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» Classification with reject option in gene expression data
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BMCBI
2006
129views more  BMCBI 2006»
14 years 9 months ago
Identifying genes that contribute most to good classification in microarrays
Background: The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The dis...
Stuart G. Baker, Barnett S. Kramer
BMCBI
2006
200views more  BMCBI 2006»
14 years 9 months ago
Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data
Background: Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, clas...
Ian B. Jeffery, Desmond G. Higgins, Aedín C...
KES
2006
Springer
14 years 9 months ago
Combined Gene Selection Methods for Microarray Data Analysis
In recent years, the rapid development of DNA Microarray technology has made it possible for scientists to monitor the expression level of thousands of genes in a single experiment...
Hong Hu, Jiuyong Li, Hua Wang, Grant Daggard
APBC
2004
121views Bioinformatics» more  APBC 2004»
14 years 11 months ago
Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection
Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early...
Larry T. H. Yu, Fu-Lai Chung, Stephen Chi-fai Chan...
CSDA
2008
128views more  CSDA 2008»
14 years 9 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...