|Title||Ontology-driven approaches to analyzing data in functional genomics|
|Publication Type||Journal Article|
|Year of Publication||2006|
|Authors||Azuaje, F, Al-Shahrour, F, Dopazo, J|
|Journal||Methods Mol Biol|
|Keywords||babelomics; Cluster Analysis; Cluster Analysis Computational Biology/*methods *Data Interpretation; Computational Biology; Statistical Gene Expression Profiling; Statistical Gene Expression Profiling *Genomics Humans|
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.
Azuaje, Francisco Al-Shahrour, Fatima Dopazo, Joaquin Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t Review United States Methods in molecular biology (Clifton, N.J.) Methods Mol Biol. 2006;316:67-86.