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BMCBI
2010
176views more  BMCBI 2010»
15 years 2 months ago
Bayesian statistical modelling of human protein interaction network incorporating protein disorder information
Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
JCB
2007
198views more  JCB 2007»
15 years 1 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
UAI
2003
15 years 3 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
15 years 7 months ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole
130
Voted
BICOB
2009
Springer
15 years 8 months ago
A Bayesian Approach to High-Throughput Biological Model Generation
Abstract. With the availability of hundreds and soon-to-be thousands of complete genomes, the construction of genome-scale metabolic models for these organisms has attracted much a...
Xinghua Shi, Rick L. Stevens