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» A framework for modelling virus gene expression data
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FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
13 years 9 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
CIBCB
2007
IEEE
13 years 11 months ago
Associative Artificial Neural Network for Discovery of Highly Correlated Gene Groups Based on Gene Ontology and Gene Expression
Abstract-- The advance of high-throughput experimental technologies poses continuous challenges to computational data analysis in functional and comparative genomics studies. Gene ...
Ji He, Xinbin Dai, Xuechun Zhao
ENTCS
2010
97views more  ENTCS 2010»
13 years 4 months ago
A Framework for Modelling and Simulating Networks of Cells
Several complex biological phenomena are to be modelled in terms of a large and dynamic network of compartments, where the interplay between inter-compartment and intra-compartmen...
Sara Montagna, Mirko Viroli
GPB
2010
231views Solid Modeling» more  GPB 2010»
13 years 4 months ago
Mining Gene Expression Profiles: An Integrated Implementation of Kernel Principal Component Analysis and Singular Value Decompos
The detection of genes that show similar profiles under different experimental conditions is often an initial step in inferring the biological significance of such genes. Visualiz...
Ferran Reverter, Esteban Vegas, Pedro Sánch...
BMCBI
2007
138views more  BMCBI 2007»
13 years 7 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...