DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites.

Background: A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted with the seemingly arbitrary choice between numerous algorithms to perform cluster analysis.

Results: We developed an exploratory application that benchmarks the results of clustering methods using functional annotations.

FIVA: Functional Information Viewer and Analyzer extracting biological knowledge from transcriptome data of prokaryotes.

Unlabelled: FIVA (Function Information Viewer and Analyzer) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software assists in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes.

Availability: http://bioinformatics.