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» K2GA: Heuristically Guided Evolution of Bayesian Network Str...
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RECOMB
2005
Springer
14 years 5 months ago
Pairwise Local Alignment of Protein Interaction Networks Guided by Models of Evolution
Abstract. With ever increasing amount of available data on protein-protein interaction (PPI) networks and research revealing that these networks evolve at a modular level, discover...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
PERCOM
2007
ACM
14 years 5 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
UAI
1996
13 years 6 months ago
Learning Equivalence Classes of Bayesian Network Structures
Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
David Maxwell Chickering
UAI
2003
13 years 6 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
BMCBI
2006
239views more  BMCBI 2006»
13 years 5 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...