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BIBE
2007
IEEE
136views Bioinformatics» more  BIBE 2007»
13 years 9 months ago
A Two-Stage Gene Selection Algorithm by Combining ReliefF and mRMR
Abstract—Gene expression data usually contains a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes ...
Yi Zhang, Chris H. Q. Ding, Tao Li
BMCBI
2007
176views more  BMCBI 2007»
13 years 7 months ago
The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications
Background: Information resources on the World Wide Web play an indispensable role in modern biology. But integrating data from multiple sources is often encumbered by the need to...
J. Christopher Bare, Paul T. Shannon, Amy K. Schmi...
BMCBI
2006
102views more  BMCBI 2006»
13 years 7 months ago
Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of
Background: The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the la...
Tao Han, Jianyong Wang, Weida Tong, Martha M. Moor...
CANDC
2005
ACM
13 years 7 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
JCB
2002
160views more  JCB 2002»
13 years 7 months ago
Inference from Clustering with Application to Gene-Expression Microarrays
There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different u...
Edward R. Dougherty, Junior Barrera, Marcel Brun, ...