ArticlePloS one2012
QServer: a biclustering server for prediction and assessment of co-expressed gene clusters.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Gene differential co-expression analysis of male infertility patients based on statistical and machine learning methods.Frontiers in microbiology · 2023Article
- QUBIC2: a novel and robust biclustering algorithm for analyses and interpretation of large-scale RNA-Seq data.Bioinformatics (Oxford, England) · 2020Article
- It is time to apply biclustering: a comprehensive review of biclustering applications in biological and biomedical data.Briefings in bioinformatics · 2019Review
- Bacterial regulon modeling and prediction based on systematic cis regulatory motif analyses.Scientific reports · 2016Article
- Computational analyses of transcriptomic data reveal the dynamic organization of the Escherichia coli chromosome under different conditions.Nucleic acids research · 2013Article
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Authors and funding
4 authors.
Funding
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Abstract
backgroundBiclustering 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.
resultsWe 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.
conclusionWe believe that QServer provides an easy-to-use and highly effective platform useful for hypothesis formulation and testing related to transcription co-regulation.
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