COMPUTATIONAL AND INTEGRATIVE OMICS APPROACHES TO STUDY THE EFFECT OF PERTURBATIONS ON METABOLIC PHENOTYPES

Abstract

ORGANISMS RESPOND TO GENETIC OR ENVIRONMENTAL PERTURBATIONS BY MODULATING THEIR CELLULAR METABOLISM. CHANGES TO THESE METABOLIC PROCESSES ARE ELICITED THROUGH THE REGULATION OF GENE, PROTEIN AND METABOLITE LEVELS. METABOLITES THAT ARE INTERMEDIATES OR END-PRODUCTS OF THESE REGULATORY PROCESSES, CAN BE REGARDED AS THE ULTIMATE BIOCHEMICAL PHENOTYPE OF A CELLULAR SYSTEM. ANALYSIS OF METABOLOMICS DATA IN COMBINATION WITH OTHER OMICS OR METADATA CAN PROVIDE VITAL INSIGHTS ON HOW GENETIC INFORMATION AND ENVIRONMENTAL FACTORS CAN INFLUENCE THESE PROCESSES. WITH THIS OBJECTIVE, I HAVE DEVELOPED DATA ANALYSIS STRATEGIES FOR (I) IDENTIFYING AND REMOVING NON-BIOLOGICAL SOURCES OF VARIATION IN UNTARGETED METABOLOME SURVEYS USING MULTIVARIATE STATISTICAL TECHNIQUES; (II) ANALYZING NATURAL VARIATION IN METABOLIC PROFILES OF OLEAGINOUS MICROALGAE- CHLORELLA, BY INVESTIGATING STRAIN-SPECIFIC METABOLIC REPROGRAMMING STRATEGIES AND THEIR ASSOCIATIONS WITH PHYSIOCHEMICAL MEASUREMENTS; (III) UNDERSTANDI