Integrated Assessment and Prediction of Transcription Factor Binding
Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is co...
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| Vydané v: | PLoS computational biology Ročník 2; číslo 6; s. e70 |
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| Hlavní autori: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
Public Library of Science
01.06.2006
Public Library of Science (PLoS) |
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| ISSN: | 1553-7358, 1553-734X, 1553-7358 |
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| Abstract | Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined. |
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| AbstractList | Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined.Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined. Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF–target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which “standard conditions” are ill defined. Transcription factors (TFs) bind close to their target genes for regulating transcript levels depending on cellular conditions. Each gene may be regulated differently from others through the binding of specific groups of TFs (TF modules). Recently, a wide variety of large-scale measurements about transcriptional networks has become available. Here the authors present a framework for consistently integrating all of this evidence to systematically determine the precise set of genes directly regulated by each TF (i.e., TF–target interactions). The framework is applied to the yeast Saccharomyces cerevisiae using seven distinct sources of evidences to score all possible TF–target interactions in this organism. Subsequently, the authors employ another newly developed algorithm to reveal TF modules based on the top 5,000 TF–target interactions, yielding more than 300 TF modules. The new scoring scheme for TF–target interactions allows predicting the binding of TFs under so-far untested conditions, which is demonstrated by experimentally verifying interactions for two TFs (Pdr1p, Rpn4p). Importantly, the new methods (scoring of TF–target interactions and TF module identification) are scalable to much larger datasets, making them applicable to future studies in humans, which are thought to have substantially larger numbers of TF–target interactions. Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined. Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms and humans. However, measurement of chromatin binding does not necessarily imply regulation, and binding may be difficult to detect if it is condition or cofactor dependent. To address these challenges, we present an approach for reliably assigning transcription factors (TFs) to target genes that integrates many lines of direct and indirect evidence into a single probabilistic model. Using this approach, we analyze publicly available chIP-chip binding profiles measured for yeast TFs in standard conditions, showing that our model interprets these data with significantly higher accuracy than previous methods. Pooling the high-confidence interactions reveals a large network containing 363 significant sets of factors (TF modules) that cooperate to regulate common target genes. In addition, the method predicts 980 novel binding interactions with high confidence that are likely to occur in so-far untested conditions. Indeed, using new chIP-chip experiments we show that predicted interactions for the factors Rpn4p and Pdr1p are observed only after treatment of cells with methyl-methanesulfonate, a DNA-damaging agent. We outline the first approach for consistently integrating all available evidences for TF-target interactions and we comprehensively identify the resulting TF module hierarchy. Prioritizing experimental conditions for each factor will be especially important as increasing numbers of chIP-chip assays are performed in complex organisms such as humans, for which "standard conditions" are ill defined. |
