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BMCBI
2008
142views more  BMCBI 2008»
13 years 10 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu
BMCBI
2005
122views more  BMCBI 2005»
13 years 9 months ago
GenClust: A genetic algorithm for clustering gene expression data
Background: Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designe...
Vito Di Gesù, Raffaele Giancarlo, Giosu&egr...
BIOCOMP
2006
13 years 11 months ago
Learning Genetic and Gene Bayesian Networks with Hidden Variables: Bilayer Verification Algorithm
To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
Jason E. Aten
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
14 years 3 months ago
Multiplex PCR primer design for gene family using genetic algorithm
Hong-Long Liang, Chungnan Lee, Jain-Shing Wu
GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
14 years 3 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit