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Workshop Aims NMSU GO Workshop 20 May 2010. Aims of this Workshop  WIIFM? modeling examples background information about GO modeling  Strategies for.

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Presentation on theme: "Workshop Aims NMSU GO Workshop 20 May 2010. Aims of this Workshop  WIIFM? modeling examples background information about GO modeling  Strategies for."— Presentation transcript:

1 Workshop Aims NMSU GO Workshop 20 May 2010

2 Aims of this Workshop  WIIFM? modeling examples background information about GO modeling  Strategies for functional modeling of high throughput data sets (eg. arrays, proteomics, RNA-Seq)  Continued support to help with modeling

3 http://www.agbase.msstate.edu/

4 "Today’s challenge is to realise greater knowledge and understanding from the data-rich opportunities provided by modern high-throughput genomic technology." Professor Andrew Cossins, Consortium for Post-Genome Science, Chairman.

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7 What is the Gene Ontology? “a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing”  the de facto standard for functional annotation  assign functions to gene products at different levels, depending on how much is known about a gene product  is used for a diverse range of species  structured to be queried at different levels, eg: find all the chicken gene products in the genome that are involved in signal transduction zoom in on all the receptor tyrosine kinases  human readable GO function has a digital tag to allow computational analysis of large datasets

8 Who uses GO? http://www.ebi.ac.uk/GOA/users.html

9 Functional Modeling Approaches  GO analysis functional representation of gene products need to add your own GO?  Pathway analysis GO Biological Process includes some pathways, but may not be comprehensive organism specific pathway information is limited  Network analysis GO Molecular Function includes interaction data, but may not be comprehensive/hard to extract interactions – key molecules regulation of system

10 Functional Modeling Considerations  Should I add my own GO? use GOProfiler to see how much GO is available for your species use GORetriever to see how much GO is available for your dataset  Should I do GO analysis and pathway analysis and network analysis? different functional modeling methods show different aspects about your data (complementary) is this type of data available for your species (or a close ortholog)?  What tools should I use? which tools have data for your species of interest? what type of accessions are accepted? availability (commercial and freely available)

11 Key Points  Modeling is subordinate to the biological questions/hypotheses.  Together the Gene Ontology and canonical genetic networks/pathways provide the central and complementary foundation for modeling functional genomics data.  Annotation follows information and information changes daily: STEP 1 in analyzing functional genomics data is re-annotating your dataset.  There is no “right answer”: different ways of looking at your data will give you different insights.

12  Tools and materials from this workshop will be available online at the AgBase database Educational Resources link.  For continuing support and assistance please contact: agbase@cse.msstate.edu This workshop is supported by USDA CSREES grant number MISV-329140.


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