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JCB
2006
185views more  JCB 2006»
14 years 9 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson
ISMB
1993
14 years 11 months ago
Pattern Discovery in Gene Regulation: Designing an Analysis Environment
Interactions that determinecellular fate are exceedingly complex, can take place at different levels of gene regulation and involve a large numberof components(such as genes, prot...
Stella Veretnik, Bruce R. Schatz
JMLR
2010
140views more  JMLR 2010»
14 years 4 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
ICPR
2008
IEEE
15 years 4 months ago
A supervised learning approach for imbalanced data sets
This paper presents a new learning approach for pattern classification applications involving imbalanced data sets. In this approach, a clustering technique is employed to resamp...
Giang Hoang Nguyen, Abdesselam Bouzerdoum, Son Lam...
WABI
2009
Springer
124views Bioinformatics» more  WABI 2009»
15 years 4 months ago
Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction
Background: Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often use...
Matthew Hansen, Logan Everett, Larry Singh, Sridha...