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» Using Bayesian networks to analyze expression data
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IJCAI
2007
14 years 11 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
CGF
2008
142views more  CGF 2008»
14 years 10 months ago
Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context
DNA microarrays are used to measure the expression levels of thousands of genes simultaneously. In a time series experiment, the gene expressions are measured as a function of tim...
Michel A. Westenberg, Sacha A. F. T. van Hijum, Os...
MM
2010
ACM
163views Multimedia» more  MM 2010»
14 years 10 months ago
Sonify your face: facial expressions for sound generation
We present a novel visual creativity tool that automatically recognizes facial expressions and tracks facial muscle movements in real time to produce sounds. The facial expression...
Roberto Valenti, Alejandro Jaimes, Nicu Sebe
FLAIRS
2006
14 years 11 months ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
ITSSA
2006
109views more  ITSSA 2006»
14 years 10 months ago
Gene Expression Analysis in Multi-Agent Environment
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...