Pathways, Networks and Systems Session Introduction

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Pathways, Networks and Systems SessionIntroductio
n

• Vincent Schächter
• Alfonso Valencia

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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

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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

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Types of biomolecular networks

• ChIP-Chip
• Gene expression data
• Sequence
• Sequence
• Classical biochemistry
• Mass spectrometry
• Isotope labeling
• Yeast two-hybrid
• Mass spectrometry
• Measurements of post-translational modifications

• 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

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Computational Biology of Networks

• Modeling
• Reconstruction
• Simulation
• Analysis
• Structural (topological) properties
• Dynamical properties
• Tools for visualization and navigation

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Pathways Networks _at_ISMB05

• 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

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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, 250-315pm
• Modeling the Organization of the WUSCHEL
  Expression Domain in the Shoot Apical
  MeristemJönsson, Heisler, Reddy, Agrawal, Gor,
  Shapiro, Mjolsness, MeyerowitzSun, 435-5pm

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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, 345-410pm
• Predicting Protein-Protein Interaction by
  Searching Evolutionary Tree Automorphism
  SpaceJothi, Kann, PrzytyckaTue, 210-235pm
• Metabolic Pathways Reconstruction
• Supervised Enzyme Network Inference from the
  Integration of Genomic Data and Chemical
  InformationYamanishi, Vert, Kanehisa Tue,
  305-330pm
• Automatic Detection of Subsystem/Pathway Variants
  in Genome AnalysisYe, Osterman, Overbeek,
  GodzikSun, 410-435pm

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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, 410-435pm
• Mining Coherent Dense Subgraphs Across Massive
  Biological Networks for Functional DiscoveryHu,
  Yan, Huang, Han, Zhou Tue, 355-420pm

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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,
  330-355pm

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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, 250-315pm
• Kernel Methods for Predicting Protein-protein
  InteractionsBen-Hur, NobleSun, 345-410pm
• Automatic Detection of Subsystem/Pathway Variants
  in Genome AnalysisYe, Osterman, Overbeek,
  GodzikSun, 410-435pm
• Modeling the Organization of the WUSCHEL
  Expression Domain in the Shoot Apical
  MeristemJönsson, Heisler, Reddy, Agrawal, Gor,
  Shapiro, Mjolsness, MeyerowitzSun, 435-5pm

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