Sciweavers

111 search results - page 11 / 23
» Evaluation of gene importance in microarray data based upon ...
Sort
View
BMCBI
2006
164views more  BMCBI 2006»
13 years 6 months ago
Evaluation of clustering algorithms for gene expression data
Background: Cluster analysis is an integral part of high dimensional data analysis. In the context of large scale gene expression data, a filtered set of genes are grouped togethe...
Susmita Datta, Somnath Datta
BMCBI
2010
153views more  BMCBI 2010»
13 years 6 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...
JCB
2002
160views more  JCB 2002»
13 years 6 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, ...
BMCBI
2008
160views more  BMCBI 2008»
13 years 6 months ago
A method for analyzing censored survival phenotype with gene expression data
Background: Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles a...
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Ch...
CEC
2007
IEEE
13 years 10 months ago
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
Enrique Alba, José García-Nieto, Lae...