ArticleNucleic acids research2012
CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model.BioMed research international · 2017Article
- Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells.Frontiers in genetics · 2016Review
- Article
- GAMI-CRM: Using de novo motif inference to detect cis-regulatory modules.Proceedings of the ... Congress on Evolutionary Computation. Congress on Evolutionary Computation · 2014Article
- CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining.PloS one · 2014Article
- HOCOMOCO: a comprehensive collection of human transcription factor binding sites models.Nucleic acids research · 2013Article
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Authors and funding
5 authors at 4 institutions in 5 countries.
Funding
Abstract
Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.
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