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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Journal ArticleDOI
Investigating the contribution of distance-based features to automatic sleep stage classification
TL;DR: Evaluated new features to characterize each sleep stage in such a way that extracted features were more powerful than conventional features, to distinguish sleep stages from each other, and to improve classifiers accuracy.
Proceedings ArticleDOI
Multiple feature construction in classification on high-dimensional data using GP
TL;DR: This paper proposes a GP-based method that simultaneously performs multiple feature construction and feature selection to automatically transform high-dimensional datasets into much smaller ones and reveals different preferences of the three learning algorithms on these feature sets.
Proceedings ArticleDOI
Optimized feature subsets for epileptic seizure prediction studies
TL;DR: A comparative study of three feature selection methods, based on Support Vector Machines, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.
Journal ArticleDOI
Predicting linear B-cell epitopes by using sequence-derived structural and physicochemical features
TL;DR: A novel encoding scheme which combines several groups of sequence-derived structural and physicochemical features, and support vector machine was used to construct the prediction models, and demonstrated better results than benchmark methods.
Journal ArticleDOI
The Max-Min High-Order Dynamic Bayesian Network for Learning Gene Regulatory Networks with Time-Delayed Regulations
TL;DR: Results show that MMHO-DBN is more accurate than current time-delayed GRN learning methods, and has an intermediate computing performance, and it is able to learn long time-Delayed relationships between genes.
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.