PMID: 15852500Apr 27, 2005Paper

Minimum redundancy feature selection from microarray gene expression data

Journal of Bioinformatics and Computational Biology
Chris Ding, Hanchuan Peng

Abstract

How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes. Widely used methods typically rank genes according to their differential expressions among phenotypes and pick the top-ranked genes. We observe that feature sets so obtained have certain redundancy and study methods to minimize it. We propose a minimum redundancy - maximum relevance (MRMR) feature selection framework. Genes selected via MRMR provide a more balanced coverage of the space and capture broader characteristics of phenotypes. They lead to significantly improved class predictions in extensive experiments on 6 gene expression data sets: NCI, Lymphoma, Lung, Child Leukemia, Leukemia, and Colon. Improvements are observed consistently among 4 classification methods: Naive Bayes, Linear discriminant analysis, Logistic regression, and Support vector machines. SUPPLIMENTARY: The top 60 MRMR genes for each of the datasets are listed in http://crd.lbl.gov/~cding/MRMR/. More information related to MRMR methods can be found at http://www.hpeng.net/.

References

Jun 9, 1999·Proceedings of the National Academy of Sciences of the United States of America·U AlonA J Levine
Mar 4, 2000·Nature Genetics·U ScherfJ N Weinstein
Dec 7, 2000·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·A Ben-DorZ Yakhini
Feb 7, 2001·Proceedings of the National Academy of Sciences of the United States of America·J B WelshG M Hampton
Jul 27, 2001·Bioinformatics·F ModelC Piepenbrock
Nov 3, 2001·Genome Research·M XiongJ Zhao
Nov 15, 2001·Proceedings of the National Academy of Sciences of the United States of America·M E GarberI Petersen
Feb 12, 2002·Bioinformatics·Danh V Nguyen, David M Rocke
Feb 5, 2008·IEEE Transactions on Neural Networks·Chih-Wei Hsu, Chih-Jen Lin
Nov 26, 2009·Genome Génome / Conseil National De Recherches Canada·M ButiL Natali

❮ Previous
Next ❯

Citations

Aug 13, 2010·Journal of Medical Systems·C Okan Sakar, Olcay Kursun
Aug 4, 2011·Journal of Medical Systems·Sheau-Ling HsiehFeipei Lai
Jul 28, 2009·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Michael R MehanXianghong Jasmine Zhou
Jan 19, 2010·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Peng QiuSylvia K Plevritis
Feb 15, 2014·Advances in Wound Care·Tomasz ArodzRobert F Diegelmann
Sep 2, 2006·Bioinformatics·Chunlin WangStephen R Holbrook
Jul 1, 2008·Bioinformatics·Jun LiuTamer Kahveci
Jul 8, 2008·Bioinformatics·Hanchuan Peng
Apr 3, 2012·Bioinformatics·Robert KüffnerRalf Zimmer
Sep 24, 2010·Nucleic Acids Research·Dong DongZhaolei Zhang
Sep 13, 2012·Epilepsia·Wesley T KerrMark S Cohen
Mar 21, 2008·EURASIP Journal on Bioinformatics & Systems Biology·Patrick E MeyerGianluca Bontempi
Jan 17, 2009·EURASIP Journal on Bioinformatics & Systems Biology·Catharina OlsenGianluca Bontempi
Oct 10, 2013·Neural Computation·Makoto YamadaMasashi Sugiyama
Sep 24, 2010·BMC Bioinformatics·Hui LiuYufei Huang
Jul 16, 2011·BMC Bioinformatics·Jeff SkinnerAndrey Morgun
Nov 15, 2012·BMC Bioinformatics·Hongyan ZhangZheming Yuan
Mar 26, 2005·BMC Bioinformatics·Xiaoxing LiuAdrian Mondry
Oct 5, 2007·BMC Bioinformatics·Ji-Gang Zhang, Hong-Wen Deng
Mar 6, 2012·BMC Genomics·Chang ChangTieliu Shi
Mar 19, 2013·BMC Medical Imaging·Sonal KothariMay D Wang
Oct 6, 2010·BMC Systems Biology·Gökmen Altay, Frank Emmert-Streib
Jan 29, 2011·BMC Medical Genomics·Azadeh MohammadiMansoor Salehi
Dec 3, 2010·PLoS Computational Biology·Lior ShamirIlya G Goldberg
Aug 5, 2011·PloS One·Yue CuiUNKNOWN Alzheimer's Disease Neuroimaging Initiative

❮ Previous
Next ❯

Related Concepts

Related Feeds

Allen Institute for Brain Science Network

The Allen Institute for Brain Science Network is a not-for-profit biomedical research organization that provides open access to multiple neuroscience tools and resources. Find the latest research from tjr Allen Institute for Brain Science Network here.