Workshop Aims GO Workshop 3-6 August 2010

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

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

"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.

Workshop Aims: understand how ontologies can be used to organise data learn about the Gene Ontology (GO) and how it can help you model functional genomics data gain experience in using GO based tools for functional modeling discussion of bioinformatics resources required to support functional modeling of IITA crops data continuing support via the AgBase database

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

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)

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.

For continuing support and assistance please contact: 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 NABDA and the USDA CSREES