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Activity Number:
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421
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Type:
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Contributed
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Date/Time:
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Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #307046 |
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Title:
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Combining QTL Analysis and Bayesian Network Discovery Methods To Determine Genetic Relationships in a Micorarray/Marker Dataset
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Author(s):
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Christine W. Duarte*+ and Zhao-Bang Zeng
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Companies:
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North Carolina State University and Bioinformatics Research Center
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Address:
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Bioinformatics Research Center, Raleigh, NC, 27695-7566,
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Keywords:
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QTL ; microarray ; Bayesian networks
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Abstract:
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The knowledge of genetic regulatory mechanisms has important applications in medicine and biotechnology, but experiments for determining such mechanisms are labor-intensive and costly. The analysis of large-scale genomic datasets may represent an alternative path to learning genetic relationships, but first bioinformatic tools to mine this data must be developed. In this work, a method for the discovery of genetic networks has been developed which combines QTL analysis methodology and Bayesian Network learning algorithms. This method involves analyzing microarray and marker data from the progeny of a backcross of two genetically distinct lines. This method has been applied to analyze the genetic mechanism underlying the co-regulation of genes involved in the lignin biosynthesis pathway in Eucalptus trees. Preliminary results in the analysis of yeast data will be presented as well.
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