Computational prediction of transcription-factor binding site locations

By Martha L. Bulyk. Genome Biology, 2003

332 citations recorded by the source corpus.

Identifying genomic locations of transcription-factor binding sites, particularly in higher eukaryotic genomes, has been an enormous challenge. Various experimental and computational approaches have been used to detect these sites; methods involving computational comparisons of related genomes have been particularly successful.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/94d37a6ecf1f5264a161d4346db423c436446324

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In Molecular Biology

Citations in the corpus

iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections (2014, background): “Although a lot of progress has been made over the last decade and many motif discovery methods have been developed and refined (reviewed in [16–19]), motif discovery methods alone are not sufficient to map a gene regulatory network, nor can they be applied to noisy gene sets containing mixtures of…”
Non-coding nuclear DNA markers in phylogenetic reconstruction (2009, methodology): “The method most frequently applied for the determination of transcription factor binding sites within promoter regions is phylogenetic footprinting (Wasserman et al. 2000; Bulyk 2003; Weitzman 2003; Zhang and Gerstein 2003).”
Discovering Motifs in Ranked Lists of DNA Sequences (2007, background): “Several excellent reviews narrate the different strategies for motif detection and use quantitative benchmarking to compare their performance [25, 26, 27, 28, 29].”
Learning from mistakes: Accurate prediction of cell type-specific transcription factor binding (2017, background): “However, it soon became evident that in-silico binding site predictions based on sequence motifs alone are insuﬃcient to explain in-vivo bind-42 ing of TFs and that determinants beyond sequence speciﬁcity likely play an important role (Stormo and Fields, 1998; Bulyk, 2003).”
DBD––taxonomically broad transcription factor predictions: new content and functionality (2007, background): “Sequence-specific DNA-binding transcription factors (TFs) each recognize a family of cis-regulatory DNA sequences described by a consensus motif (1) or positionspecific weight matrix ( 2 ).”