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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2005
88views more  BMCBI 2005»
13 years 7 months ago
Using large-scale perturbations in gene network reconstruction
Background: Recent analysis of the yeast gene network shows that most genes have few inputs, indicating that enumerative gene reconstruction methods are both useful and computatio...
Thomas MacCarthy, Andrew Pomiankowski, Robert Seym...
IDA
2005
Springer
14 years 29 days ago
Bayesian Networks Learning for Gene Expression Datasets
DNA arrays yield a global view of gene expression and can be used to build genetic networks models, in order to study relations between genes. Literature proposes Bayesian network ...
Giacomo Gamberoni, Evelina Lamma, Fabrizio Riguzzi...
BMCBI
2007
151views more  BMCBI 2007»
13 years 7 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
IWANN
2009
Springer
14 years 2 months ago
GREAT: Gene Regulation EvAluation Tool
Our understanding of biological systems is highly dependent on the study of the mechanisms that regulate genetic expression. In this paper we present a tool to evaluate scientific ...
Catia Machado, Hugo P. Bastos, Francisco M. Couto
HIS
2008
13 years 9 months ago
Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
André L. D. Rossi, André C. P. L. F....