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» Smoothing Gene Expression Using Biological Networks
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BMCBI
2005
98views more  BMCBI 2005»
13 years 7 months ago
Iterative approach to model identification of biological networks
Background: Recent advances in molecular biology techniques provide an opportunity for developing detailed mathematical models of biological processes. An iterative scheme is intr...
Kapil G. Gadkar, Rudiyanto Gunawan, Francis J. Doy...
IJCNN
2000
IEEE
14 years 3 days ago
Evolving Neural Network Structures Using Axonal Growth Mechanisms
In the eld of arti cial evolution creating methods to evolve neural networks is an important goal. But how to encode the structure and properties of the neural network in the geno...
Peter Eggenberger
RECOMB
2003
Springer
14 years 8 months ago
An integrated probabilistic model for functional prediction of proteins
We develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression network, protein complex data, and d...
Minghua Deng, Ting Chen, Fengzhu Sun
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Systematic identification of yeast cell cycle transcription factors using multiple data sources
Background: Eukaryotic cell cycle is a complex process and is precisely regulated at many levels. Many genes specific to the cell cycle are regulated transcriptionally and are exp...
Wei-Sheng Wu, Wen-Hsiung Li
BMCBI
2008
129views more  BMCBI 2008»
13 years 7 months ago
Gene set enrichment analysis for non-monotone association and multiple experimental categories
Background: Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression...
Rongheng Lin, Shuangshuang Dai, Richard D. Irwin, ...