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Ming-Jung Liu, Alexander Seddon, Z. Tsai, I. Major, M. Floer, G. Howe, Shin-Han Shiu (2015)
Determinants of nucleosome positioning and their influence on plant gene expressionGenome Research, 25
Pauline Vasseur, Saphia Tonazzini, Rahima Ziane, A. Camasses, O. Rando, M. Radman-Livaja (2016)
Dynamics of Nucleosome Positioning Maturation following Genomic ReplicationCell Reports, 16
Christian Szegedy, Wei Liu, Yangqing Jia, P. Sermanet, Scott Reed, Dragomir Anguelov, D. Erhan, Vincent Vanhoucke, Andrew Rabinovich (2014)
Going deeper with convolutions2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
(2016)
2016) Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks
Jeffrey Hayes, T. Tullius, A. Wolffe (1990)
The structure of DNA in a nucleosome.Proceedings of the National Academy of Sciences of the United States of America, 87
L. Xi, Yvonne Fondufe-Mittendorf, Lei Xia, Jared Flatow, J. Widom, Ji-Ping Wang (2010)
Predicting nucleosome positioning using a duration Hidden Markov ModelBMC Bioinformatics, 11
O. Bell, V. Tiwari, N. Thomä, D. Schübeler (2011)
Determinants and dynamics of genome accessibilityNature Reviews Genetics, 12
Kristin Brogaard, L. Xi, Ji-ping Wang, J. Widom (2012)
A map of nucleosome positions in yeast at base-pair resolutionNature, 486
Wei Chen, Pengmian Feng, H. Ding, Hao Lin, K. Chou (2016)
Using deformation energy to analyze nucleosome positioning in genomes.Genomics, 107 2-3
K. Luger, A. Mäder, R. Richmond, D. Sargent, T. Richmond (1997)
Crystal structure of the nucleosome core particle at 2.8 Å resolutionNature, 389
A. Morozov, Karissa Fortney, Daria Gaykalova, V. Studitsky, J. Widom, E. Siggia (2009)
Using DNA mechanics to predict in vitro nucleosome positions and formation energiesNucleic Acids Research, 37
William Lee, Desiree Tillo, N. Bray, R. Morse, Ronald Davis, T. Hughes, C. Nislow (2007)
A high-resolution atlas of nucleosome occupancy in yeastNature Genetics, 39
I. Ioshikhes, Sergey Hosid, Pugh Bf (2011)
Variety of genomic DNA patterns for nucleosome positioning.Genome research, 21 11
R. Kornberg, Y. Lorch (1999)
Twenty-Five Years of the Nucleosome, Fundamental Particle of the Eukaryote ChromosomeCell, 98
Yoshua Bengio, Aaron Courville, Pascal Vincent (2012)
Representation Learning: A Review and New PerspectivesIEEE Transactions on Pattern Analysis and Machine Intelligence, 35
(2011)
Determinants and dynamics of genome
T. Richmond, C. Davey (2003)
The structure of DNA in the nucleosome coreNature, 423
Muhammad Tahir, Maqsood Hayat (2016)
iNuc-STNC: a sequence-based predictor for identification of nucleosome positioning in genomes by extending the concept of SAAC and Chou's PseAAC.Molecular bioSystems, 12 8
A. Barski, Suresh Cuddapah, Kairong Cui, Tae-Young Roh, Dustin Schones, Zhibin Wang, Gang Wei, I. Chepelev, K. Zhao (2007)
High-Resolution Profiling of Histone Methylations in the Human GenomeCell, 129
Yvonne Fondufe-Mittendorf, Lingyi Chen, Y. Field, Irene Moore (2006)
A genomic code for nucleosome
B. Bernstein, C. Liu, Emily Humphrey, E. Perlstein, S. Schreiber (2004)
Global nucleosome occupancy in yeastGenome Biology, 5
A. Esteva, Brett Kuprel, R. Novoa, J. Ko, S. Swetter, H. Blau, S. Thrun (2017)
Dermatologist-level classification of skin cancer with deep neural networksNature, 542
K. Chou (2001)
Prediction of protein cellular attributes using pseudo‐amino acid compositionProteins: Structure, 43
S. Guo, En-Ze Deng, Li-Qin Xu, H. Ding, Hao Lin, Wei Chen, K. Chou (2014)
iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide compositionBioinformatics, 30 11
(2007)
Chromatin remodelling at promoters suppresses
S. Satchwell, H. Drew, A. Travers (1986)
Sequence periodicities in chicken nucleosome core DNA.Journal of molecular biology, 191 4
