ArticleBioinformatics (Oxford, England)2009
Predicting functionality of protein-DNA interactions by integrating diverse evidence.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 40 citations in OpenAlex.
- White-opaque switching inMicrobiology and molecular biology reviews : MMBR · 2024Review
- Article
- Biotinylated Tn5 transposase-mediated CUT&Tag efficiently profiles transcription factor-DNA interactions in plants.Plant biotechnology journal · 2023Article
- Validating a re-implementation of an algorithm to integrate transcriptome and ChIP-seq data.PeerJ · 2023Article
- Integrating binding and expression data to predict transcription factors combined function.BMC genomics · 2020Article
- Lessons from eRNAs: understanding transcriptional regulation through the lens of nascent RNAs.Transcription · 2020Review
- Binding Sites in the EFG1 Promoter for Transcription Factors in a Proposed Regulatory Network: A Functional Analysis in the White and Opaque Phases of Candida albicans.G3 (Bethesda, Md.) · 2016Article
- High-Throughput Identification of Cis-Regulatory Rewiring Events in Yeast.Molecular biology and evolution · 2015Article
- p53-dependent gene repression through p21 is mediated by recruitment of E2F4 repression complexes.Oncogene · 2014Article
- Assessing computational methods for transcription factor target gene identification based on ChIP-seq data.PLoS computational biology · 2013Article
- Inferring functional transcription factor-gene binding pairs by integrating transcription factor binding data with transcription factor knockout data.BMC systems biology · 2013Article
- Transcription factors: from enhancer binding to developmental control.Nature reviews. Genetics · 2012Review
- Extracting regulator activity profiles by integration of de novo motifs and expression data: characterizing key regulators of nutrient depletion responses in Streptomyces coelicolor.Nucleic acids research · 2012Article
- Learning transcriptional regulation on a genome scale: a theoretical analysis based on gene expression data.Briefings in bioinformatics · 2012Review
- Chromatin-driven de novo discovery of DNA binding motifs in the human malaria parasite.BMC genomics · 2011Article
- Leveraging domain information to restructure biological prediction.BMC bioinformatics · 2011Article
- GRISOTTO: A greedy approach to improve combinatorial algorithms for motif discovery with prior knowledge.Algorithms for molecular biology : AMB · 2011Article
- Computational study of associations between histone modification and protein-DNA binding in yeast genome by integrating diverse information.BMC genomics · 2011Article
- Exploring and exploiting disease interactions from multi-relational gene and phenotype networks.PloS one · 2011Article
- Dynamic CRM occupancy reflects a temporal map of developmental progression.Molecular systems biology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chromatin immunoprecipitation (ChIP-chip) experiments enable capturing physical interactions between regulatory proteins and DNA in vivo. However, measurement of chromatin binding alone is not sufficient to detect regulatory interactions. A detected binding event may not be biologically relevant, or a known regulatory interaction might not be observed under the growth conditions tested so far. To correctly identify physical interactions between transcription factors (TFs) and genes and to determine their regulatory implications under various experimental conditions, we integrated ChIP-chip data with motif binding sites, nucleosome occupancy and mRNA expression datasets within a probabilistic framework. This framework was specifically tailored for the identification of functional and non-functional DNA binding events. Using this, we estimate that only 50% of condition-specific protein-DNA binding in budding yeast is functional. We further investigated the molecular factors determining the functionality of protein-DNA interactions under diverse growth conditions. Our analysis suggests that the functionality of binding is highly condition-specific and highly dependent on the presence of specific cofactors. Hence, the joint analysis of both, functional and non-functional DNA binding, may lend important new insights into transcriptional regulation.
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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.