Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding
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Polly M. Fordyce | Yaron Orenstein | Tyler C. Shimko | P. Fordyce | Yaron Orenstein | D. Le | Arjun K. Aditham | Allison Keys | Daniel D. Le | Allison M. Keys
[1] R. Roeder,et al. Chemically ubiquitylated histone H2B stimulates hDot1L-mediated intranucleosomal methylation , 2008, Nature.
[2] Joshua L. Payne,et al. A thousand empirical adaptive landscapes and their navigability , 2017, Nature Ecology &Evolution.
[3] Gary D. Stormo,et al. ScerTF: a comprehensive database of benchmarked position weight matrices for Saccharomyces species , 2011, Nucleic Acids Res..
[4] R. Mann,et al. Cofactor Binding Evokes Latent Differences in DNA Binding Specificity between Hox Proteins , 2011, Cell.
[5] C. Goding,et al. Single amino acid substitutions alter helix‐loop‐helix protein specificity for bases flanking the core CANNTG motif. , 1992, The EMBO journal.
[6] E. O’Shea,et al. A quantitative model of transcription factor–activated gene expression , 2008, Nature Structural &Molecular Biology.
[7] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[8] Barbara E. Engelhardt,et al. Stability selection for regression-based models of transcription factor–DNA binding specificity , 2013, Bioinform..
[9] Aviv Regev,et al. Transcriptional Regulatory Circuits: Predicting Numbers from Alphabets , 2009, Science.
[10] T. D. Schneider,et al. Quantitative analysis of the relationship between nucleotide sequence and functional activity. , 1986, Nucleic acids research.
[11] Ting Wang,et al. An improved map of conserved regulatory sites for Saccharomyces cerevisiae , 2006, BMC Bioinformatics.
[12] Ville Mustonen,et al. Energy-dependent fitness: A quantitative model for the evolution of yeast transcription factor binding sites , 2008, Proceedings of the National Academy of Sciences.
[13] Yue Zhao,et al. Inferring Binding Energies from Selected Binding Sites , 2009, PLoS Comput. Biol..
[14] Terence P. Speed,et al. Finding short DNA motifs using permuted markov models , 2004, RECOMB.
[15] Alexandre V. Morozov,et al. Biophysical Fitness Landscapes for Transcription Factor Binding Sites , 2013, PLoS Comput. Biol..
[16] Eran Segal,et al. Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation , 2009, RECOMB.
[17] I. Korf,et al. Bind-n-Seq: high-throughput analysis of in vitro protein–DNA interactions using massively parallel sequencing , 2009, Nucleic acids research.
[18] J. Szostak,et al. In vitro selection of RNA molecules that bind specific ligands , 1990, Nature.
[19] Gary D. Stormo,et al. Identifying DNA and protein patterns with statistically significant alignments of multiple sequences , 1999, Bioinform..
[20] R. Mann,et al. Building accurate sequence-to-affinity models from high-throughput in vitro protein-DNA binding data using FeatureREDUCE , 2015, eLife.
[21] G. Stormo,et al. Quantitative analysis demonstrates most transcription factors require only simple models of specificity , 2011, Nature Biotechnology.
[22] S. Linnarsson,et al. Counting absolute numbers of molecules using unique molecular identifiers , 2011, Nature Methods.
[23] S. Quake,et al. De Novo Identification and Biophysical Characterization of Transcription Factor Binding Sites with Microfluidic Affinity Analysis , 2010, Nature Biotechnology.
[24] Juan M. Vaquerizas,et al. Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities. , 2010, Genome research.
[25] Lin Yang,et al. DNAshape: a method for the high-throughput prediction of DNA structural features on a genomic scale , 2013, Nucleic Acids Res..
[26] E. Siggia,et al. Analysis of Combinatorial cis-Regulation in Synthetic and Genomic Promoters , 2008, Nature.
[27] R. Shamir,et al. Transcription factor family‐specific DNA shape readout revealed by quantitative specificity models , 2017, Molecular systems biology.
[28] T. Eulgem. Eukaryotic transcription factors , 2001, Genome Biology.
[29] E. O’Shea,et al. Chromatin decouples promoter threshold from dynamic range , 2008, Nature.
[30] Y. Kyōgoku,et al. Crystal structure of PHO4 bHLH domain–DNA complex: flanking base recognition , 1997, The EMBO journal.
[31] Terence Hwa,et al. Transcriptional regulation by the numbers: models. , 2005, Current opinion in genetics & development.
[32] Alexandre V. Morozov,et al. Statistical mechanical modeling of genome-wide transcription factor occupancy data by MatrixREDUCE , 2006, ISMB.
[33] S. P. Fodor,et al. Molecular indexing enables quantitative targeted RNA sequencing and reveals poor efficiencies in standard library preparations , 2014, Proceedings of the National Academy of Sciences.
[34] G. Stormo,et al. Improved Models for Transcription Factor Binding Site Identification Using Nonindependent Interactions , 2012, Genetics.
[35] Raluca Gordân,et al. Nonconsensus Protein Binding to Repetitive DNA Sequence Elements Significantly Affects Eukaryotic Genomes , 2015, PLoS Comput. Biol..
[36] Justin Crocker,et al. The Soft Touch: Low-Affinity Transcription Factor Binding Sites in Development and Evolution. , 2016, Current topics in developmental biology.
[37] E. O’Shea,et al. Integrated approaches reveal determinants of genome-wide binding and function of the transcription factor Pho4. , 2011, Molecular cell.
[38] D. S. Fields,et al. Specificity, free energy and information content in protein-DNA interactions. , 1998, Trends in biochemical sciences.
[39] Xiaohui S. Xie,et al. DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences , 2015, bioRxiv.
