Bioinformatics and Big Data Analytics

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The interplay between our genetic makeup and environmental factors plays a key role in our health and wellness. Metabolomics is the comprehensive study of small compounds (metabolome) present in a biological system. The metabolome includes both endogenous metabolites and compounds derived from food, gut microbiome, chemical exposures, etc., representing the final products of complex gene-environment-microbiome (GEM) interactions. Global metabolomics based on high-resolution mass spectrometry (HRMS) is increasingly applied together with next-generation sequencing technologies to understand complex GEM interactions, with great promise to transform medicine, public and environmental health. The central theme of Dr. Xia's research is to develop powerful yet highly accessible bioinformatics solutions to address the current big data challenges in metabolomics, microbiomics and multi-omics. The main research objective in the next five years is to develop, validate and apply high-throughput and sensitive metabolomic activity analysis and suspect screening based on HRMS systems, and to integrate global metabolomics with other omics data for systems insights. In particular, his team will 1) integrate data-driven and knowledge-driven approaches to enable fast and sensitive global metabolomics; 2) develop scalable approaches for exposomics and multi-omics data analysis and visualization; and 3) leverage the latest digital technologies to streamline and democratize big data analytics. These solutions will empower many researchers to obtain deep insights to inform the development of better treatment strategies and to improve public and environmental health.