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» Can we Find Molecular Signatures from Gene Expression Data
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BMCBI
2006
213views more  BMCBI 2006»
13 years 8 months ago
CoXpress: differential co-expression in gene expression data
Background: Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find...
Michael Watson
BMCBI
2011
13 years 6 days ago
Gene set analysis for longitudinal gene expression data
Background: Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. ...
Ke Zhang, Haiyan Wang, Arne C. Bathke, Solomon W. ...
RECOMB
2001
Springer
14 years 9 months ago
Applications of generalized pair hidden Markov models to alignment and gene finding problems
Hidden Markov models (HMMs) have been successfully applied to a variety of problems in molecular biology, ranging from alignment problems to gene nding and annotation. Alignment p...
Lior Pachter, Marina Alexandersson, Simon Cawley
BMCBI
2007
151views more  BMCBI 2007»
13 years 8 months ago
A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microar
Background: The incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a...
Peter Larsen, Eyad Almasri, Guanrao Chen, Yang Dai
BMCBI
2007
198views more  BMCBI 2007»
13 years 8 months ago
Correlation analysis reveals the emergence of coherence in the gene expression dynamics following system perturbation
Time course gene expression experiments are a popular means to infer co-expression. Many methods have been proposed to cluster genes or to build networks based on similarity measu...
Nicola Neretti, Daniel Remondini, Marc Tatar, John...