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BMCBI
2005
124views more  BMCBI 2005»
13 years 7 months ago
ErmineJ: Tool for functional analysis of gene expression data sets
Background: It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories...
Homin K. Lee, William Braynen, Kiran Keshav, Paul ...
BIOINFORMATICS
2007
137views more  BIOINFORMATICS 2007»
13 years 7 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
ICPR
2008
IEEE
14 years 2 months ago
A fuzzy c-means algorithm using a correlation metrics and gene ontology
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...
BMCBI
2010
153views more  BMCBI 2010»
13 years 7 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BMCBI
2008
146views more  BMCBI 2008»
13 years 7 months ago
ProLoc-GO: Utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization
Background: Gene Ontology (GO) annotation, which describes the function of genes and gene products across species, has recently been used to predict protein subcellular and subnuc...
Wen-Lin Huang, Chun-Wei Tung, Shih-Wen Ho, Shiow-F...