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Activity Number:
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506
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2009 : 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 - #304375 |
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Title:
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A Bayesian Hierarchical Model to Translate Microarray Findings into Biological Functional Profiles
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Author(s):
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Song Zhang*+
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Companies:
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The University of Texas Southwestern Medical Center
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Address:
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, Dallas, TX, 75390,
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Keywords:
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Micro Array ; Gene Ontology ; Bayes
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Abstract:
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High throughput screenings such as microarray experiments often produce a long list of genes which share a certain characteristic (e.g., differential expression). In many cases, this gene list does not provide sufficient insight into the underlying biology. Many approaches have been developed to translate the set of selected genes into biological functional profiles based on biological knowledge databases. Gene Ontology (GO) Consortium is one of the most widely used databases. The ontologies are structured as a directed acyclic graph indicating parent-child relationship. One drawback of the current approaches is that the hierarchical structure of the gene ontologies is ignored, which contains a substantial amount of information about interactive dependence among GO terms.
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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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