MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model
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We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding-site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces , we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.
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There is an inverse relationship between the degeneracy of columns within an RNAcompete motif and the evolutionary conservation of the matching bases within the predicted binding site in transcripts.
“there is an inverse relationship between the degeneracy of columns within an RNAcompete motif and the evolutionary conservation of the matching bases within the predicted binding site in transcripts”
From A compendium of RNA-binding motifs for decoding gene regulation (2013) · cites this paper as [23]
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- Authors
- Moses, A. M., Chiang, D. Y., Pollard, D. A., Iyer, V. N., & Eisen, M. B.
- Affiliations
- University of California, Berkeley (US)
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Eisen, Michael B
- Venue
- Genome Biology
- Published
- 2004-11-30
- Volume
- 5
- Issue
- 12
- Pages
- R98-R98
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC545801
- OpenAlex
- W2109314645
- Cited by
- 153
- References
- 53
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2022: 1 · 2021: 4 · 2018: 1 · 2017: 4 · 2016: 4 · 2015: 3 · 2014: 4 · 2013: 6 · 2012: 12
- FWCI
- 6.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- University of North Texas Digital Library (University of North Texas) (submittedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- National Human Genome Research Institute (R01HG002779)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- transcription factor binding sites, conserved binding sites, binding site evolution, Saccharomyces, phylogenetic distance
- MeSH terms
- Binding Sites, DNA, DNA-Binding Proteins, DNA, Fungal, Biological Evolution, Gene Expression Regulation, Models, Genetic, Saccharomyces cerevisiae, Software, Species Specificity, Transcription Factors, Sequence Alignment, Conserved Sequence, Saccharomyces cerevisiae Proteins
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