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» Classification of microarray data using gene networks
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127
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BMCBI
2007
152views more  BMCBI 2007»
15 years 2 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
138
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BIOINFORMATICS
2002
146views more  BIOINFORMATICS 2002»
15 years 2 months ago
A duplication growth model of gene expression networks
Motivation: There has been considerable interest in developing computational techniques for inferring genetic regulatory networks from whole-genome expression profiles. When expre...
Ashish Bhan, David J. Galas, T. Gregory Dewey
BMCBI
2008
142views more  BMCBI 2008»
15 years 2 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...
124
Voted
RECOMB
2006
Springer
16 years 2 months ago
Identification and Evaluation of Functional Modules in Gene Co-expression Networks
Abstract. Identifying gene functional modules is an important step towards elucidating gene functions at a global scale. In this paper, we introduce a simple method to construct ge...
Jianhua Ruan, Weixiong Zhang
APIN
2010
108views more  APIN 2010»
15 years 2 months ago
A low variance error boosting algorithm
Abstract. This paper introduces a robust variant of AdaBoost, cwAdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with da...
Ching-Wei Wang, Andrew Hunter