Background: Expression array data are used to predict biological functions of uncharacterized genes by comparing their expression profiles to those of characterized genes. While b...
Background: Availability of high-resolution RNA crystal structures for the 30S and 50S ribosomal subunits and the subsequent validation of comparative secondary structure models h...
Yadhu Kumar, Ralf Westram, Peter Kipfer, Harald Me...
Background: Microarray technology produces gene expression data on a genomic scale for an endless variety of organisms and conditions. However, this vast amount of information nee...
Background: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the G...
Background: Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functiona...
Steffen Klamt, Julio Saez-Rodriguez, Jonathan A. L...
Background: High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that...
Kyoungmi Kim, Grier P. Page, T. Mark Beasley, Step...
Background: Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is informati...
Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. ...