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Activity Number:
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522
- New Statistical Methods for Emerging Linked Data and Multi-View Data
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Type:
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Invited
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Date/Time:
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Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
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Sponsor:
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Biometrics Section
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Abstract #309425
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Title:
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A Linked Data Model for Decomposition of Biologically Structured Gene Expression Matrix Environments
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Author(s):
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Huan Chen and Luo Xiao* and Carlo Colantuoni and Brian Caffo
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Companies:
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Johns Hopkins University and North Carolina State University and Johns Hopkins University and Johns Hopkins University
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Keywords:
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Linked data;
Gene expression;
Matrix decomposition;
Sample covariance
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Abstract:
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We propose a structured linked data model for the decomposition of biologically structured gene expression matrix environments to elucidate conserved and unique molecular dynamics across diverse biological and technological systems. A novel statistical estimation method is proposed to circumvent challenges in existing approaches.
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Authors who are presenting talks have a * after their name.
