This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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222
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 2, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #307284 |
Title:
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Bayesian Models for Genetic Pathways
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Author(s):
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Yuan Ji*+
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Companies:
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MD Anderson Cancer Center
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Address:
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1400 Pressler Street, Houston, TX, 77230,
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Keywords:
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Graphical models ;
Mixture model ;
Network ;
Protein array ;
Reciprocal graph
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Abstract:
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We define a class of Bayesian graphical models for the inference of molecular pathways based on expression data. Under a Bayesian framework, our models update a prior consensus pathway using expression profiles and provide posterior estimates of protein-protein interactions that are specific to the study population. Specifically, we define mixture models for the observed expression data which further introduce latent states of the expression. We construct informative network prior models for the latent states to quantify the prior information of consensus pathways. For inference, the posterior network is presented as reciprocal graphs with directionality and strength for each protein-protein interaction. We demonstrate the models using a novel type of proteomics data based on reverse phase protein arrays (RPPA).
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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