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» Gene expression modeling through positive boolean functions
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APBC
2004
116views Bioinformatics» more  APBC 2004»
13 years 8 months ago
Evolving Genetic Regulatory Networks Using an Artificial Genome
Boolean models of genetic regulatory networks (GRNs) have been shown to exhibit many of the characteristic dynamics of real GRNs, with gene expression patterns settling to point a...
Jennifer Hallinan, Janet Wiles
BMCBI
2005
189views more  BMCBI 2005»
13 years 7 months ago
Quantitative inference of dynamic regulatory pathways via microarray data
Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway ar...
Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen
NN
2007
Springer
267views Neural Networks» more  NN 2007»
13 years 7 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
BMCBI
2011
12 years 11 months ago
Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities
Background: Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Un...
Yao Fu, Laura R. Jarboe, Julie A. Dickerson
CORR
2007
Springer
128views Education» more  CORR 2007»
13 years 7 months ago
Model Selection Through Sparse Maximum Likelihood Estimation
We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting undirected graphical model is sparse. Our approach is to...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...