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» Modelling Developmental Regulatory Networks
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JMLR
2008
209views more  JMLR 2008»
13 years 8 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
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
13 years 10 months ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
GI
2009
Springer
14 years 20 days ago
Massively-Parallel Simulation of Biochemical Systems
: Understanding biological evolution prompts for a detailed understanding of the realized phenotype. Biochemical and gene regulatory dynamics are a cornerstone for the physiology o...
Jens Ackermann, Paul Baecher, Thorsten Franzel, Mi...
BMCBI
2008
130views more  BMCBI 2008»
13 years 8 months ago
Function approximation approach to the inference of reduced NGnet models of genetic networks
Background: The inference of a genetic network is a problem in which mutual interactions among genes are deduced using time-series of gene expression patterns. While a number of m...
Shuhei Kimura, Katsuki Sonoda, Soichiro Yamane, Hi...