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HINT specifications

Information


Unique identifier OMICS_11372
Name HINT
Alternative name Hmm-based IdeNtification of Tf footprints
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability Stable
Maintained Yes

Subtool


  • Regulatory Genomics Toolbox

Versioning


No version available

Maintainer


  • person_outline Eduardo Gusmao

Publication for Hmm-based IdeNtification of Tf footprints

HINT citations

 (6)
library_books

Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes

2018
BMC Genomics
PMCID: 5780744
PMID: 29363429
DOI: 10.1186/s12864-017-4339-5

[…] anscriptional cascades, to reduce false positive predictions of enhancer-promoter associations from open chromatin regions, the identification of DNase peaks will be modified using a new tool such as HINT [].In this study, I focused on three types of immune cells and stem cells such as H1-hESC and iPSC to examine transcriptional target genes in a genome scale, since in my previous study, I examine […]

library_books

Sox5 regulates beta cell phenotype and is reduced in type 2 diabetes

2017
Nat Commun
PMCID: 5467166
PMID: 28585545
DOI: 10.1038/ncomms15652

[…] TFBS were detected using the Regulatory Genomics Toolbox (regen.googlecode.com). A region 1‚ÄČkilobases (kb) upstream of the gene promoter (Ensembl built GRCh37.p13) was used to find binding sites. Next, a motif match analysis was […]

library_books

Most brain disease associated and eQTL haplotypes are not located within transcription factor DNase seq footprints in brain

2016
Hum Mol Genet
PMCID: 5351933
PMID: 27798116
DOI: 10.1093/hmg/ddw369

[…] ovide the best estimates of true binding sites and also, unlike some other DNase-seq footprinting methods, is not reliant on the presence of TF motifs (,). Other footprint-calling algorithms, such as HINT, additionally account for sequence-specific DNase cut biases and are likely to identify a larger proportion of footprints than Wellington (). These approaches rely on the imbalance in strand-spec […]

library_books

Epigenetic program and transcription factor circuitry of dendritic cell development

2015
Nucleic Acids Res
PMCID: 4787753
PMID: 26476451
DOI: 10.1093/nar/gkv1056

[…] e details in Supplementary Data). A further enrichment analysis was performed on footprints of cell-specific H3K4me1 peaks following Gusmao et¬†al. (). This general workflow is based on tools from the Regulatory Genomics toolbox (www.regulatory-genomics.org). […]

library_books

MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome wide signatures

2015
BMC Genomics
PMCID: 4474412
PMID: 26099518
DOI: 10.1186/1471-2164-16-S7-S13

[…] fferent cell types [].Some recent algorithms have already taken advantage of histone mark information to identify individual occurrences of known motifs, such as CENTIPEDE [], CHROMIA [], FIMO [] and HINT []. Considering a large collection of TFBSs and other CRMs (cis-regulatory modules) are still unrevealed, and sources like histone modification signals can be informative, there is some space to […]

library_books

Replicative senescence is associated with nuclear reorganization and with DNA methylation at specific transcription factor binding sites

2015
Clin Epigenetics
PMCID: 4356053
PMID: 25763115
DOI: 10.1186/s13148-015-0057-5

[…] Transcription factor enrichment analysis was performed with the Regulatory Genomics Toolbox (http://www.regulatory-genomics.org). Regarding DMRs, we extended or shortened the regions to have a length of 40 bps. For up-/downregulated genes, we used 1-kb regions ups […]

Citations

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HINT institution(s)
IZKF Computational Biology Research Group, Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany; Computational RNA Biology Lab and Bioinformatics Core, Max Planck Institute for Biology of Ageing, Cologne, Germany; Department of Cell Biology, Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany; Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Medical School, Aachen, Germany; Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, Aachen, Germany; Center of Informatics, Federal University of Pernambuco, Recife, Brazil
HINT funding source(s)
Interdisciplinary Center for Clinical Research (IZKF Aachen), RWTH Aachen University Medical School, Aachen, Germany; and Brazilian research agencies: FACEPE and CNPq

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