understanding of cellular processes • allowing prediction of cellular state observables at different levels of detail • allowing intervention with predictable & measurable outcomes • Guide experiments by providing testable hypotheses obeying parsimony criteria • Compare processes within and across organisms, gain insight into their evolution • Better characterize the function of single genes ISMB’05 – Detroit, MI

4. Gene regulatory networks Vertices : genes Edges : regulatory influences Metabolic networks Vertices : metabolites, reactions (catalyzed by enzymes) Edges : consumption, production Degenerate networks : enzymes, metabolites Protein-protein interaction networks Vertices : proteins Edges : physical interactions Signaling networks Vertices : proteins with state information Edges : interactions modifying states Networks of functional links Vertices : genes Edges : functional relationships ChIP-Chip Gene expression data Sequence Sequence Classical biochemistry Mass spectrometry Isotope labeling Yeast two-hybrid Mass spectrometry Measurements of post-translational modifications Sequence (of several organisms) Expression data Any data type allowing definition of a similarity measure… Types of biomolecular networks ISMB’05 – Detroit, MI

5. Computational Biology of Networks • Modeling • Reconstruction • Simulation • Analysis • Structural (topological) properties • Dynamical properties • Tools for visualization and navigation ISMB’05 – Detroit, MI

6. Pathways & Networks @ISMB’05 • Pathways, networks and systems session • 8 papers selected from 64 submissions • Pathways, networks and proteomics session • Oral abstracts, Sunday morning and Wednesday • BioPathways SIG • Started at ISMB 2000, yearly meeting • Sessions on : • metabolic networks • regulatory networks • protein-protein interaction networks • database, exchange formats & software tools ISMB’05 – Detroit, MI

7. Modeling • Design modeling frameworks adapted to • the type of biological network / system • the type(s) of experimental data available to build the model • the type of predictions the model will be used for • the type of experimental data model predictions will be compared to • Design predictive methods to answer specific questions on network architecture or dynamics • Model, validate, refine specific biological systems • Validation of Qualitative Models of Genetic Regulatory Networks by Model Checking: Analysis of the Nutritional Stress Response in Escherichia coliBatt, Ropers, de Jong, Geiselmann, Mateescu, Page, SchneiderSun, 2:50-3:15pm • Modeling the Organization of the WUSCHEL Expression Domain in the Shoot Apical MeristemJönsson, Heisler, Reddy, Agrawal, Gor, Shapiro, Mjolsness, MeyerowitzSun, 4:35-5pm ISMB’05 – Detroit, MI

8. Network Reconstruction Infer networks from experimental data • using one or several experimental data types • using prior knowledge about network structure • Challenges : • Data quantity and availability • Validation sets ? • Methods • Machine learning • Comparison across organisms, evolutionary reasoning Protein-protein interaction prediction • Kernel Methods for Predicting Protein-protein InteractionsBen-Hur, NobleSun, 3:45-4:10pm • Predicting Protein-Protein Interaction by Searching Evolutionary Tree Automorphism SpaceJothi, Kann, PrzytyckaTue, 2:10-2:35pm Metabolic Pathways Reconstruction • Supervised Enzyme Network Inference from the Integration of Genomic Data and Chemical InformationYamanishi, Vert, Kanehisa Tue, 3:05-3:30pm • Automatic Detection of Subsystem/Pathway Variants in Genome AnalysisYe, Osterman, Overbeek, GodzikSun, 4:10-4:35pm ISMB’05 – Detroit, MI

9. Analyses of network structure • Motivation • Experimental data on the mechanistic details of network dynamics not available at large scale • Identifying biologically relevant dynamical properties of large networks is a hard problem • Focus first on topological properties of networks • Goals • Build simplified, tractable view of network architecture : modules… • Identify properties of network structure with potential interpretation as traces of underlying biological mechanisms • Dynamics : how structure reflects dynamics • Evolution : how structure reflects evolutionary history and thus fitness constraints • Automatic Detection of Subsystem/Pathway Variants in Genome AnalysisYe, Osterman, Overbeek, GodzikSun, 4:10-4:35pm • Mining Coherent Dense Subgraphs Across Massive Biological Networks for Functional DiscoveryHu, Yan, Huang, Han, Zhou Tue, 3:55-4:20pm ISMB’05 – Detroit, MI

10. Function prediction using networks Predict function of individual genes/proteins using network structure Variations on the intuitive guilt-by-association idea • Whole-proteome Prediction of Protein Function via Graph-theoretic Analysis of Interaction MapsNabieva, Jim, Agarwal, Chazelle, SinghTue, 3:30-3:55pm ISMB’05 – Detroit, MI

11. Pathways, Networks and Systems Session Sunday afternoon : • Validation of Qualitative Models of Genetic Regulatory Networks by Model Checking: Analysis of the Nutritional Stress Response in Escherichia coliBatt, Ropers, de Jong, Geiselmann, Mateescu, Page, SchneiderSun, 2:50-3:15pm • Kernel Methods for Predicting Protein-protein InteractionsBen-Hur, NobleSun, 3:45-4:10pm • Automatic Detection of Subsystem/Pathway Variants in Genome AnalysisYe, Osterman, Overbeek, GodzikSun, 4:10-4:35pm • Modeling the Organization of the WUSCHEL Expression Domain in the Shoot Apical MeristemJönsson, Heisler, Reddy, Agrawal, Gor, Shapiro, Mjolsness, MeyerowitzSun, 4:35-5pm ISMB’05 – Detroit, MI

12. ISMB’05 – Detroit, MI