ArticleBioinformatics (Oxford, England)2011
CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Improved linking of motifs to their TFs using domain information.Bioinformatics (Oxford, England) · 2020Pooled it
- MODSIDE: a motif discovery pipeline and similarity detector.BMC genomics · 2018Article
- Novel dual regulators of Pseudomonas aeruginosa essential for productive biofilms and virulence.Molecular microbiology · 2018Article
- TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets.BMC genomics · 2018Article
- MOTIFSIM 2.1: An Enhanced Software Platform for Detecting Similarity in Multiple DNA Motif Data Sets.Journal of computational biology : a journal of computational molecular cell biology · 2017Article
- Androgen receptor transcriptionally regulates semaphorin 3C in a GATA2-dependent manner.Oncotarget · 2017Article
- A novel comparative pattern analysis approach identifies chronic alcohol mediated dysregulation of transcriptomic dynamics during liver regeneration.BMC genomics · 2016Article
- A novel comparative pattern count analysis reveals a chronic ethanol-induced dynamic shift in immediate early NF-κB genome-wide promoter binding during liver regeneration.Molecular bioSystems · 2016Article
- HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models.Nucleic acids research · 2016Article
- BolA is a transcriptional switch that turns off motility and turns on biofilm development.mBio · 2015Article
- iRegulon: from a gene list to a gene regulatory network using large motif and track collections.PLoS computational biology · 2014Article
- A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data.Biology direct · 2014Review
- Application of experimentally verified transcription factor binding sites models for computational analysis of ChIP-Seq data.BMC genomics · 2014Article
- Motif-based analysis of large nucleotide data sets using MEME-ChIP.Nature protocols · 2014Article
- Chromatin accessibility: a window into the genome.Epigenetics & chromatin · 2014Review
- Estrogen represses gene expression through reconfiguring chromatin structures.Nucleic acids research · 2013Article
- Motif discovery and transcription factor binding sites before and after the next-generation sequencing era.Briefings in bioinformatics · 2013Article
- MotifLab: a tools and data integration workbench for motif discovery and regulatory sequence analysis.BMC bioinformatics · 2013Article
- HOCOMOCO: a comprehensive collection of human transcription factor binding sites models.Nucleic acids research · 2013Article
- Practical guidelines for the comprehensive analysis of ChIP-seq data.PLoS computational biology · 2013Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
unlabelledCompleteMOTIFs (cMOTIFs) is an integrated web tool developed to facilitate systematic discovery of overrepresented transcription factor binding motifs from high-throughput chromatin immunoprecipitation experiments. Comprehensive annotations and Boolean logic operations on multiple peak locations enable users to focus on genomic regions of interest for de novo motif discovery using tools such as MEME, Weeder and ChIPMunk. The pipeline incorporates a scanning tool for known motifs from TRANSFAC and JASPAR databases, and performs an enrichment test using local or precalculated background models that significantly improve the motif scanning result. Furthermore, using the cMOTIFs pipeline, we demonstrated that multiple transcription factors could cooperatively bind to the upstream of important stem cell differentiation regulators. AVAILABILITY: http://cmotifs.tchlab.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.