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Machine learning applications in genetics and genomics

author

William S. Noble

2000 -

published in: Nature Reviews Genetics

date of publication: 2015-05-07

language: English

main subject: machine learning

Cites articles 46

Date

Title

Authors

2014-02-02

A general framework for estimating the relative pathogenicity of human genetic variants

Martin Kircher, Brian J O'Roak, Gregory M Cooper, Jay Shendure, Daniela Witten
2013-10-12

Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology

Ali Mobasheri, Anna Swan, David Allaway, Jaume Bacardit
2013-05-29

Machine learning and genome annotation: a match meant to be?

Mark Bender Gerstein
2013-03

Machine learning approaches for the discovery of gene-gene interactions in disease data

Rosie Upstill-Goddard, Andrew Collins, Diana Eccles
2012-11-01

An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems

Jason H. Moore
2012-09-06

An integrated encyclopedia of DNA elements in the human genome

Alvis Brazma, Laurens G Wilming, Toby Hunt, Andrew Berry
2012

Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors

Ewan Birney, Mark Bender Gerstein, Anshul Kundaje, Joel Rozowsky, Michael P. Snyder, Peter J. Bickel
2012

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data

Enrico Glaab, Jaume Bacardit, Jonathan M. Garibaldi, Natalio Krasnogor
2012-03-18

Unsupervised pattern discovery in human chromatin structure through genomic segmentation

Michael M. Hoffman, William S. Noble, Orion J Buske
2012-02-28

ChromHMM: automating chromatin-state discovery and characterization

Manolis Kellis
2012-01-01

Epigenetic priors for identifying active transcription factor binding sites

William S. Noble, Gabriel Cuellar-Partida, Timothy L. Bailey
2012

Using Expert Knowledge to Guide Covering and Mutation in a Michigan Style Learning Classifier System to Detect Epistasis and Heterogeneity

Jason H. Moore
2011-03

Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data

Yoav Gilad, Roger Pique-Regi, Daniel J Gaffney, Jonathan K. Pritchard
2011-06-14

On the choice of the best imputation methods for missing values considering three groups of classification methods

Salvador García, Francisco Herrera
2010-01-01

Computational methods for ab initio and comparative gene finding

Graziano Pesole, Ernesto Picardi
2010-02

DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells

Gregory E. Crawford, Lingyun Song
2010-02-01

Histone modification levels are predictive for gene expression

Martin Vingron
2010-07-01

Illuminating eukaryotic transcription start sites
2009-12-07

ChIP-Seq of transcription factors predicts absolute and differential gene expression in embryonic stem cells
2009-08-31

An ensemble model of competitive multi-factor binding of the genome

Alexander J Hartemink
2009-01-19

Probabilistic models and machine learning in structural bioinformatics.

Thomas Hamelryck
2008-06-27

A critical assessment of Mus musculus gene function prediction using integrated genomic evidence

Andrea Pagnani, Ziv Bar-Joseph, Trupti Joshi, Frederick P. Roth, Judith A. Blake, Judith Klein-Seetharaman, Wan Kyu Kim, Sara Mostafavi, Olga Troyanskaya, Quaid D Morris, Edward Marcotte, Chao Zhang, Michael I. Jordan, David Warde-Farley
2008-04-18

Predicting co-complexed protein pairs from heterogeneous data

William S. Noble
2007-03-23

Unsupervised segmentation of continuous genomic data

John Stamatoyannopoulos
2007-03

Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome

Rhona K Stuart, Gregory E. Crawford
2006-12-01

What is a support vector machine?
2006-08-17

A genomic code for nucleosome positioning

Eran Segal
2006-05-05

Optimizing amino acid substitution matrices with a local alignment kernel

Jean-Philippe Vert, Tatsuya Akutsu
2004-06-01

A probabilistic view of gene function

Andrew G. Fraser, Edward Marcotte
2004-05-06

A statistical framework for genomic data fusion

William S. Noble, Michael I. Jordan
2004-02-01

Inferring cellular networks using probabilistic graphical models

Nir Friedman
2004-04-01

Predicting gene expression from sequence.

Article - wd:Q38463061

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