01646nas a2200217 4500008004100000245007200041210006900113300001000182490000800192520083200200653001501032653002101047653007301068653002601141653004201167653005901209100001501268700002401283700001501307856010601322 2006 eng d00aOntology-driven approaches to analyzing data in functional genomics0 aOntologydriven approaches to analyzing data in functional genomi a67-860 v3163 a
Ontologies are fundamental knowledge representations that provide not only standards for annotating and indexing biological information, but also the basis for implementing functional classification and interpretation models. This chapter discusses the application of gene ontology (GO) for predictive tasks in functional genomics. It focuses on the problem of analyzing functional patterns associated with gene products. This chapter is divided into two main parts. The first part overviews GO and its applications for the development of functional classification models. The second part presents two methods for the characterization of genomic information using GO. It discusses methods for measuring functional similarity of gene products, and a tool for supporting gene expression clustering analysis and validation.
10ababelomics10aCluster Analysis10aCluster Analysis Computational Biology/*methods *Data Interpretation10aComputational Biology10aStatistical Gene Expression Profiling10aStatistical Gene Expression Profiling *Genomics Humans1 aAzuaje, F.1 aAl-Shahrour, Fatima1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16671401