Journal ArticleDOI
Minimum redundancy feature selection from microarray gene expression data.
Chris Ding,Hanchuan Peng +1 more
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How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes.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 ...read more
Citations
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A Novel Method Incorporating Gene Ontology Information for Unsupervised Clustering and Feature Selection
TL;DR: A framework is presented that incorporates prior ontology information, which helped to perform unsupervised clustering of the phenotypes, and identify the genes relevant to each cluster of phenotypes that conferred differential toxicity to saturated vs. unsaturated FFAs.
Journal ArticleDOI
Robust gene selection methods using weighting schemes for microarray data analysis
Suyeon Kang,Jongwoo Song +1 more
TL;DR: The results of simulation study and real data analysis have demonstrated that the proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates.
Journal ArticleDOI
A cell profiling framework for modeling drug responses from HCS imaging.
Alvin Ng,Alvin Ng,Jagath C. Rajapakse,Jagath C. Rajapakse,Roy E. Welsch,Roy E. Welsch,Paul Matsudaira,Paul Matsudaira,Victor Horodincu,James G. Evans +9 more
TL;DR: The authors present an unsupervised, scalable, and interpretable cell profiling framework that is compatible with data gathered from high-content screening and identifies significant features of cell phenotypes for unsuper supervised learning based on maximum relevancy and minimum redundancy criteria.
Journal ArticleDOI
MAPanalyzer: a novel online tool for analyzing microtubule-associated proteins.
TL;DR: A MAP-centered online analysis tool, which consists of a MAP database and a novel MAP predictor which combines specialized machine learning classifiers and the BLAST homology searching tool, to serve as a promising computational resource for the investigations of MAPs.
Journal ArticleDOI
Text mining with emergent self organizing maps and multi-dimensional scaling: A comparative study on domestic violence
TL;DR: The usability of ESOM and MDS as text exploration instruments in police investigations is compared and they are combined with traditional classification instruments such as the SVM and Naive Bayes for significantly improving the classification accuracy.
References
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Journal ArticleDOI
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Journal ArticleDOI
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Ash A. Alizadeh,Michael B. Eisen,R. Eric Davis,Izidore S. Lossos,Andreas Rosenwald,Jennifer C. Boldrick,Hajeer Sabet,Truc Tran,Xin Yu,John Powell,Liming Yang,Gerald E. Marti,Troy Moore,James I. Hudson,Li-Sheng Lu,David B. Lewis,Robert Tibshirani,Gavin Sherlock,Wing C. Chan,Timothy C. Greiner,Dennis D. Weisenburger,James O. Armitage,Roger A. Warnke,Ronald Levy,Wyndham H. Wilson,M. R. Grever,John C. Byrd,David Botstein,Patrick O. Brown,Louis M. Staudt +29 more
TL;DR: It is shown that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour.
Journal ArticleDOI
Wrappers for feature subset selection
Ron Kohavi,George H. John +1 more
TL;DR: The wrapper method searches for an optimal feature subset tailored to a particular algorithm and a domain and compares the wrapper approach to induction without feature subset selection and to Relief, a filter approach tofeature subset selection.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.
Journal ArticleDOI
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.
Uri Alon,Naama Barkai,Daniel A. Notterman,Kurt C. Gish,S. Ybarra,David H. Mack,A. J. Levine,A. J. Levine +7 more
TL;DR: In this paper, a two-way clustering algorithm was applied to both the genes and the tissues, revealing broad coherent patterns that suggest a high degree of organization underlying gene expression in these tissues.