[40] Lin Yang,et al. TFBSshape: a motif database for DNA shape features of transcription factor binding sites , 2013, Nucleic Acids Res..
[41] R. Shamir,et al. SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics , 2016, Scientific Reports.
[42] A. Philippakis,et al. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities , 2006, Nature Biotechnology.
[43] Omar Wagih,et al. ggseqlogo: a versatile R package for drawing sequence logos , 2017, Bioinform..
[44] M. Levine,et al. Syntax compensates for poor binding sites to encode tissue specificity of developmental enhancers , 2016, Proceedings of the National Academy of Sciences.
[45] Juan M. Vaquerizas,et al. DNA-Binding Specificities of Human Transcription Factors , 2013, Cell.
[46] Dieter Söll,et al. A chemical biology route to site-specific authentic protein modifications , 2016, Science.
[47] Polly M Fordyce,et al. Basic leucine zipper transcription factor Hac1 binds DNA in two distinct modes as revealed by microfluidic analyses , 2012, Proceedings of the National Academy of Sciences.
[48] Daniel E. Newburger,et al. Diversity and Complexity in DNA Recognition by Transcription Factors , 2009, Science.
[49] Edward J. Oakeley,et al. Position dependencies in transcription factor binding sites , 2007, Bioinform..
[50] V. Zhurkin,et al. DNA sequence-dependent deformability deduced from protein-DNA crystal complexes. , 1998, Proceedings of the National Academy of Sciences of the United States of America.
[51] L. Hellman,et al. Electrophoretic mobility shift assay (EMSA) for detecting protein–nucleic acid interactions , 2007, Nature Protocols.
[52] J. Hegemann,et al. CPF1, a yeast protein which functions in centromeres and promoters. , 1990, The EMBO journal.
[53] R. Mann,et al. The role of DNA shape in protein-DNA recognition , 2009, Nature.
[54] Zheng Zuo,et al. High-Resolution Specificity from DNA Sequencing Highlights Alternative Modes of Lac Repressor Binding , 2014, Genetics.
[55] Eran Segal,et al. A Feature-Based Approach to Modeling Protein–DNA Interactions , 2007, RECOMB.
[56] Lin Yang,et al. DNAshapeR: an R/Bioconductor package for DNA shape prediction and feature encoding , 2015, Bioinform..
[57] R. Mann,et al. Deconvolving the Recognition of DNA Shape from Sequence , 2015, Cell.
[58] Z. Yakhini,et al. Unraveling determinants of transcription factor binding outside the core binding site , 2015, Genome research.
[59] S. Luo,et al. Direct measurement of DNA affinity landscapes on a high-throughput sequencing instrument , 2011, Nature Biotechnology.
[60] E. Siggia,et al. Connecting protein structure with predictions of regulatory sites , 2007, Proceedings of the National Academy of Sciences.
[61] S. Quake,et al. A Systems Approach to Measuring the Binding Energy Landscapes of Transcription Factors , 2007, Science.
[62] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[63] G. Tkačik,et al. Dynamics of Transcription Factor Binding Site Evolution , 2015, PLoS genetics.
[64] Wyeth W. Wasserman,et al. The Next Generation of Transcription Factor Binding Site Prediction , 2013, PLoS Comput. Biol..
[65] Mathew G. Lewsey,et al. Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape , 2016, Cell.
[66] Anirvan M. Sengupta,et al. A biophysical approach to transcription factor binding site discovery. , 2003, Genome research.
[67] N. D. Clarke,et al. Differential binding of the related transcription factors Pho4 and Cbf1 can tune the sensitivity of promoters to different levels of an induction signal , 2013, Nucleic acids research.
[68] T. D. Schneider,et al. Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli. , 1982, Nucleic acids research.
[69] L. Gold,et al. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. , 1990, Science.
[70] Raluca Gordân,et al. Protein−DNA binding in the absence of specific base-pair recognition , 2014, Proceedings of the National Academy of Sciences.
[71] S. P. Fodor,et al. Counting individual DNA molecules by the stochastic attachment of diverse labels , 2011, Proceedings of the National Academy of Sciences.
[72] H. Lähdesmäki,et al. A Linear Model for Transcription Factor Binding Affinity Prediction in Protein Binding Microarrays , 2011, PloS one.
[73] R. Young,et al. Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays , 2004, Nature Genetics.
[74] M. Bulyk,et al. Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape. , 2013, Cell reports.
[75] A. Burlingame,et al. The Site-Specific Installation of Methyl-Lysine Analogs into Recombinant Histones , 2007, Cell.
[76] R. Siddharthan. Dinucleotide Weight Matrices for Predicting Transcription Factor Binding Sites: Generalizing the Position Weight Matrix , 2010, PloS one.
[77] G. Church,et al. Nucleotides of transcription factor binding sites exert interdependent effects on the binding affinities of transcription factors. , 2002, Nucleic acids research.
[78] G. Stormo,et al. Identifying protein-binding sites from unaligned DNA fragments. , 1989, Proceedings of the National Academy of Sciences of the United States of America.
[79] E. Segal,et al. Predicting expression patterns from regulatory sequence in Drosophila segmentation , 2008, Nature.
[80] Atina G. Coté,et al. Evaluation of methods for modeling transcription factor sequence specificity , 2013, Nature Biotechnology.
[81] Sebastian J Maerkl,et al. Mapping the fine structure of a eukaryotic promoter input-output function , 2013, Nature Genetics.
[82] Joseph R. Ecker,et al. Erratum: Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape (Cell (2016) 165(5) (1280–1292)) , 2016 .
[83] Susan Jones,et al. An overview of the basic helix-loop-helix proteins , 2004, Genome Biology.
[84] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[85] Philipp Bucher,et al. SMiLE-seq identifies binding motifs of single and dimeric transcription factors , 2017, Nature Methods.