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JCB
2002
160views more  JCB 2002»
13 years 4 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, ...
IJPP
2008
158views more  IJPP 2008»
13 years 4 months ago
The ParTriCluster Algorithm for Gene Expression Analysis
Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under...
Renata Braga Araújo, Guilherme Henrique Tri...
VLDB
2004
ACM
143views Database» more  VLDB 2004»
13 years 10 months ago
GPX: Interactive Mining of Gene Expression Data
Discovering co-expressed genes and coherent expression patterns in gene expression data is an important data analysis task in bioinformatics research and biomedical applications. ...
Daxin Jiang, Jian Pei, Aidong Zhang
CSB
2004
IEEE
136views Bioinformatics» more  CSB 2004»
13 years 8 months ago
Minimum Entropy Clustering and Applications to Gene Expression Analysis
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Haifeng Li, Keshu Zhang, Tao Jiang
BMCBI
2008
133views more  BMCBI 2008»
13 years 5 months ago
A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
Background: Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible f...
Luca Corradi, Marco Fato, Ivan Porro, Silvia Scagl...