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» Learning Methods for DNA Binding in Computational Biology
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BMCBI
2011
14 years 4 months ago
Motif-guided sparse decomposition of gene expression data for regulatory module identification
Background: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for e...
Ting Gong, Jianhua Xuan, Li Chen, Rebecca B. Riggi...
89
Voted
BMCBI
2010
179views more  BMCBI 2010»
14 years 9 months ago
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties
Background: Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited ...
Zhuhong You, Zheng Yin, Kyungsook Han, De-Shuang H...
88
Voted
BMCBI
2007
185views more  BMCBI 2007»
14 years 9 months ago
GEDI: a user-friendly toolbox for analysis of large-scale gene expression data
Background: Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, a...
André Fujita, João Ricardo Sato, Car...
85
Voted
RECOMB
2001
Springer
15 years 10 months ago
Predicting the beta-helix fold from protein sequence data
A method is presented that uses b-strand interactions to predict the parallel right-handed b-helix super-secondary structural motif in protein sequences. A program called BetaWrap...
Phil Bradley, Lenore Cowen, Matthew Menke, Jonatha...
BMCBI
2007
164views more  BMCBI 2007»
14 years 9 months ago
Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...