DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli

Lemmens, Kim; Bie, Tijl De; Dhollander, Thomas; Keersmaecker, Sigrid C. J. De; Thijs, Inge M; Schoofs, Geert; Weerdt, Ami De; Moor, Bart De; Vanderleyden, Jos; Collado‐Vides, Julio; Engelen, Kristof; Marchal, Kathleen

doi:10.1186/gb-2009-10-3-r27

Cited by 53 publications

(60 citation statements)

References 71 publications

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“…We first generate an ensemble of querybased biclustering solutions by running QDB [5] for each gene from the query-list separately on an E. coli gene expression compendium [8]. This results in 44 query-driven biclustering solutions (not for all query-genes a solution could be obtained) that at least partially overlap: 23/44 QDB-outcomes show an overlap of at least 50% (geometric coefficient) with at least one other QDB-outcome.…”

Section: Resultsmentioning

confidence: 99%

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An ensemble method for querying gene expression compendia with experimental lists

Smet

Marchal

2010

2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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Query-based biclustering can be used to explore public gene expression data for genes coexpressed with genes of interest to a certain researcher (the query). These methods, however, fail when faced with a list of query-genes with diverse expression profiles. In addition, a threshold on the minimal coexpression with the query-genes needs to be defined in advance. To deal with these problems we introduce an ensemble approach for query-based biclustering. The method relies on a specifically designed consensus matrix in which the biclustering outcomes for multiple query-genes and for different possible coexpression thresholds are merged in a statistically robust way. Graph clustering is used to obtain non-redundant consensus biclusters from this matrix. We tested out different ensemble construction schemes and illustrate the effectiveness of this approach

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Section: Resultsmentioning

confidence: 99%

“…An Escherichia coli cross-platform gene expression compendium containing 4557 genes and 870 conditions derived from publicly available gene expression data was used [8]. A query-list was obtained from an E. coli FNR ChIP-chip experiment [9].…”

Section: A Datasetsmentioning

confidence: 99%

An ensemble method for querying gene expression compendia with experimental lists

Smet

Marchal

2010

2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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“…To demonstrate that our tool can assist a user in analyzing the output of a module detection tool, it was applied on the results obtained by DISTILLER [6]. DISTILLER is a data integration tool that uses expression data and regulatory motif data to identify modules together with their regulatory program.…”

Section: Resultsmentioning

confidence: 99%

Layout and Post-Processing of Transcriptional Modules

Sun

Bulcke

Moor

et al. 2009

2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing

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Visualization of transcriptional modules together with their transcriptional program is a non-trivial task. We have therefore developed a module visualization tool that allows visualizing overlapping transcriptional modules in a very intuitive way. By visualizing not only the genes and the experiments in which the genes are co-expressed, but also additional properties of the modules such as the regulators and regulatory motifs that are responsible for the observed coexpression, our tool can assist in the biological analysis and interpretation of the output of module detection tools.

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“…Whereas ARACNE is dedicated to mammalians, SEREND (SEmi-supervised REgulatory Network Discoverer) 39) , SIRENE 40) and DISTILLER 41) are gene network reconstruction systems developed and tested specific for data derived from experiments with E. coli . Subsequent experimental validation of the performance of these methods at the genome scale had to be done.…”

Section: Gene Regulation Network Inference Methodsmentioning

confidence: 99%

Data resources and mining tools for reconstructing gene regulatory networks in Lactococcus lactis

Jong

Kuipers

2011

Jpn. J. Lactic Acid Bact.

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complete sequenced lactococci genomes is increasing, while the majority of the strains will only be studied in silico. This review focuses on the visualization and mining of the complex transcription and translation systems via interactive graphics and network reconstruction tools and the amalgamation of DNA microarray data with biological data that together lead to the reconstruction of gene regulatory networks (GRN). These networks are a valuable source of information and knowledge that can be used for studying L. lactis physiology and provide clues for improving industrial strains by either non-GMO methods (strain selection, fermentation condition) or by specific engineering.

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DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli

Cited by 53 publications

References 71 publications

An ensemble method for querying gene expression compendia with experimental lists

An ensemble method for querying gene expression compendia with experimental lists

Layout and Post-Processing of Transcriptional Modules

Data resources and mining tools for reconstructing gene regulatory networks in Lactococcus lactis

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