QServer: A Biclustering Server for Prediction and Assessment of Co-Expressed Gene Clusters

Background: Biclustering is a powerful technique for identification of co-expressed gene groups under any (unspecified) substantial subset of given experimental conditions, which can be used for elucidation of transcriptionally co-regulated genes. Results: We have previously developed a biclustering algorithm, QUBIC, which can solve more general biclustering problems than previous biclustering algorithms. To fully utilize the analysis power the algorithm provides, we have developed a web server, QServer, for prediction, computational validation and analyses of co-expressed gene clusters. Specifically, the QServer has the following capabilities in addition to biclustering by QUBIC: (i) prediction and assessment of conserved cis regulatory motifs in promoter sequences of the predicted co-expressed genes; (ii) functional enrichment analyses of the predicted co-expressed gene clusters using Gene Ontology (GO) terms, and (iii) visualization capabilities in support of interactive biclustering analyses. QServer supports the biclustering and functional analysis for a wide range of organisms, including human, mouse, Arabidopsis, bacteria and archaea, whose underlying genome database will be continuously updated. Conclusion: We believe that QServer provides an easy-to-use and highly effective platform useful for hypothesis formulation and testing related to transcription co-regulation.