| Audience | Academic |
| Author | Möller, Ulrich Radke, Dörte Wilhelm, Thomas Hollunder, Jens Workman, Christopher Beyer, Andreas Ideker, Trey |
| AuthorAffiliation | 1 Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America 2 Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany 3 Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany EMBL Heidelberg, Germany |
| AuthorAffiliation_xml | – name: 2 Leibniz Institute for Age Research, Fritz Lipmann Institute, Jena, Germany – name: 1 Department of Bioengineering, University of California San Diego, La Jolla, California, United States of America – name: 3 Leibniz Institute for Natural Product Research and Infection Biology, Hans Knöll Institute, Jena, Germany – name: EMBL Heidelberg, Germany |
| Author_xml | – sequence: 1 givenname: Andreas surname: Beyer fullname: Beyer, Andreas – sequence: 2 givenname: Christopher surname: Workman fullname: Workman, Christopher – sequence: 3 givenname: Jens surname: Hollunder fullname: Hollunder, Jens – sequence: 4 givenname: Dörte surname: Radke fullname: Radke, Dörte – sequence: 5 givenname: Ulrich surname: Möller fullname: Möller, Ulrich – sequence: 6 givenname: Thomas surname: Wilhelm fullname: Wilhelm, Thomas – sequence: 7 givenname: Trey surname: Ideker fullname: Ideker, Trey |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/16789814$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1002/pmic.200401121 10.1038/ng1165 10.1126/science.285.5428.751 10.1016/0005-2795(75)90109-9 10.1073/pnas.0308661100 10.1038/ng724 10.1126/science.1087361 10.1038/nature01763 10.1073/pnas.0402591101 10.1091/mbc.12.10.2987 10.1016/S1568-7864(02)00187-8 10.1073/pnas.0406614101 10.1046/j.1365-2958.2002.02823.x 10.1038/nbt1103 10.1186/gb-2005-6-13-r114 10.1038/ng941 10.1073/pnas.0405537102 10.1186/gb-2004-5-8-r56 10.1142/9789814447331_0044 10.1038/387s067 10.1093/bioinformatics/bth166 10.1126/science.292.5518.929 10.1126/science.282.5389.699 10.1016/S0092-8674(01)00494-9 10.1038/nsmb820 10.1089/10665270050514945 10.1093/nar/gki166 10.1128/MCB.25.6.2138-2146.2005 10.1126/science.1075090 10.1126/science.1099511 10.1038/nature02800 10.1073/pnas.96.8.4285 10.1091/mbc.11.12.4241 10.1093/nar/29.1.281 10.1128/MCB.17.2.545 10.1038/nbt890 10.1073/pnas.0407365101 10.1016/j.febslet.2004.11.019 10.1093/nar/25.1.28 10.1186/gb-2005-6-7-r62 10.1046/j.1365-2958.2002.03262.x 10.1093/bioinformatics/15.7.607 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2006 Public Library of Science 2006 Beyer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Beyer A, Workman C, Hollunder J, Radke D, Möller U, et al. (2006) Integrated Assessment and Prediction of Transcription Factor Binding. PLoS Comput Biol 2(6): e70. doi:10.1371/journal.pcbi.0020070 2006 Beyer et al. 2006 |
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| References | (pcbi-0020070-b036) 1975; 405 (pcbi-0020070-b009) 2001; 106 (pcbi-0020070-b026) 2005; 5 (pcbi-0020070-b002) 2001; 29 (pcbi-0020070-b003) 2005; 33 (pcbi-0020070-b017) 2004; 578 (pcbi-0020070-b025) 2004; 101 (pcbi-0020070-b040) 2003; 19 (pcbi-0020070-b044) 1998; 282 (pcbi-0020070-b005) 2004; 11 (pcbi-0020070-b028) 1999; 285 (pcbi-0020070-b001) 2000; 11 (pcbi-0020070-b035) 2003; 2 (pcbi-0020070-b027) 2004; 101 (pcbi-0020070-b007) 2001; 292 (pcbi-0020070-b013) 2004; 5 (pcbi-0020070-b041) 2005; 6 (pcbi-0020070-b015) 2002; 31 (pcbi-0020070-b042) 2004; 20 (pcbi-0020070-b014) 2004; 101 (pcbi-0020070-b018) 2005; 21 (pcbi-0020070-b020) 2004; 101 (pcbi-0020070-b008) 2003; 424 (pcbi-0020070-b024) 2005; 23 (pcbi-0020070-b031) 1997; 387 (pcbi-0020070-b046) 2002; 3 (pcbi-0020070-b010) 2002; 298 (pcbi-0020070-b038) 1999; 15 (pcbi-0020070-b004) 2003; 21 (pcbi-0020070-b016) 2003; 34 (pcbi-0020070-b033) 2002; 46 (pcbi-0020070-b011) 2004; 431 (pcbi-0020070-b030) 1997; 17 (pcbi-0020070-b032) 1997; 25 (pcbi-0020070-b006) 2005; 102 (pcbi-0020070-b039) 2001; 29 (pcbi-0020070-b045) 2004; 20 pcbi-0020070-b037 (pcbi-0020070-b034) 2002; 43 (pcbi-0020070-b043) 2001; 12 (pcbi-0020070-b022) 2005; 6 (pcbi-0020070-b021) 2004; 306 (pcbi-0020070-b023) 2003; 302 (pcbi-0020070-b019) 2005; 6 (pcbi-0020070-b029) 1999; 96 (pcbi-0020070-b047) 2000; 7 (pcbi-0020070-b012) 2005; 25 |
