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» Bayesian inference for differential equations
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BMCBI
2005
178views more  BMCBI 2005»
13 years 8 months ago
A quantization method based on threshold optimization for microarray short time series
Background: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often ...
Barbara Di Camillo, Fatima Sanchez-Cabo, Gianna To...
BMCBI
2010
136views more  BMCBI 2010»
13 years 8 months ago
Bias correction and Bayesian analysis of aggregate counts in SAGE libraries
Background: Tag-based techniques, such as SAGE, are commonly used to sample the mRNA pool of an organism's transcriptome. Incomplete digestion during the tag formation proces...
Russell L. Zaretzki, Michael A. Gilchrist, William...
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...
NIPS
2008
13 years 10 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
CMSB
2009
Springer
14 years 3 months ago
Probabilistic Approximations of Signaling Pathway Dynamics
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
Bing Liu, P. S. Thiagarajan, David Hsu