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Network & Systems Modeling

Network & Systems Modeling. 29 June 2009 NCSU GO Workshop. GO Enrichment & Systems Biology. GO Enrichment: the structure of the GO allows its to be queried in a hierarchical manner. use the GO DAG Structure to cluster differentially expressed gene sets

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Network & Systems Modeling

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  1. Network & Systems Modeling 29 June 2009 NCSU GO Workshop

  2. GO Enrichment & Systems Biology • GO Enrichment: the structure of the GO allows its to be queried in a hierarchical manner. • use the GO DAG Structure to cluster differentially expressed gene sets • determine which GO terms are statistically over-represented in the set • Systems biology: study of complex interactions in biological systems • integrates data from multiple experimental types • develop networks describing interactions within the system

  3. http://www.geneontology.org/

  4. GO Enrichment Analysis • DAVID: http://david.abcc.ncifcrf.gov/ • GOStat: http://gostat.wehi.edu.au/ • EasyGO: http://bioinformatics.cau.edu.cn/easygo/ • AmiGO http://amigo.geneontology.org/cgi-bin/amigo/term_enrichment(does not use IEA) • Onto-Express & OE2GOhttp://vortex.cs.wayne.edu/projects.htm • GOEAST http://omicslab.genetics.ac.cn/GOEAST • http://www.geneontology.org/GO.tools.shtml • Comparison of enrichment analysis tools : Nucleic Acids Research, 2009, Vol. 37, No. 1 1–13 (Tool_Comparison_09.pdf)

  5. Database for Annotation, Visualization and Integrated Discovery

  6. Species represented in Onto-Express For uploading your own annotations use OE2GO

  7. Comparison • Onto-Express , EasyGO, GOstat and DAVID • Test set: 60 randomly selected chicken genes • Used AgBase GO annotations as baseline annotations Vandenberg et al (BMC Bioinformatics, in review)

  8. Systems Biology Models interactions of components in the system (dynamic). Nanduri B. and McCarthy F.M. (2007). "AgBase - a tool for systems biology in agricultural species." CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 2(078):13-26.

  9. Systems Biology Workflow Nanduri & McCarthy CAB reviews, 2008

  10. Pathways & Networks • A network is a collection of interactions • Pathways are a subset of networks Network of interacting proteins that carry out biological functions such as metabolism and signal transduction • All pathways are networks of interactions • NOT ALL NETWORKS ARE PATHWAYS

  11. Biological Networks • Networks often represented as graphs • Nodes represent proteins or genes that code for proteins • Edges represent the functional links between nodes (ex regulation) • Small changes in graph’s topology/architecture can result in the emergence of novel properties

  12. Yeast Protein-Protein Interaction Map Nature411, 2001, H. Jeong, et al

  13. Types of interactions • protein (enzyme) – metabolite (ligand) • metabolic pathways • protein – protein • cell signaling pathways, protein complexes • protein – gene • genetic networks

  14. Database/URL/FTP DIP http://dip.doe-mbi.ucla.edu BIND http://bind.ca MPact/MIPS http://mips.gsf.de/services/ppi STRING http://string.embl.de MINT http://mint.bio.uniroma2.it/mint IntAct http://www.ebi.ac.uk/intact BioGRID http://www.thebiogrid.org HPRD http://www.hprd.org ProtCom http://www.ces.clemson.edu/compbio/ProtCom 3did, Interprets http://gatealoy.pcb.ub.es/3did/ Pibase, Modbase http://alto.compbio.ucsf.edu/pibase CBM ftp://ftp.ncbi.nlm.nih.gov/pub/cbm SCOPPI http://www.scoppi.org/ iPfam http://www.sanger.ac.uk/Software/Pfam/iPfam InterDom http://interdom.lit.org.sg DIMA http://mips.gsf.de/genre/proj/dima/index.html Prolinks http://prolinks.doe-mbi.ucla.edu/cgibin/functionator/pronav/ Predictome http://predictome.bu.edu/ PLoS Computational Biology March 2007, Volume 3 e42

  15. Some resources KEGG http://www.genome.jp/kegg/pathway.html/ BioCyc http://www.biocyc.org/ Reactome http://www.reactome.org/ GenMAPP http://www.genmapp.org/ BioCarta http://www.biocarta.com/ Pathguide – the pathway resource list http://www.pathguide.org/

  16. I have interactions what next? • Evaluate the quality of interactions i.e. type of method used for identification….what exactly are these methods? • Visualize these interactions as a network and analyze.

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