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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Advancing Precision Medicine through Integrative Bioinformatics Approaches for Robust Biological Knowledge Discovery
Committee:
Dr. May Wang, BME , Advisor
Dr. Robert Butera, ECE
Dr. Omer Inan, ECE
Dr. Peng Qiu, BME
Dr. William Mahle, Emory
Abstract:
Facilitated by -omic data, precision medicine is a promising medical model that may revolutionize the quality of the current healthcare system. Currently, -omic data are being rapidly accumulated because of the advent of high-throughput -omic assays. Though challenging, abundant information embedded in these data is encouraging for the realization of precision medicine. The goal of my Ph.D. research is to address some key challenges in the process from raw -omic data to disease subgroup assignment for precision medicine, including (1) the lack of standardized bioinformatics pipelines that extract high-quality gene expression from the raw RNA sequencing data; (2) the lack of quantitative assessment of the contribution of upstream pipeline components to downstream variations in identified biomarkers and clinical endpoint prediction performance; and (3) the lack of effective strategies for integrating knowledge derived from multiple -omic data sources, either the same type or different types. This dissertation addresses these challenges through three specific aims—(1) Quality Control for Precision Medicine: to investigate and control the impact of bioinformatics pipelines on feature quality using RNA sequencing data; (2) Knowledge Discovery for Precision Medicine: to discover impactful biomarkers that facilitate disease subgroup classification using NGS data; and (3) Integrative Analysis for Precision Medicine: to integrate multi-source, multi-modal -omic data for improved disease subgroup classification.
