BMCBI
2007
13 years 4 months ago
2007
Background: Clustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the explorati...
BMCBI
2007
13 years 4 months ago
2007
Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, a...
BMCBI
2007
13 years 4 months ago
2007
Background: Clustering methods are widely used on gene expression data to categorize genes with similar expression profiles. Finding an appropriate (dis)similarity measure is crit...
BMCBI
2008
13 years 4 months ago
2008
Background: This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascade...
BMCBI
2007
13 years 4 months ago
2007
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
BMCBI
2010
13 years 4 months ago
2010
Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful inf...
BMCBI
2008
13 years 4 months ago
2008
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
BMCBI
2010
13 years 4 months ago
2010
Background: There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunatel...
BMCBI
2010
13 years 4 months ago
2010
Background: Principal component analysis (PCA) has gained popularity as a method for the analysis of highdimensional genomic data. However, it is often difficult to interpret the ...
BIBM
2008
IEEE
13 years 4 months ago
2008
IEEE
This paper addresses the protein classification problem, and explores how its accuracy can be improved by using information from time-course gene expression data. The methods are ...