| References_xml | – volume: 5 start-page: 2082 year: 2005 ident: pcbi-0020070-b026 article-title: Identification and characterization of protein subcomplexes in yeast. publication-title: Proteomics doi: 10.1002/pmic.200401121 – volume: 34 start-page: 166 year: 2003 ident: pcbi-0020070-b016 article-title: Module networks: Identifying regulatory modules and their condition-specific regulators from gene expression data. publication-title: Nat Genet doi: 10.1038/ng1165 – volume: 285 start-page: 751 year: 1999 ident: pcbi-0020070-b028 article-title: Detecting protein function and protein-protein interactions from genome sequences. publication-title: Science doi: 10.1126/science.285.5428.751 – volume: 405 start-page: 442 year: 1975 ident: pcbi-0020070-b036 article-title: Comparison of the predicted and observed secondary structure of T4 phage lysozyme. publication-title: Biochim Biophys Acta doi: 10.1016/0005-2795(75)90109-9 – volume: 19 start-page: i273 issue: (Suppl 1) year: 2003 ident: pcbi-0020070-b040 article-title: Genome-wide discovery of transcriptional modules from DNA sequence and gene expression. publication-title: Bioinformatics – volume: 101 start-page: 2981 year: 2004 ident: pcbi-0020070-b020 article-title: Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0308661100 – volume: 20 start-page: i23 issue: (Suppl 1) year: 2004 ident: pcbi-0020070-b045 article-title: Deconvolving cell cycle expression data with complementary information. publication-title: Bioinformatics – volume: 29 start-page: 153 year: 2001 ident: pcbi-0020070-b002 article-title: Identifying regulatory networks by combinatorial analysis of promotor elements. publication-title: Nat Genet doi: 10.1038/ng724 – volume: 302 start-page: 449 year: 2003 ident: pcbi-0020070-b023 article-title: A Bayesian networks approach for predicting protein-protein interactions from genomic data. publication-title: Science doi: 10.1126/science.1087361 – volume: 424 start-page: 147 year: 2003 ident: pcbi-0020070-b008 article-title: Transcription regulation and animal diversity. publication-title: Nature doi: 10.1038/nature01763 – volume: 101 start-page: 9033 year: 2004 ident: pcbi-0020070-b027 article-title: Coevolution of gene expression among interacting proteins. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0402591101 – volume: 12 start-page: 2987 year: 2001 ident: pcbi-0020070-b043 article-title: Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p. publication-title: Mol Biol Cell doi: 10.1091/mbc.12.10.2987 – volume: 21 start-page: ii197 issue: (Suppl 2) year: 2005 ident: pcbi-0020070-b018 article-title: Genome-wide decoding of hierarchical modular structure of transcriptional regulation by cis-element and expression clustering. publication-title: Bioinformatics – volume: 2 start-page: 73 year: 2003 ident: pcbi-0020070-b035 article-title: DNA mismatch repair and acquired cisplatin resistance in E. coli and human ovarian carcinoma cells. publication-title: DNA Repair (Amst) doi: 10.1016/S1568-7864(02)00187-8 – volume: 101 start-page: 15682 year: 2004 ident: pcbi-0020070-b025 article-title: Combining biological networks to predict genetic interactions. