Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers
暂无分享,去创建一个
Michael J. Purcaro | Z. Weng | A. Kundaje | M. Purcaro | Ruixin Zhu | Cizhong Jiang | Jill E. Moore | Henry E. Pratt | K. Fan | Aiping Lu | Shaliu Fu | Cuihua Gu | Qin Wang | H. Pratt
[1] Niko Beerenwinkel,et al. Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb , 2017, PLoS Comput. Biol..
[2] D. Dickel,et al. Improved regulatory element prediction based on tissue-specific local epigenomic signatures , 2017, Proceedings of the National Academy of Sciences.
[3] Tao Liu,et al. Cistrome Data Browser: a data portal for ChIP-Seq and chromatin accessibility data in human and mouse , 2016, Nucleic Acids Res..
[4] Katherine S. Pollard,et al. Features that define the best ChIP-seq peak calling algorithms , 2016, Briefings Bioinform..
[5] Ryuichiro Nakato,et al. Recent advances in ChIP-seq analysis: from quality management to whole-genome annotation , 2016, Briefings Bioinform..
[6] Matthew T. Maurano,et al. Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells , 2016, Cell.
[7] D. Geschwind,et al. Histone Acetylome-wide Association Study of Autism Spectrum Disorder , 2016, Cell.
[8] Tyler H. Garvin,et al. Genome-wide compendium and functional assessment of in vivo heart enhancers , 2016, Nature Communications.
[9] Julia Zeitlinger,et al. Genome-wide identification of Drosophila dorso-ventral enhancers by differential histone acetylation analysis , 2016, Genome Biology.
[10] Feng Liu,et al. PEDLA: predicting enhancers with a deep learning-based algorithmic framework , 2016, Scientific Reports.
[11] Yu Zhang,et al. Jointly characterizing epigenetic dynamics across multiple human cell types , 2016, Nucleic acids research.
[12] H. Ng,et al. Comprehensive benchmarking reveals H2BK20 acetylation as a distinctive signature of cell-state-specific enhancers and promoters , 2016, Genome research.
[13] John G Flannery,et al. Massively parallel cis-regulatory analysis in the mammalian central nervous system , 2016, Genome research.
[14] B. L,et al. The accessible chromatin landscape of the human genome , 2016 .
[15] Yiming Lu,et al. DELTA: A Distal Enhancer Locating Tool Based on AdaBoost Algorithm and Shape Features of Chromatin Modifications , 2015, PloS one.
[16] C. Glass,et al. The selection and function of cell type-specific enhancers , 2015, Nature Reviews Molecular Cell Biology.
[17] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[18] Mark Gerstein,et al. MUSIC: identification of enriched regions in ChIP-Seq experiments using a mappability-corrected multiscale signal processing framework , 2014, Genome Biology.
[19] A. Quinlan. BEDTools: The Swiss‐Army Tool for Genome Feature Analysis , 2014, Current protocols in bioinformatics.
[20] E. Segal,et al. In pursuit of design principles of regulatory sequences , 2014, Nature Reviews Genetics.
[21] Thomas A. Down,et al. A Comparison of Peak Callers Used for DNase-Seq Data , 2014, bioRxiv.
[22] V. Corces,et al. CTCF: an architectural protein bridging genome topology and function , 2014, Nature Reviews Genetics.
[23] Katherine S. Pollard,et al. Integrating Diverse Datasets Improves Developmental Enhancer Prediction , 2013, PLoS Comput. Biol..
[24] Weiqun Peng,et al. Spatial clustering for identification of ChIP-enriched regions (SICER) to map regions of histone methylation patterns in embryonic stem cells. , 2014, Methods in molecular biology.
[25] Anaïs F. Bardet,et al. Identification of transcription factor binding sites from ChIP-seq data at high resolution , 2013, Bioinform..
[26] Howard Y. Chang,et al. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.
[27] Wei Wang,et al. Predicting enhancer transcription and activity from chromatin modifications , 2013, Nucleic acids research.
[28] H. Ng,et al. Uniform, optimal signal processing of mapped deep-sequencing data , 2013, Nature Biotechnology.
[29] J. Wysocka,et al. Modification of enhancer chromatin: what, how, and why? , 2013, Molecular cell.
[30] Wei Xie,et al. RFECS: A Random-Forest Based Algorithm for Enhancer Identification from Chromatin State , 2013, PLoS Comput. Biol..
[31] D. Menke,et al. Pitx1 broadly associates with limb enhancers and is enriched on hindlimb cis-regulatory elements. , 2013, Developmental biology.
[32] William Stafford Noble,et al. Integrative annotation of chromatin elements from ENCODE data , 2012, Nucleic acids research.
