Sciweavers

1674 search results - page 29 / 335
» Evaluation of clustering algorithms for gene expression data
Sort
View
62
Voted
CSB
2005
IEEE
121views Bioinformatics» more  CSB 2005»
15 years 7 months ago
Clustering Genes Using Gene Expression and Text Literature Data
Chengyong Yang, Erliang Zeng, Tao Li, Giri Narasim...
APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 2 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
BMCBI
2007
147views more  BMCBI 2007»
15 years 1 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn
BMCBI
2005
142views more  BMCBI 2005»
15 years 1 months ago
CLU: A new algorithm for EST clustering
Background: The continuous flow of EST data remains one of the richest sources for discoveries in modern biology. The first step in EST data mining is usually associated with EST ...
Andrey A. Ptitsyn, Winston Hide
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
15 years 1 months ago
Annotation-based distance measures for patient subgroup discovery in clinical microarray studies
: Background Clustering algorithms are widely used in the analysis of microarray data. In clinical studies, they are often applied to find groups of co-regulated genes. Clustering...
Claudio Lottaz, Joern Toedling, Rainer Spang