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» Using Bayesian networks to analyze expression data
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CVPR
2003
IEEE
14 years 6 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
WSC
2007
13 years 6 months ago
Analyzing air combat simulation results with dynamic Bayesian networks
In this paper, air combat simulation data is reconstructed into a dynamic Bayesian network. It gives a compact probabilistic model that describes the progress of air combat and al...
Jirka Poropudas, Kai Virtanen
BMCBI
2004
139views more  BMCBI 2004»
13 years 4 months ago
Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels an
Background: The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge r...
Jeffrey P. Townsend
BMCBI
2010
133views more  BMCBI 2010»
13 years 4 months ago
New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...