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» Clustering cancer gene expression data: a comparative study
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KDD
2002
ACM
183views Data Mining» more  KDD 2002»
16 years 3 days ago
E-CAST: A Data Mining Algorithm for Gene Expression Data
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
BMCBI
2006
186views more  BMCBI 2006»
14 years 11 months ago
Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method
Background: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments....
Xiaoli Li, Yin-Chet Tan, See-Kiong Ng
BMCBI
2007
180views more  BMCBI 2007»
14 years 11 months ago
Splicy: a web-based tool for the prediction of possible alternative splicing events from Affymetrix probeset data
Background: The Affymetrix™ technology is nowadays a well-established method for the analysis of gene expression profiles in cancer research studies. However, changes in gene ex...
Davide Rambaldi, Barbara Felice, Viviane Praz, Phi...
ICASSP
2008
IEEE
15 years 6 months ago
Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory
Based on the correlation between expression and ontologydriven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic f...
Yinyin Yuan, Chang-Tsun Li
BMCBI
2010
152views more  BMCBI 2010»
14 years 11 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...