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» Bayesian Networks Learning for Gene Expression Datasets
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BMCBI
2007
146views more  BMCBI 2007»
14 years 9 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
PSB
2004
14 years 10 months ago
Modeling Cellular Processes with Variational Bayesian Cooperative Vector Quantizer
Gene expression of a cell is controlled by sophisticated cellular processes. The capability of inferring the states of these cellular processes would provide insight into the mech...
Xinghua Lu, Milos Hauskrecht, Roger S. Day
ISBRA
2009
Springer
15 years 4 months ago
Using Gene Expression Modeling to Determine Biological Relevance of Putative Regulatory Networks
Identifying gene regulatory networks from high-throughput gene expression data is one of the most important goals of bioinformatics, but it remains difficult to define what makes a...
Peter Larsen, Yang Dai
BMCBI
2006
153views more  BMCBI 2006»
14 years 9 months ago
Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling
Background: It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that prope...
Xia Li, Shaoqi Rao, Wei Jiang, Chuanxing Li, Yun X...
JMLR
2008
209views more  JMLR 2008»
14 years 9 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger