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Activity Number: 522 - New Statistical Methods for Emerging Linked Data and Multi-View Data
Type: Invited
Date/Time: Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
Sponsor: Biometrics Section
Abstract #309425
Title: A Linked Data Model for Decomposition of Biologically Structured Gene Expression Matrix Environments
Author(s): Huan Chen and Luo Xiao* and Carlo Colantuoni and Brian Caffo
Companies: Johns Hopkins University and North Carolina State University and Johns Hopkins University and Johns Hopkins University
Keywords: Linked data; Gene expression; Matrix decomposition; Sample covariance

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.

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

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