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» Two-phase clustering strategy for gene expression data sets
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KDD
2003
ACM
142views Data Mining» more  KDD 2003»
15 years 10 months ago
Mining phenotypes and informative genes from gene expression data
Mining microarray gene expression data is an important research topic in bioinformatics with broad applications. While most of the previous studies focus on clustering either gene...
Chun Tang, Aidong Zhang, Jian Pei
81
Voted
ISMB
2000
14 years 10 months ago
Mining for Putative Regulatory Elements in the Yeast Genome Using Gene Expression Data
We have developed a set of methods and tools for automatic discovery of putative regulatory signals in genome sequences. The analysis pipeline consists of gene expression data clu...
Jaak Vilo, Alvis Brazma, Inge Jonassen, Alan J. Ro...
BMCBI
2005
122views more  BMCBI 2005»
14 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...
69
Voted
DAWAK
2005
Springer
15 years 3 months ago
Gene Expression Biclustering Using Random Walk Strategies
A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rando...
Fabrizio Angiulli, Clara Pizzuti
BMCBI
2011
14 years 4 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso