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Abstract Details
Activity Number:
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72
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Biometrics Section
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Abstract - #300711 |
Title:
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Comotif: A Method for Identifying Transcription Co-Regulator Binding Sites in Chip-Seq Data
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Author(s):
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Mengyuan Xu*+ and Leping Li and Clarice Weinberg and David Umbach
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Companies:
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National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences and National Institute of Environmental Health Sciences
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Address:
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111 TW Alexander Dr, RTP, NC, 27709,
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Keywords:
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mixture model ;
missing data ;
Em-algorithm
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Abstract:
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It is known that multiple transcription factors may work together to regulate gene expression in development and specification. Most existing methods for motif discovery consider only one motif at a time. Here, we present a multi-component mixture framework to model the joint distribution of two motifs. Our method uses the expectation-maximization (EM) algorithm to numerically maximize the observed data likelihood with respect to the proportions and position weight matrices of the two motifs. We are able to estimate the position weight matrices of each motif and the sequence probabilities of containing none (pure noise), one of, and both binding sites at the same time. Then we compute the posterior probabilities of any given sequence and classify it as containing none, one of, or both binding sites.
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