HOCOMOCO: A comprehensive collection of human transcription factor binding sites models
AuthorsKulakovskiy, Ivan V.
Kasianov, Artem S.
Vorontsov, Ilya E.
Bajic, Vladimir B.
Makeev, Vsevolod J.
KAUST DepartmentApplied Mathematics and Computational Science Program
Computational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Online Publication Date2012-11-21
Print Publication Date2013-01-01
Permanent link to this recordhttp://hdl.handle.net/10754/325453
MetadataShow full item record
AbstractTranscription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/ hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source. The Author(s) 2012.
CitationKulakovskiy IV, Medvedeva YA, Schaefer U, Kasianov AS, Vorontsov IE, et al. (2012) HOCOMOCO: a comprehensive collection of human transcription factor binding sites models. Nucleic Acids Research 41: D195-D202. doi:10.1093/nar/gks1089.
PublisherOxford University Press (OUP)
JournalNucleic Acids Research
PubMed Central IDPMC3531053
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- Issue date: 2016 Jan 4
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- Issue date: 2018 Jan 4
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- Authors: Khamis AM, Motwalli O, Oliva R, Jankovic BR, Medvedeva YA, Ashoor H, Essack M, Gao X, Bajic VB
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- Authors: Bülow L, Brill Y, Hehl R
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A deeper look into transcription regulatory code by preferred pair distance templates for transcription factor binding sitesKulakovskiy, Ivan V.; Belostotsky, A. A.; Kasianov, Artem S.; Esipova, Natalia G.; Medvedeva, Yulia; Eliseeva, Irina A.; Makeev, Vsevolod J. (Bioinformatics, Oxford University Press (OUP), 2011-08-18) [Article]Motivation: Modern experimental methods provide substantial information on protein-DNA recognition. Studying arrangements of transcription factor binding sites (TFBSs) of interacting transcription factors (TFs) advances understanding of the transcription regulatory code. Results: We constructed binding motifs for TFs forming a complex with HIF-1α at the erythropoietin 3'-enhancer. Corresponding TFBSs were predicted in the segments around transcription start sites (TSSs) of all human genes. Using the genome-wide set of regulatory regions, we observed several strongly preferred distances between hypoxia-responsive element (HRE) and binding sites of a particular cofactor protein. The set of preferred distances was called as a preferred pair distance template (PPDT). PPDT dramatically depended on the TF and orientation of its binding sites relative to HRE. PPDT evaluated from the genome-wide set of regulatory sequences was used to detect significant PPDT-consistent binding site pairs in regulatory regions of hypoxia-responsive genes. We believe PPDT can help to reveal the layout of eukaryotic regulatory segments. © The Author 2011. Published by Oxford University Press. All rights reserved.