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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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Cytoscape team l.jpg
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


Annette Adler

Allan Kuchinsky

Aditya Vailaya

Mike Creech

Logistics l.jpg

  • 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

Schedule l.jpg

Thursday am: getting started


Coffee break

Biological network data


Thursday pm: companion resources for network analysis

Text mining

Coffee break

Gene Ontology


Friday am: mRNA Expression

Expression basics

Coffee break

Expression & text mining & GO


Friday pm: advanced topics in network topology

Modules and complexes

Coffee break

Protein domain networks, future directions, feedback.


Overview l.jpg

  • Introduction

    • What is Cytoscape?

    • Resources for getting help

    • Basic functionality

Biological networks l.jpg
Biological networks

Motivation: most biological processes are not performed by a single, independent macromolecule

Slide7 l.jpg

  • 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

  • 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

Use case 1 atherosclerosis l.jpg
Use Case 1: Atherosclerosis

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

Use case 2 hepatitis c virus infection l.jpg
Use Case 2: Hepatitis C virus infection

  • Reiss et. al., BMC Bioinformatics 2005, 6:154

Hands on session 1 l.jpg
Hands-on Session 1

  • Navigating the Cytoscape panels

  • Loading, editing, and saving a network

  • Graph layout methods

  • Setting visual properties