Abstract Details
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Activity Number:
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653
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Type:
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Contributed
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Date/Time:
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Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #310432 |
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Title:
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Microarray Gene Expression of Two Prostate Cancer Cell Lines Using Bayesian Clustering Algorithm
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Author(s):
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Jean A. Roayaei*+
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Companies:
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NIH, National Cancer Institute
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Keywords:
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Abstract:
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We analyzed .CEL files for two prostate cancer cell lines. For each cell line there are three replicates. The first three are not drug-resistant. The last three are drug-resistant. Most cancer patients at some time during treatment develop, MDR. We have queried our results using a large data base at NCI namely NCI-60. We developed a linear mixed model where the stochastic error term has a conjugate prior distribution. We have used frequentists and their Bayesian analogues to compare how many prostate cancer-causing genes are repeated in the simulation model. An MCMC model was used with 10000 burn-ins for the its convergence. We used Gibbs and Importance Sampling techniques. We discovered 328 prostate cancer-causing genes.
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Authors who are presenting talks have a * after their name.
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