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CSC, Dec.15-16,2005

CSC, Dec.15-16,2005 . Cytoscape Team. Benno Schwikowski Melissa Cline Andrea Splendiadi Lee Hood Richard Bonneau Rowan Christmas Iliana Avila-Campillo Past contributors: Larissa Kamenkovich Andrew Markiel Paul Shannon. Trey Ideker Mark Anderson Nerius Landys Ryan Kelley

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CSC, Dec.15-16,2005

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  1. CSC, Dec.15-16,2005

  2. Cytoscape Team Benno Schwikowski Melissa Cline Andrea Splendiadi Lee Hood Richard Bonneau Rowan Christmas Iliana Avila-Campillo Past contributors: Larissa Kamenkovich Andrew Markiel Paul Shannon Trey Ideker Mark Anderson Nerius Landys Ryan Kelley Chris Workman Past contributors: Nada Amin Owen Ozier Jonathan Wang Chris Sander Gary Bader Ethan Cerami Rob Sheridan Agilent Annette Adler Allan Kuchinsky Aditya Vailaya Mike Creech

  3. Logistics • Four units per day • 1/2 hour lecture • 45 minute hands-on exercises • Lecture • Background for the hands-on exercises • Questions and comments encouraged • Hands-on exercises • Mostly Cytoscape 2.2, a little Cytoscape 2.1. • Teamwork encouraged • Proceed at own pace

  4. Thursday am: getting started Introduction Coffee break Biological network data Lunch Thursday pm: companion resources for network analysis Text mining Coffee break Gene Ontology Leave Friday am: mRNA Expression Expression basics Coffee break Expression & text mining & GO Lunch Friday pm: advanced topics in network topology Modules and complexes Coffee break Protein domain networks, future directions, feedback. Schedule

  5. Overview • Introduction • What is Cytoscape? • Resources for getting help • Basic functionality

  6. Biological networks Motivation: most biological processes are not performed by a single, independent macromolecule

  7. Core Features • Customize network data display using visual styles • Powerful graph layout tools • Easily organize multiple networks • Easily navigate large networks • Filter the network • Plugin API Cytoscape.org • Additional features are available as plugins.  • jActiveModules: identify significant “active” subnetworks • Expression Correlation Network: cluster expression data • Agilent Literature Search: build networks by extracting interactions from scientific literature. • MCODE: finds clusters of highly interconnected regions in networks • cPath: query, retrieve and visualize interactions from the MSKCC Cancer Pathway database • BiNGO:determine which Gene Ontology (GO) categories are statistically over-represented in a set of genes • Motif Finder: runs a Gibbs sampling motif detector on sequences for nodes in a Cytoscape network. • CytoTalk: Interact with Cytoscape from Perl, Python, R, shell scripts or C or C++ programs. Cytoscape is a freely-available (open-source, java-based) bioinformatics software platform forvisualizing biological networks (e.g. molecular interaction networks) andanalyzing networks with gene expression profiles and other state data. • Input/Output • Protein protein interactions from BIND, TRANSFAC databases • Gene functional annotations from Gene Ontology (GO) and KEGG databases • Biological models from Systems Biology Markup Language (SBML) • cPath: Cancer Pathway database • Proteomics Standards Initiative Molecular Interaction (PSI-MI) or Biopathway Exchange Language (BioPAX) formats • Oracle Spatial Network data model

  8. Use Case 1: Atherosclerosis • King et. al., Physiol Genomics. 2005 Sep 21;23(1):103-18.

  9. Use Case 2: Hepatitis C virus infection • Reiss et. al., BMC Bioinformatics 2005, 6:154

  10. Hands-on Session 1 • Navigating the Cytoscape panels • Loading, editing, and saving a network • Graph layout methods • Setting visual properties

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