ArticleNucleic acids research2006
Composite Module Analyst: identification of transcription factor binding site combinations using genetic algorithm.
Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
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- Motif and conserved module analysis in DNA (promoters, enhancers) and RNA (lncRNA, mRNA) using AlModules.Scientific reports · 2022Article
- Transcriptome Analysis Reveals Intrinsic Proinflammatory Signaling in Healthy African American Skin.The Journal of investigative dermatology · 2022Article
- Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer.Gastro hep advances · 2022Article
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- Signaling Pathways Potentially Responsible for Foam Cell Formation: Cholesterol Accumulation or Inflammatory Response-What is First?International journal of molecular sciences · 2020Article
- Role of Phagocytosis in the Pro-Inflammatory Response in LDL-Induced Foam Cell Formation; a Transcriptome Analysis.International journal of molecular sciences · 2020Article
- Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer.BMC bioinformatics · 2019Article
- Computational master-regulator search reveals mTOR and PI3K pathways responsible for low sensitivity of NCI-H292 and A427 lung cancer cell lines to cytotoxic action of p53 activator Nutlin-3.BMC medical genomics · 2018Article
- Modified LDL Particles Activate Inflammatory Pathways in Monocyte-derived Macrophages: Transcriptome Analysis.Current pharmaceutical design · 2018Article
- Data on master regulators and transcription factor binding sites found by upstream analysis of multi-omics data on methotrexate resistance of colon cancer.Data in brief · 2017Article
- Multi-omics "upstream analysis" of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer.EuPA open proteomics · 2016Article
- Prediction of protein-DNA interactions of transcription factors linking proteomics and transcriptomics data.EuPA open proteomics · 2016Article
- Characterization and identification of cis-regulatory elements in Arabidopsis based on single-nucleotide polymorphism information.Plant physiology · 2014Article
- MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters.BMC bioinformatics · 2013Article
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Authors and funding
9 authors.
Funding
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Abstract
Composite Module Analyst (CMA) is a novel software tool aiming to identify promoter-enhancer models based on the composition of transcription factor (TF) binding sites and their pairs. CMA is closely interconnected with the TRANSFAC database. In particular, CMA uses the positional weight matrix (PWM) library collected in TRANSFAC and therefore provides the possibility to search for a large variety of different TF binding sites. We model the structure of the long gene regulatory regions by a Boolean function that joins several local modules, each consisting of co-localized TF binding sites. Having as an input a set of co-regulated genes, CMA builds the promoter model and optimizes the parameters of the model automatically by applying a genetic-regression algorithm. We use a multicomponent fitness function of the algorithm which includes several statistical criteria in a weighted linear function. We show examples of successful application of CMA to a microarray data on transcription profiling of TNF-alpha stimulated primary human endothelial cells. The CMA web server is freely accessible at http://www.gene-regulation.com/pub/programs/cma/CMA.html. An advanced version of CMA is also a part of the commercial system ExPlaintrade mark (www.biobase.de) designed for causal analysis of gene expression data.
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