Yann LeCun, Yoshua Bengio, Geoffrey Hinton (2015)
Deep LearningNature, 521
(2009)
This PDF file includes: Materials and Methods
E. Segal, Yvonne Fondufe-Mittendorf, Lingyi Chen, A. Thåström, Y. Field, Irene Moore, Ji-ping Wang, J. Widom (2006)
A genomic code for nucleosome positioningNature, 442
M. Leung, H. Xiong, Leo Lee, B. Frey (2014)
Deep learning of the tissue-regulated splicing codeBioinformatics, 30
Guocheng Yuan, Yuen-Jong Liu, Michael Dion, M. Slack, Lani Wu, S. Altschuler, O. Rando (2005)
Genome-Scale Identification of Nucleosome Positions in S. cerevisiaeScience, 309
(2008)
Nucleosome organization in the Drosophila
Hinton (2006)
Reducing the dimensionality of data with neural networksScience, 313
Y. Field, Noam Kaplan, Yvonne Fondufe-Mittendorf, Irene Moore, Eilon Sharon, Yaniv Lubling, J. Widom, E. Segal (2008)
Distinct Modes of Regulation by Chromatin Encoded through Nucleosome Positioning SignalsPLoS Computational Biology, 4
A. Weiner, A. Hughes, M. Yassour, O. Rando, N. Friedman (2010)
High-resolution nucleosome mapping reveals transcription-dependent promoter packaging.Genome research, 20 1
M. Eaton, K. Galani, Sukhyun Kang, S. Bell, D. MacAlpine (2010)
Conserved nucleosome positioning defines replication origins.Genes & development, 24 8
(2009)
High-resolution nucleosome mapping reveals
Anton Valouev, Steven Johnson, S. Boyd, Cheryl Smith, A. Fire, A. Sidow (2011)
Determinants of nucleosome organization in primary human cellsNature, 474
Anton Valouev, J. Ichikawa, T. TonThat, Jeremy Stuart, S. Ranade, H. Peckham, K. Zeng, J. Malek, G. Costa, K. McKernan, A. Sidow, A. Fire, Steven Johnson (2008)
A high-resolution, nucleosome position map of C. elegans reveals a lack of universal sequence-dictated positioning.Genome research, 18 7
(2017)
Dermatologist classification of skin cancer with deep neural networks
A. Awazu (2016)
Prediction of nucleosome positioning by the incorporation of frequencies and distributions of three different nucleotide segment lengths into a general pseudo k-tuple nucleotide compositionBioinformatics, 33
Yong Zhang, Z. Moqtaderi, Barbara Rattner, G. Euskirchen, M. Snyder, J. Kadonaga, X. Liu, K. Struhl (2009)
Intrinsic histone-DNA interactions are not the major determinant of nucleosome positions in vivoNature structural & molecular biology, 16
Wei Chen, Hao Lin, Pengmian Feng, Chen Ding, Yongchun Zuo, K. Chou (2012)
iNuc-PhysChem: A Sequence-Based Predictor for Identifying Nucleosomes via Physicochemical PropertiesPLoS ONE, 7
Yann Dauphin, Angela Fan, Michael Auli, David Grangier (2016)
Language Modeling with Gated Convolutional Networks
Sara González, Alicia García, Enrique Vázquez, Rebeca Serrano, Mar Sánchez, L. Quintales, F. Antequera (2016)
Nucleosomal signatures impose nucleosome positioning in coding and noncoding sequences in the genomeGenome Research, 26
F. Smagulova, Ivan Gregoretti, Kevin Brick, P. Khil, R. Camerini‐Otero, G. Petukhova (2011)
Genome-wide analysis reveals novel molecular features of mouse recombination hotspotsNature, 472
Bin Liu, Ren Long, K. Chou (2016)
iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble learning frameworkBioinformatics, 32 16
Dustin Schones, Kairong Cui, Suresh Cuddapah, Tae-Young Roh, A. Barski, Zhibin Wang, Gang Wei, K. Zhao (2008)
Dynamic Regulation of Nucleosome Positioning in the Human GenomeCell, 132
Geoffrey Hinton, L. Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, N. Jaitly, A. Senior, Vincent Vanhoucke, Patrick Nguyen, Tara Sainath, Brian Kingsbury (2017)
Top Downloads in IEEE Xplore [Reader's Choice]IEEE Signal Processing Magazine, 34
(2016)
2016) A Language modeling with gated convolutional networks. arXiv: 1612.08083v1
Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alexander Alemi (2016)
Inception-v4, Inception-ResNet and the Impact of Residual Connections on LearningArXiv, abs/1602.07261
