:: DESCRIPTION
ModuleDigger is an itemset mining based strategy for computationally detecting cis-regulatory modules (CRMs) in a set of genes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
BMC Bioinformatics. 2009 Jan 30;10 Suppl 1:S30.
ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules.
Sun H, De Bie T, Storms V, Fu Q, Dhollander T, Lemmens K, Verstuyf A, De Moor B, Marchal K.
:: DESCRIPTION
CisModule: A Bayesian module sampler by hierachical mixture modeling
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Zhou, Q. and Wong, W.H. (2004).
CisModule: De novo discovery of cis-regulatory modules by hierarchical mixture modeling.
Proceedings of the National Academy of Sciences USA, 101: 12114-12119.
:: DESCRIPTION
INSECT (IN-silico SEarch for Co-occurring Transcription factors) is an easy-to-use and powerful web server for biologists analysing genomic sequence data for in silico cis-regulatory modules prediction and analysis.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
INSECT 2.0: a web-server for genome-wide cis-regulatory modules prediction.
Parra RG, Rohr CO, Koile D, Perez-Castro C, Yankilevich P.
Bioinformatics. 2015 Dec 12. pii: btv726.
:: DESCRIPTION
PhylCRM is a new cis-regulatory module (CRM) prediction algorithm. PhylCRM combines data for individual motif occurances scored on an alignment using previously described MONKEY scoring sheme (Moses et al., Genome Biology 5, R98, 2004) into a single CRM prediction. PhylCRM can scan very long genomic sequences for candidate CRMs by quantifying both motif clustering and conservation across arbitrarily many genomes using an evolutionary model consistent with the phylogeny of the genomes.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Nat Methods. 2008 Apr;5(4):347-53. doi: 10.1038/nmeth.1188. Epub 2008 Mar 2.
Systematic identification of mammalian regulatory motifs’ target genes and functions.
Warner JB, Philippakis AA, Jaeger SA, He FS, Lin J, Bulyk ML.
:: DESCRIPTION
i-cisTarget is an integrative genomics method for the prediction of regulatory features (motifs and in vivo features), and cis-regulatory modules in Drosophila
::DEVELOPER
Laboratory of Computational Biology @ the Center for Human Genetics (CME), at the Faculty of Medicine
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: MORE INFORMATION
Citation
Nucleic Acids Res. 2012 Aug;40(15):e114. doi: 10.1093/nar/gks543. Epub 2012 Jun 20.
i-cisTarget: an integrative genomics method for the prediction of regulatory features and cis-regulatory modules.
Herrmann C1, Van de Sande B, Potier D, Aerts S.
:: DESCRIPTION
MOPAT (Motif Pair Tree) identifies CRMs through the identification of motif modules, groups of motifs co-ccurring in multiple CRMs. It can identify orthologous CRMs without multiple alignments. It can also find CRMs given a large number of known motifs.
::DEVELOPER
Data Integration and Knowledge Discovery Lab
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
Hu J, Hu H, Li X.
MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs.
Nucleic Acids Res. 2008; 36(13):4488-97
:: DESCRIPTION
MORPH: Probabilistic alignment combined with hidden Markov models of cis-regulatory modules
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation:
MORPH: probabilistic alignment combined with hidden Markov models of cis-regulatory modules.
Sinha S, He X.
PLoS Comput Biol. 2007 Nov;3(11):e216.
:: DESCRIPTION
ModuleMaster is a novel application for finding cis-regulatory modules (CRMs) in sets of co-expressed genes. The application comes with a newly developed method which not only considers transcription factor binding information but also multivariate functional relationships between regulators and target genes to improve the detection of CRMs. Given only the results of a microarray and a subsequent clustering experiment, the program includes all necessary data and algorithms to perform every step to find CRMs.
::DEVELOPER
the Center for Bioinformatics Tübingen (Zentrum für Bioinformatik Tübingen, ZBIT).
:: SCREENSHOTS
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Biosystems. 2010 Jan;99(1):79-81. doi: 10.1016/j.biosystems.2009.09.005. Epub 2009 Oct 9.
ModuleMaster: a new tool to decipher transcriptional regulatory networks.
Wrzodek C, Schröder A, Dräger A, Wanke D, Berendzen KW, Kronfeld M, Harter K, Zell A.
:: DESCRIPTION
CisPlusFinder predicts cis-regulatory modules based on perfect local ungapped sequences using comparative sequence data from multiple organisms.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Pierstorff, N., C.M. Bergman & T. Wiehe. (2006)
Identifying cis-regulatory modules by combining comparative and compositional analysis of DNA.
Bioinformatics 22:2858-2864.
:: DESCRIPTION
bbq (Barbeques) is a command-line tool for discovering clusters of transcription factor binding sites that occur simultaneously in several genome sequences. Finding such clusters – which are sometimes also referred to as cis-regulatory modules – is done in a multiple-alignment-like fashion by solving a certain combinatorial and geometric optimization problem, the so-called best barbeque problem (explaining the name bbq). As opposed to classical, typically dynamic programming based, alignment procedures, the order of the binding sites’ occurences can be arbitrarily shuffled, so that bbq is the result of developing completely new algorithms.
::DEVELOPER
:: SCREENSHOTS
N/A
:: REQUIREMENTS
:: DOWNLOAD
:: MORE INFORMATION
Citation
Detecting Phylogenetic Footprint Clusters by Optimizing Barbeques
Axel Mosig, Türker Biyikoglu, Sonja J. Prohaska, Peter F. Stadler
