ArticleProceedings of the National Academy of Sciences of the United States of America2007
Connecting protein structure with predictions of regulatory sites.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- Predicting bacterial transcription factor binding sites through machine learning and structural characterization based on DNA duplex stability.Briefings in bioinformatics · 2024Article
- Less-is-more: selecting transcription factor binding regions informative for motif inference.Nucleic acids research · 2024Article
- Comparative Analysis of the IclR-Family of Bacterial Transcription Factors and Their DNA-Binding Motifs: Structure, Positioning, Co-Evolution, Regulon Content.Frontiers in microbiology · 2021Article
- Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Transcriptional Profiling ofG3 (Bethesda, Md.) · 2018Article
- Predicting transcription factor binding motifs from DNA-binding domains, chromatin accessibility and gene expression data.Nucleic acids research · 2017Article
- Article
- Unraveling determinants of transcription factor binding outside the core binding site.Genome research · 2015Article
- Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism.Nucleic acids research · 2015Article
- GntR Family of Bacterial Transcription Factors and Their DNA Binding Motifs: Structure, Positioning and Co-Evolution.PloS one · 2015Article
- Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes.Nucleic acids research · 2014Article
- Article
- Mapping yeast transcriptional networks.Genetics · 2013Review
- A comprehensive functional portrait of two heat shock factor-type transcriptional regulators involved in Candida albicans morphogenesis and virulence.PLoS pathogens · 2013Article
- An Exploration Into Improving DNA Motif Inference by Looking for Highly Conserved Core Regions.IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology proceedings. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology · 2013Article
- The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.PLoS computational biology · 2013Article
- Improved predictions of transcription factor binding sites using physicochemical features of DNA.Nucleic acids research · 2012Article
- A flexible integrative approach based on random forest improves prediction of transcription factor binding sites.Nucleic acids research · 2012Article
- DBD2BS: connecting a DNA-binding protein with its binding sites.Nucleic acids research · 2012Article
- Towards a theoretical understanding of false positives in DNA motif finding.BMC bioinformatics · 2012Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
A common task posed by microarray experiments is to infer the binding site preferences for a known transcription factor from a collection of genes that it regulates and to ascertain whether the factor acts alone or in a complex. The converse problem can also be posed: Given a collection of binding sites, can the regulatory factor or complex of factors be inferred? Both tasks are substantially facilitated by using relatively simple homology models for protein-DNA interactions, as well as the rapidly expanding protein structure database. For budding yeast, we are able to construct reliable structural models for 67 transcription factors and with them redetermine factor binding sites by using a Bayesian Gibbs sampling algorithm and an extensive protein localization data set. For 49 factors in common with a prior analysis of this data set (based largely on phylogenetic conservation), we find that half of the previously predicted binding motifs are in need of some revision. We also solve the inverse problem of ascertaining the factors from the binding sites by assigning a correct protein fold to 25 of the 49 cases from a previous study. Our approach is easily extended to other organisms, including higher eukaryotes. Our study highlights the utility of enlarging current structural genomics projects that exhaustively sample fold structure space to include all factors with significantly different DNA-binding specificities.
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