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» Analysis techniques for microarray time-series data
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BIOINFORMATICS
2002
146views more  BIOINFORMATICS 2002»
13 years 8 months ago
A duplication growth model of gene expression networks
Motivation: There has been considerable interest in developing computational techniques for inferring genetic regulatory networks from whole-genome expression profiles. When expre...
Ashish Bhan, David J. Galas, T. Gregory Dewey
WSC
1998
13 years 10 months ago
Advanced Methods for Simulation Output Analysis
This paper reviews statistical methods for analyzing output data from computer simulations of single systems. In particular, it focuses on the problems of choosing initial conditi...
Christos Alexopoulos, Andrew F. Seila
BMCBI
2006
239views more  BMCBI 2006»
13 years 8 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...
BMCBI
2007
169views more  BMCBI 2007»
13 years 8 months ago
Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and i
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...
Abdallah Sayyed-Ahmad, Kagan Tuncay, Peter J. Orto...
BMCBI
2010
152views more  BMCBI 2010»
13 years 8 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...