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Activity Number: 262
Type: Contributed
Date/Time: Monday, August 1, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #319414
Title: Genome-Wide Transcription Regulation Discovery for Breast Cancer Cell Lines
Author(s): Zangdong He* and Lang Li and Changyu Shen
Companies: Indiana University Fairbanks School of Public Health and Indiana University School of Medicine and Indiana University School of Medicine
Keywords: Transcription ; Mixture model ; Empirical Bayes ; Breast Cancer

Long-range chromatin interactions based on chromosome folding involve bringing physically separated functional elements into close proximity. In particular, interaction between distant enhancers and promoters is an essential mechanism for transcriptional regulation of genes. We hypothesize that, in breast cancer cell lines, upon hormone/chemo treatment, the interactions between transcriptional regulation regions and promoters for target genes that are sensitive to treatment will alter significantly. We developed a Mixture Beta-Binomial model imbedded in the saturated empirical Bayesian Framework to characterize chromosome folding, and identify potential target genes as well significant interactions genome widely.

Authors who are presenting talks have a * after their name.

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