Estimating Biological Networks from High-Dimensional Omics Data

• Activity Number: 263 - Introductory Overview Lecture: Network Data, Modeling, Analysis, and Applications
• Type: Invited
• Date/Time: Tuesday, August 1, 2017 : 8:30 AM to 10:20 AM
• Sponsor: JSM Partner Societies
• Author(s): George Michailidis*
• Companies: University of Florida

Abstract

Biological networks capture important information regarding various interactions -e.g. signaling, regulation- amongst biomolecules that are critical in furthering our understanding of biological mechanisms, as well as onset and disease progression. The advent of high-throughput Omics technologies has enabled researchers to use such data to estimate these large-scale interactions networks and complement approaches that utilize carefully designed experiments for uncovering specific interactions. In this talk, we provide a broad overview of the topic discussing different types of biological interaction networks and statistical techniques to estimate them from high-dimensional Omics data. We also address how to utilize prior biological information for improved estimation, as well as the problem of joint estimation of interaction networks across similar disease subtypes. We conclude with some remarks on network based integration of multi-modal Omics data.