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0406614101 – volume: 43 start-page: 1295 year: 2002 ident: pcbi-0020070-b034 article-title: Control of 26S proteasome expression by transcription factors regulating multidrug resistance in Saccharomyces cerevisiae. publication-title: Mol Microbiol doi: 10.1046/j.1365-2958.2002.02823.x – volume: 23 start-page: 951 year: 2005 ident: pcbi-0020070-b024 article-title: Probabilistic model of the human protein-protein interaction network. publication-title: Nat Biotechnol doi: 10.1038/nbt1103 – volume: 6 start-page: R114 year: 2005 ident: pcbi-0020070-b022 article-title: Discovery of biological networks from diverse functional genomic data. publication-title: Genome Biol doi: 10.1186/gb-2005-6-13-r114 – volume: 31 start-page: 370 year: 2002 ident: pcbi-0020070-b015 article-title: Revealing modular organization in the yeast transcriptional network. publication-title: Nat Genet doi: 10.1038/ng941 – volume: 102 start-page: 1998 year: 2005 ident: pcbi-0020070-b006 article-title: Inference of combinatorial regulation in yeast transcriptional networks: A case study of sporulation. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0405537102 – volume: 5 start-page: R56 year: 2004 ident: pcbi-0020070-b013 article-title: Identifying combinatorial regulation of transcription factors and binding motifs. publication-title: Genome Biol doi: 10.1186/gb-2004-5-8-r56 – ident: pcbi-0020070-b037 doi: 10.1142/9789814447331_0044 – volume: 387 start-page: 67 year: 1997 ident: pcbi-0020070-b031 article-title: Genetic and physical maps of Saccharomyces cerevisiae. publication-title: Nature doi: 10.1038/387s067 – volume: 20 start-page: 1993 year: 2004 ident: pcbi-0020070-b042 article-title: Defining transcription modules using large-scale gene expression data. publication-title: Bioinformatics doi: 10.1093/bioinformatics/bth166 – volume: 292 start-page: 929 year: 2001 ident: pcbi-0020070-b007 article-title: Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. publication-title: Science doi: 10.1126/science.292.5518.929 – volume: 282 start-page: 699 year: 1998 ident: pcbi-0020070-b044 article-title: The transcriptional program of sporulation in budding yeast. publication-title: Science doi: 10.1126/science.282.5389.699 – volume: 106 start-page: 697 year: 2001 ident: pcbi-0020070-b009 article-title: Serial regulation of transcriptional regulators in the yeast cell cycle. publication-title: Cell doi: 10.1016/S0092-8674(01)00494-9 – volume: 11 start-page: 812 year: 2004 ident: pcbi-0020070-b005 article-title: Combinatorial control of gene expression. publication-title: Nat Struct Mol Biol doi: 10.1038/nsmb820 – volume: 7 start-page: 805 year: 2000 ident: pcbi-0020070-b047 article-title: Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data. publication-title: J Comput Biol doi: 10.1089/10665270050514945 – volume: 33 start-page: 605 year: 2005 ident: pcbi-0020070-b003 article-title: Extraction of transcription regulatory signals from genome-wide DNA-protein interaction data. publication-title: Nucleic Acids Res doi: 10.1093/nar/gki166 – volume: 25 start-page: 2138 year: 2005 ident: pcbi-0020070-b012 article-title: Combined global localization analysis and transcriptome data identify genes that are directly coregulated by Adr1 and Cat8. publication-title: Mol Cell Biol doi: 10.1128/MCB.25.6.2138-2146.2005 – volume: 298 start-page: 799 year: 2002 ident: pcbi-0020070-b010 article-title: Transcriptional regulatory networks in Saccharomyces cerevisiae. publication-title: Science doi: 10.1126/science.1075090 – volume: 306 start-page: 1555 year: 2004 ident: pcbi-0020070-b021 article-title: A probabilistic functional network of yeast genes. publication-title: Science doi: 10.1126/science.1099511 – volume: 6 start-page: 557 year: 2005 ident: pcbi-0020070-b041 article-title: Learning module networks. publication-title: J Mach Learn Res – volume: 431 start-page: 99 year: 2004 ident: pcbi-0020070-b011 article-title: Transcriptional regulatory code of a eukaryotic genome. publication-title: Nature doi: 10.1038/nature02800 – volume: 96 start-page: 4285 year: 1999 ident: pcbi-0020070-b029 article-title: Assigning protein functions by comparative genome analysis: Protein phylogenetic profiles. