Machine learning applications in genetics and genomics
暂无分享,去创建一个
[1] A. Tikhonov. On the stability of inverse problems , 1943 .
[2] Jacob Cohen,et al. Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. , 1968 .
[3] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[4] P. Bucher. Weight matrix descriptions of four eukaryotic RNA polymerase II promoter elements derived from 502 unrelated promoter sequences. , 1990, Journal of molecular biology.
[5] Bernhard E. Boser,et al. A training algorithm for optimal margin classifiers , 1992, COLT '92.
[6] Michael I. Jordan. Why the logistic function? A tutorial discussion on probabilities and neural networks , 1995 .
[7] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[8] R. Durbin,et al. Pfam: A comprehensive database of protein domain families based on seed alignments , 1997, Proteins.
[9] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[10] Alexander J. Smola,et al. Learning with kernels , 1998 .
[11] Gunnar Rätsch,et al. Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites , 2000, German Conference on Bioinformatics.
[12] J. Pearl. Causality: Models, Reasoning and Inference , 2000 .
[13] Michal Linial,et al. Using Bayesian Networks to Analyze Expression Data , 2000, J. Comput. Biol..
[14] M. Ashburner,et al. Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.
[15] T. Poggio,et al. Multiclass cancer diagnosis using tumor gene expression signatures , 2001, Proceedings of the National Academy of Sciences of the United States of America.
[16] Russ B. Altman,et al. Missing value estimation methods for DNA microarrays , 2001, Bioinform..
[17] Alex Bateman,et al. The InterPro database, an integrated documentation resource for protein families, domains and functional sites , 2001, Nucleic Acids Res..
[18] Bernard De Baets,et al. Feature subset selection for splice site prediction , 2002, ECCB.
[19] Eleazar Eskin,et al. The Spectrum Kernel: A String Kernel for SVM Protein Classification , 2001, Pacific Symposium on Biocomputing.
[20] G. Rubin,et al. Computational analysis of core promoters in the Drosophila genome , 2002, Genome Biology.
[21] Jason Weston,et al. Learning Gene Functional Classifications from Multiple Data Types , 2002, J. Comput. Biol..
[22] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2003, ICTAI.
[23] A. Owen,et al. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae) , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[24] Bernhard Schölkopf,et al. Kernel Methods in Computational Biology , 2005 .
[25] Nello Cristianini,et al. A statistical framework for genomic data fusion , 2004, Bioinform..
[26] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[27] A. Fraser,et al. A probabilistic view of gene function , 2004, Nature Genetics.
[28] P. Kantor. Foundations of Statistical Natural Language Processing , 2001, Information Retrieval.
[29] Michael A. Beer,et al. Predicting Gene Expression from Sequence , 2004, Cell.
[30] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2004 .
[31] Martin A. Nowak,et al. Inferring Cellular Networks Using Probabilistic Graphical Models , 2004 .
[32] Irene K. Moore,et al. A genomic code for nucleosome positioning , 2006, Nature.
[33] William Stafford Noble,et al. Support vector machine , 2013 .
[34] Alexander Zien,et al. Semi-Supervised Learning , 2006 .
[35] Tatsuya Akutsu,et al. Optimizing amino acid substitution matrices with a local alignment kernel , 2006, BMC Bioinformatics.
[36] William Stafford Noble,et al. Unsupervised segmentation of continuous genomic data , 2007, Bioinform..
[37] Nathaniel D. Heintzman,et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome , 2007, Nature Genetics.
[38] Michael I. Jordan,et al. A critical assessment of Mus musculus gene function prediction using integrated genomic evidence , 2008, Genome Biology.
[39] William Stafford Noble,et al. Predicting Co-Complexed Protein Pairs from Heterogeneous Data , 2008, PLoS Comput. Biol..
[40] Thomas Hamelryck,et al. Probabilistic models and machine learning in structural bioinformatics , 2009, Statistical methods in medical research.
[41] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[42] A. Hartemink,et al. An ensemble model of competitive multi-factor binding of the genome. , 2009, Genome research.
[43] W. Wong,et al. ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells , 2009, Proceedings of the National Academy of Sciences.
[44] Julia A. Lasserre,et al. Histone modification levels are predictive for gene expression , 2010, Proceedings of the National Academy of Sciences.
[45] Ernesto Picardi,et al. Computational methods for ab initio and comparative gene finding. , 2010, Methods in molecular biology.
[46] Geoffrey I. Webb,et al. Encyclopedia of Machine Learning , 2011, Encyclopedia of Machine Learning.
[47] G. Crawford,et al. DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. , 2010, Cold Spring Harbor protocols.
[48] Illuminating eukaryotic transcription start sites , 2010, Nature Methods.
[49] Jacob F. Degner,et al. Sequence and Chromatin Accessibility Data Accurate Inference of Transcription Factor Binding from Dna Material Supplemental Open Access , 2022 .
[50] Francisco Herrera,et al. On the choice of the best imputation methods for missing values considering three groups of classification methods , 2012, Knowledge and Information Systems.
[51] Kevin Y. Yip,et al. Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors , 2012, Genome Biology.
[52] Jonathan M. Garibaldi,et al. Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data , 2012, PloS one.
[53] William Stafford Noble,et al. Epigenetic priors for identifying active transcription factor binding sites , 2012, Bioinform..
[54] Data production leads,et al. An integrated encyclopedia of DNA elements in the human genome , 2012 .
[55] T. Koski,et al. A Review of Bayesian Networks and Structure Learning , 2012 .
[56] William Stafford Noble,et al. Unsupervised pattern discovery in human chromatin structure through genomic segmentation , 2012, Nature Methods.
[57] Jason H. Moore,et al. Using Expert Knowledge to Guide Covering and Mutation in a Michigan Style Learning Classifier System to Detect Epistasis and Heterogeneity , 2012, PPSN.
[58] Jason H. Moore,et al. An analysis pipeline with statistical and visualization-guided knowledge discovery for Michigan-style learning classifier systems , 2012, IEEE Computational Intelligence Magazine.
[59] Martin Renqiang Min,et al. An integrated encyclopedia of DNA elements in the human genome , 2012 .
[60] Manolis Kellis,et al. ChromHMM: automating chromatin-state discovery and characterization , 2012, Nature Methods.
[61] Kevin Y. Yip,et al. Machine learning and genome annotation: a match meant to be? , 2013, Genome Biology.
[62] A. Mobasheri,et al. Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology. , 2013, Omics : a journal of integrative biology.
[63] Xavier Llorà,et al. Large‐scale data mining using genetics‐based machine learning , 2013, GECCO.
[64] Jörg Fliege,et al. Machine learning approaches for the discovery of gene-gene interactions in disease data , 2013, Briefings Bioinform..
[65] R. Hughes,et al. Cold Spring Harbor , 2014 .
[66] J. Shendure,et al. A general framework for estimating the relative pathogenicity of human genetic variants , 2014, Nature Genetics.