Ontologizing gene-expression microarray data: characterizing clusters with Gene Ontology

Peter N Robinson; Andreas Wollstein; Ulrike Böhme; Brad Beattie

doi:10.1093/bioinformatics/bth040

Ontologizing gene-expression microarray data: characterizing clusters with Gene Ontology

Bioinformatics. 2004 Apr 12;20(6):979-81. doi: 10.1093/bioinformatics/bth040. Epub 2004 Feb 5.

Authors

Peter N Robinson¹, Andreas Wollstein, Ulrike Böhme, Brad Beattie

Affiliation

¹ Institute of Medical Genetics, Charité University Hospital, Humboldt University, Augustenburger Platz 1, 13353 Berlin, Germany. peter.robinson@charite.de

PMID: 14764576
DOI: 10.1093/bioinformatics/bth040

Abstract

An XML-based Java application is described that provides a function-oriented overview of the results of cluster analysis of gene-expression microarray data based on Gene Ontology terms and associations. The application generates one HTML page with listings of the frequencies of explicit and implicit Gene Ontology annotations for each cluster, and separate, linked pages with listings of explicit annotations for each gene in a cluster.

MeSH terms

Cluster Analysis
DNA / classification*
DNA / genetics*
Gene Expression Profiling / methods*
Hypermedia
Information Storage and Retrieval / methods*
Natural Language Processing*
Oligonucleotide Array Sequence Analysis / methods*
Phylogeny
Software
User-Computer Interface*
Vocabulary, Controlled*

Substances

DNA