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.96.8.4285 – volume: 11 start-page: 4241 year: 2000 ident: pcbi-0020070-b001 article-title: Genomic expression programs in the response of yeast cells to environmental changes. publication-title: Mol Biol Cell doi: 10.1091/mbc.11.12.4241 – volume: 29 start-page: 281 year: 2001 ident: pcbi-0020070-b039 article-title: The TRANSFAC system on gene expression regulation. publication-title: Nucleic Acids Res doi: 10.1093/nar/29.1.281 – volume: 17 start-page: 545 year: 1997 ident: pcbi-0020070-b030 article-title: Hir1p and Hir2p function as transcriptional corepressors to regulate histone gene transcription in the Saccharomyces cerevisiae cell cycle. publication-title: Mol Cell Biol doi: 10.1128/MCB.17.2.545 – volume: 21 start-page: 1337 year: 2003 ident: pcbi-0020070-b004 article-title: Computational discovery of gene modules and regulatory networks. publication-title: Nat Biotechnol doi: 10.1038/nbt890 – volume: 3 start-page: 0059 year: 2002 ident: pcbi-0020070-b046 article-title: Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering. publication-title: Genome Biol – volume: 101 start-page: 16234 year: 2004 ident: pcbi-0020070-b014 article-title: Interacting models of cooperative gene regulation. publication-title: Proc Natl Acad Sci U S A doi: 10.1073/pnas.0407365101 – volume: 578 start-page: 297 year: 2004 ident: pcbi-0020070-b017 article-title: Learning module networks from genome-wide location and expression data. publication-title: FEBS Lett doi: 10.1016/j.febslet.2004.11.019 – volume: 25 start-page: 28 year: 1997 ident: pcbi-0020070-b032 article-title: MIPS: A database for protein sequences, homology data and yeast genome information. publication-title: Nucleic Acids Res doi: 10.1093/nar/25.1.28 – volume: 6 start-page: R62 year: 2005 ident: pcbi-0020070-b019 article-title: Validation and refinement of gene-regulatory pathways on a network of physical interactions. publication-title: Genome Biol doi: 10.1186/gb-2005-6-7-r62 – volume: 46 start-page: 1429 year: 2002 ident: pcbi-0020070-b033 article-title: The yeast zinc finger regulators Pdr1p and Pdr3p control pleiotropic drug resistance (PDR) as homo- and heterodimers in vivo. publication-title: Mol Microbiol doi: 10.1046/j.1365-2958.2002.03262.x – volume: 15 start-page: 607 year: 1999 ident: pcbi-0020070-b038 article-title: SCPD: A promoter database of the yeast Saccharomyces cerevisiae. publication-title: Bioinformatics doi: 10.1093/bioinformatics/15.7.607 |
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| Snippet | Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms... Systematic chromatin immunoprecipitation (chIP-chip) experiments have become a central technique for mapping transcriptional interactions in model organisms... |
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| SubjectTerms | Algorithms Base Sequence Binding Sites Bioinformatics - Computational Biology Cell Biology Chromatin Immunoprecipitation - methods Computer Simulation DNA microarrays Experiments Gene expression Genetic transcription Genetics Genomes Methods Models, Chemical Models, Genetic Molecular Sequence Data Observations Protein Binding Saccharomyces Sequence Alignment - methods Sequence Analysis, DNA - methods Systems Biology Systems Integration Transcription Factors - chemistry Transcription Factors - genetics Transcription, Genetic - genetics Yeasts |
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| Title | Integrated Assessment and Prediction of Transcription Factor Binding |
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