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BMCBI
2007
173views more  BMCBI 2007»
13 years 5 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
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, ...
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
SIGMOD
2002
ACM
132views Database» more  SIGMOD 2002»
14 years 5 months ago
Clustering by pattern similarity in large data sets
Clustering is the process of grouping a set of objects into classes of similar objects. Although definitions of similarity vary from one clustering model to another, in most of th...
Haixun Wang, Wei Wang 0010, Jiong Yang, Philip S. ...
ALMOB
2008
93views more  ALMOB 2008»
13 years 5 months ago
A weighted average difference method for detecting differentially expressed genes from microarray data
Background: Identification of differentially expressed genes (DEGs) under different experimental conditions is an important task in many microarray studies. However, choosing whic...
Koji Kadota, Yuji Nakai, Kentaro Shimizu