HOCOMOCO: towards a complete collection of transcription factor binding models for human and mouse via large-scale ChIP-Seq analysis
By I. Kulakovskiy, I. Vorontsov, I. Yevshin, R. Sharipov, A. D. Fedorova, Eugene I. Rumynskiy, Y. Medvedeva, A. Magana-Mora, Vladimir B. Bajic, Dmitri A. Papatsenko and 2 more. Nucleic Acids Res., 2017
796 citations recorded by the source corpus.
Abstract We present a major update of the HOCOMOCO collection that consists of patterns describing DNA binding specificities for human and mouse transcription factors. In this release, we profited from a nearly doubled volume of published in vivo experiments on transcription factor (TF) binding to expand the repertoire of binding models, replace low-quality models previously based on in vitro data only and cover more than a hundred TFs with previously unknown binding specificities. This was achieved by systematic motif discovery from more than five thousand ChIP-Seq experiments uniformly processed within the BioUML framework with several ChIP-Seq peak calling tools and aggregated in the GTRD database. HOCOMOCO v11 contains binding models for 453 mouse and 680 human transcription factors and includes 1302 mononucleotide and 576 dinucleotide position weight matrices, which describe primary binding preferences of each transcription factor and reliable alternative binding specificities. An interactive interface and bulk downloads are available on the web: http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco11. In this release, we complement HOCOMOCO by MoLoTool (Motif Location Toolbox, http://molotool.autosome.ru) that applies HOCOMOCO models for visualization of binding sites in short DNA sequences.
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/8aa51f8760e9d7c4073ffaae17118f415a3b26b7
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Citations in the corpus
- Benchmark and integration of resources for the estimation of human transcription factor activities (2018, methodology): “2018), (3) TFBS predictions on gene promoters using TF binding motifs from HOCOMOCO (Kulakovskiy et al. 2018) and JASPAR (Khan et al.”
- The Polygenic and Monogenic Basis of Blood Traits and Diseases (2020, methodology): “Whole-genome sequencing of rare disease patients in a national healthcare system (bioRxiv) https://www.genomicsengland.co.uk/ about-gecip/joining-researchcommunity/ Ensembl v99 EMBL-EBI https://www.ensembl.org/index.html; HOCOMOCO (Kulakovskiy et al., 2018) https://repository.kaust.edu.sa/handle/ 10”
- AnimalTFDB 3.0: a comprehensive resource for annotation and prediction of animal transcription factors (2018, methodology): “Furthermore, TFBS for 18,952 TFs of 51 species were integrated from HOCOMOCO (21), TRANSFAC, JASPAR (22) and CIS-BP databases.”
- hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets (2019, methodology): “The HOCOMOCO [22], JASPAR [23], TRANSFAC v2018 [24], and TFBSbank [31] databases focus on the collection and discovery of the motif profiles for TFBSs, while TRRUST elucidates TF–target interactions using text mining [13]. hTFtarget is the only currently available database integrating various resour”