Hagen Tilgner, Christoforos Nikolaou, S. Althammer, M. Sammeth, M. Beato, J. Valcárcel, R. Guigó (2009)
Nucleosome positioning as a determinant of exon recognitionNature Structural &Molecular Biology, 16
H. Widlund, P. Kuduvalli, M. Bengtsson, H. Cao, T. Tullius, M. Kubista (1999)
Nucleosome Structural Features and Intrinsic Properties of the TATAAACGCC Repeat Sequence*The Journal of Biological Chemistry, 274
Cizhong Jiang, B. Pugh (2009)
Nucleosome positioning and gene regulation: advances through genomicsNature Reviews Genetics, 10
(2011)
Genome-wide analysis reveals novel molecular
David Silver, Aja Huang, Chris Maddison, A. Guez, L. Sifre, George Driessche, Julian Schrittwieser, Ioannis Antonoglou, Vedavyas Panneershelvam, Marc Lanctot, S. Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, D. Hassabis (2016)
Mastering the game of Go with deep neural networks and tree searchNature, 529
Elizabeth Rach, D. Winter, A. Benjamin, D. Corcoran, T. Ni, Jun Zhu, U. Ohler (2011)
Transcription Initiation Patterns Indicate Divergent Strategies for Gene Regulation at the Chromatin LevelPLoS Genetics, 7
Xiaowen Liu, B. Shan, L. Xin, B. Ma (2010)
Better score function for peptide identification with ETD MS/MS spectraBMC Bioinformatics, 11
Michael Guertin, J. Lis (2013)
Mechanisms by which transcription factors gain access to target sequence elements in chromatin.Current opinion in genetics & development, 23 2
H. Xiong, B. Alipanahi, Leo Lee, Hannes Bretschneider, D. Merico, R. Yuen, Y. Hua, Serge Gueroussov, H. Najafabadi, T. Hughes, Q. Morris, Yoseph Barash, A. Krainer, N. Jojic, S. Scherer, B. Blencowe, B. Frey (2015)
The human splicing code reveals new insights into the genetic determinants of diseaseScience, 347
I. Ioshikhes, A. Bolshoy, K. Derenshteyn, M. Borodovsky, E. Trifonov (1996)
Nucleosome DNA sequence pattern revealed by multiple alignment of experimentally mapped sequences.Journal of molecular biology, 262 2
(1999)
Twenty-five years of the nucleosome, fundamental particle of the eukaryote
Noam Kaplan, Irene Moore, Yvonne Fondufe-Mittendorf, A. Gossett, Desiree Tillo, Y. Field, E. Leproust, T. Hughes, J. Lieb, J. Widom, E. Segal (2009)
The DNA-encoded nucleosome organization of a eukaryotic genomeNature, 458
(2016)
2016) iDHS-EL: identifying DNase I hypersensitive sites by fusing three different modes of pseudo nucleotide composition into an ensemble
Jian-Ying Wang, Jingyan Wang, Guoqing Liu (2012)
Calculation of nucleosomal DNA deformation energy: its implication for nucleosome positioningChromosome Research, 20
T. Heijden, J. Vugt, C. Logie, J. Noort (2012)
Sequence-based prediction of single nucleosome positioning and genome-wide nucleosome occupancyProceedings of the National Academy of Sciences, 109
K. Chou (2005)
Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classesBioinformatics, 21 1
Geoffrey Hinton, L. Deng, Dong Yu, George Dahl, Abdel-rahman Mohamed, N. Jaitly, A. Senior, Vincent Vanhoucke, Patrick Nguyen, Tara Sainath, Brian Kingsbury (2012)
Deep Neural Networks for Acoustic Modeling in Speech RecognitionIEEE Signal Processing Magazine, 29
I. Whitehouse, O. Rando, J. Delrow, T. Tsukiyama (2007)
Chromatin remodelling at promoters suppresses antisense transcriptionNature, 450
Krizhevsky (2012)
ImageNet classification with deep convolutional neural networksIn Proc. Adv. Neural Information Process. Syst, 25
Cheol-Koo Lee, Yoichiro Shibata, Bhargavi Rao, B. Strahl, J. Lieb (2004)
Evidence for nucleosome depletion at active regulatory regions genome-wideNature Genetics, 36
(2016)
2016) iNuc-STNC: a sequence-based predictor
(2009)
What controls nucleosome positions? Trends
Shaofeng Liu, Zhiyun Xu, He Leng, Pu Zheng, Jiayi Yang, Kaifu Chen, Jianxun Feng, Qing Li (2017)
