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JCB
2006
185views more  JCB 2006»
14 years 10 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
AAAI
1997
14 years 11 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
RECOMB
2008
Springer
15 years 10 months ago
A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics
The protein inference problem represents a major challenge in shotgun proteomics. Here we describe a novel Bayesian approach to address this challenge that incorporates the predict...
Yong Fuga Li, Randy J. Arnold, Yixue Li, Predrag R...
EMMCVPR
2007
Springer
15 years 4 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
BMCBI
2010
216views more  BMCBI 2010»
14 years 5 months ago
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies
Background: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors f...
Bo Chen, Minhua Chen, John William Paisley, Aimee ...