ArticleBriefings in bioinformatics2013
Motif discovery and transcription factor binding sites before and after the next-generation sequencing era.
Article in Briefings in bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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Who cites it
52 citing papers in PubMed, 150 citations in OpenAlex.
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- NetREX-CF integrates incomplete transcription factor data with gene expression to reconstruct gene regulatory networks.Communications biology · 2022Article
- Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data.Briefings in bioinformatics · 2022Article
- A survey on deep learning in DNA/RNA motif mining.Briefings in bioinformatics · 2021Article
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- Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application toJournal of the Royal Society, Interface · 2020Article
- Integrating Peak Colocalization and Motif Enrichment Analysis for the Discovery of Genome-Wide Regulatory Modules and Transcription Factor Recruitment Rules.Frontiers in genetics · 2020Article
- Seq-ing answers: Current data integration approaches to uncover mechanisms of transcriptional regulation.Computational and structural biotechnology journal · 2020Review
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motif discovery has been one of the most widely studied problems in bioinformatics ever since genomic and protein sequences have been available. In particular, its application to the de novo prediction of putative over-represented transcription factor binding sites in nucleotide sequences has been, and still is, one of the most challenging flavors of the problem. Recently, novel experimental techniques like chromatin immunoprecipitation (ChIP) have been introduced, permitting the genome-wide identification of protein-DNA interactions. ChIP, applied to transcription factors and coupled with genome tiling arrays (ChIP on Chip) or next-generation sequencing technologies (ChIP-Seq) has opened new avenues in research, as well as posed new challenges to bioinformaticians developing algorithms and methods for motif discovery.
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