53 search results - page 3 / 11 » Using hidden Markov models to analyze gene expression time c... |
BMCBI
2007
13 years 7 months ago
2007
Background: Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targ...
EVOW
2005
Springer
14 years 29 days ago
2005
Springer
Abstract. Clustering still represents the most commonly used technique to analyze gene expression data—be it classical clustering approaches that aim at finding biologically rel...
BMCBI
2008
13 years 7 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
2006
13 years 7 months ago
2006
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
ISBRA
2009
Springer
14 years 2 months ago
2009
Springer
Identifying gene regulatory networks from high-throughput gene expression data is one of the most important goals of bioinformatics, but it remains difficult to define what makes a...