[33] Michael Q. Zhang,et al. A novel Bayesian change-point algorithm for genome-wide analysis of diverse ChIPseq data types. , 2012, Journal of visualized experiments : JoVE.
[34] Shane J. Neph,et al. Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.
[35] Raymond K. Auerbach,et al. An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.
[36] H. Kimura,et al. H3K9 and H3K14 acetylation co-occur at many gene regulatory elements, while H3K14ac marks a subset of inactive inducible promoters in mouse embryonic stem cells , 2012, BMC Genomics.
[37] ENCODEConsortium,et al. An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.
[38] Y. Kluger,et al. Picking ChIP-seq peak detectors for analyzing chromatin modification experiments , 2012, Nucleic acids research.
[39] Manolis Kellis,et al. ChromHMM: automating chromatin-state discovery and characterization , 2012, Nature Methods.
[40] Vijay K. Tiwari,et al. DNA-binding factors shape the mouse methylome at distal regulatory regions , 2011, Nature.
[41] R. Sandberg,et al. Sequentially acting Sox transcription factors in neural lineage development. , 2011, Genes & development.
[42] Christoph D. Schmid,et al. Rapid innovation in ChIP-seq peak-calling algorithms is outdistancing benchmarking efforts , 2011, Briefings Bioinform..
[43] S. Spicuglia,et al. H3K4 tri‐methylation provides an epigenetic signature of active enhancers , 2011, The EMBO journal.
[44] Sündüz Keleş,et al. A Statistical Framework for the Analysis of ChIP-Seq Data , 2011, Journal of the American Statistical Association.
[45] Andrew D. Smith,et al. Bioinformatics Applications Note Gene Expression Identifying Dispersed Epigenomic Domains from Chip-seq Data , 2022 .
[46] Timothy J. Durham,et al. Systematic analysis of chromatin state dynamics in nine human cell types , 2011, Nature.
[47] J. Stamatoyannopoulos,et al. Chromatin accessibility pre-determines glucocorticoid receptor binding patterns , 2011, Nature Genetics.
[48] R. Young,et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state , 2010, Proceedings of the National Academy of Sciences.
[49] Salvatore Spicuglia,et al. A unique H3K4me2 profile marks tissue-specific gene regulation. , 2010, Genome research.
[50] M. Facciotti,et al. Evaluation of Algorithm Performance in ChIP-Seq Peak Detection , 2010, PloS one.
[51] Kai Tan,et al. Discover regulatory DNA elements using chromatin signatures and artificial neural network , 2010, Bioinform..
[52] C. Glass,et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. , 2010, Molecular cell.
[53] Feng Lin,et al. A signal-noise model for significance analysis of ChIP-seq with negative control , 2010, Bioinform..
[54] M. Groudine,et al. Enhancers: the abundance and function of regulatory sequences beyond promoters. , 2010, Developmental biology.
[55] T. Laajala,et al. A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments , 2009, BMC Genomics.
[56] A. Visel,et al. Genomic Views of Distant-Acting Enhancers , 2009, Nature.
[57] Nathaniel D. Heintzman,et al. Histone modifications at human enhancers reflect global cell-type-specific gene expression , 2009, Nature.
[58] A. Visel,et al. ChIP-seq accurately predicts tissue-specific activity of enhancers , 2009, Nature.
[59] P. Park,et al. Design and analysis of ChIP-seq experiments for DNA-binding proteins , 2008, Nature Biotechnology.
[60] Clifford A. Meyer,et al. Model-based Analysis of ChIP-Seq (MACS) , 2008, Genome Biology.
[61] Terrence S. Furey,et al. F-Seq: a feature density estimator for high-throughput sequence tags , 2008, Bioinform..
[62] Michael Q. Zhang,et al. Combinatorial patterns of histone acetylations and methylations in the human genome , 2008, Nature Genetics.
[63] Z. Weng,et al. The Insulator Binding Protein CTCF Positions 20 Nucleosomes around Its Binding Sites across the Human Genome , 2008, PLoS genetics.
[64] Jane M J Lin,et al. Identification and Characterization of Cell Type–Specific and Ubiquitous Chromatin Regulatory Structures in the Human Genome , 2007, PLoS genetics.
[65] Nathaniel D. Heintzman,et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome , 2007, Nature Genetics.
[66] Inna Dubchak,et al. VISTA Enhancer Browser—a database of tissue-specific human enhancers , 2006, Nucleic Acids Res..
[67] Alan M. Moses,et al. In vivo enhancer analysis of human conserved non-coding sequences , 2006, Nature.
[68] W. Williams. Hog-Wallows and Prairie Mounds , 1877, Nature.