RPA binds histone H3-H4 and functions in DNA replication–coupled nucleosome assemblyScience, 355
Jianling Zhong, Kaixuan Luo, Peter Winter, G. Crawford, E. Iversen, A. Hartemink (2016)
Mapping nucleosome positions using DNase-seqGenome Research, 26
Allen Bateman, Rositsa Karamanska, Marc Busch, Anne Dell, Christopher Olsen, S. Haslam (2010)
Glycan Analysis and Influenza A Virus Infection of Primary Swine Respiratory Epithelial CellsThe Journal of Biological Chemistry, 285
Guocheng Yuan, Jun Liu (2007)
Genomic Sequence Is Highly Predictive of Local Nucleosome DepletionPLoS Computational Biology, 4
Miele (2008)
DNA physical properties determine nucleosome occupancy from yeast to flyNucleic Acids Res, 11
Shobhit Gupta, J. Dennis, R. Thurman, R. Kingston, J. Stamatoyannopoulos, William Noble (2008)
Predicting Human Nucleosome Occupancy from Primary SequencePLoS Computational Biology, 4
Travis Mavrich, Cizhong Jiang, I. Ioshikhes, Xiaoyong Li, Bryan Venters, Sara Zanton, L. Tomsho, J. Qi, R. Glaser, S. Schuster, D. Gilmour, I. Albert, B. Pugh (2008)
Nucleosome organization in the Drosophila genomeNature, 453
P. Minary, M. Levitt (2014)
Training-free atomistic prediction of nucleosome occupancyProceedings of the National Academy of Sciences, 111
A. Krizhevsky, Ilya Sutskever, Geoffrey Hinton (2012)
ImageNet classification with deep convolutional neural networksCommunications of the ACM, 60
E. Segal, J. Widom (2009)
What controls nucleosome positions?Trends in genetics : TIG, 25 8
S. Pulivarthy, M. Lion, Guray Kuzu, A. Matthews, M. Borowsky, John Morris, R. Kingston, J. Dennis, M. Tolstorukov, M. Oettinger (2016)
Regulated large-scale nucleosome density patterns and precise nucleosome positioning correlate with V(D)J recombinationProceedings of the National Academy of Sciences, 113
K. Struhl, E. Segal (2013)
Determinants of nucleosome positioningNature Structural &Molecular Biology, 20
Rong-En Fan, Pai-Hsuen Chen, Chih-Jen Lin (2005)
Working Set Selection Using Second Order Information for Training Support Vector MachinesJ. Mach. Learn. Res., 6
David Kelley, Jasper Snoek, J. Rinn (2015)
Basset: learning the regulatory code of the accessible genome with deep convolutional neural networksGenome Research, 26
Ronan Collobert, J. Weston, L. Bottou, Michael Karlen, K. Kavukcuoglu, P. Kuksa (2011)
Natural Language Processing (Almost) from ScratchArXiv, abs/1103.0398
MotivationNucleosome positioning plays significant roles in proper genome packing and its accessibility to execute transcription regulation. Despite a multitude of nucleosome positioning resources available on line including experimental datasets of genome-wide nucleosome occupancy profiles and computational tools to the analysis on these data, the complex language of eukaryotic Nucleosome positioning remains incompletely understood.ResultsHere, we address this challenge using an approach based on a state-of-the-art machine learning method. We present a novel convolutional neural network (CNN) to understand nucleosome positioning. We combined Inception-like networks with a gating mechanism for the response of multiple patterns and long term association in DNA sequences. We developed the open-source package LeNup based on the CNN to predict nucleosome positioning in Homo sapiens, Caenorhabditis elegans, Drosophila melanogaster as well as Saccharomyces cerevisiae genomes. We trained LeNup on four benchmark datasets. LeNup achieved greater predictive accuracy than previously published methods.Availability and implementationLeNup is freely available as Python and Lua script source code under a BSD style license from https://github.com/biomedBit/LeNup.Supplementary informationSupplementary data are available at Bioinformatics online.
Bioinformatics – Oxford University Press
Published: Jan 10, 2018
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