Hosted by the School of Medicine at Cardiff University

Abstract: Small compounds or metabolites are key players of host-microbiome interactions. Global untargeted metabolomics based on high-resolution mass spectrometry provides rich information on the host-microbiome co-metabolism. However, data analysis and interpretation within the context of multiple omics data sets are currently the bottleneck for microbiome researchers. In this talk, I will share our recent research work developing computational (tools and databases), analytical (LC-MS/MS metabolomics), and experimental (C. elegans-based models) approaches to help understand microbiome functions and interactions with their host.

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Dr. Jianguo Xia is an Associate Professor and Canada Research Chair (bioinformatics and big data analytics) at McGill University. His lab explores innovative and practical ways to address the current challenges in big data analytics arising from biomedical and environmental research, focusing on metabolomics, microbiomics and multi-omics integration. His group is actively developing new-generation computational framework integrating cloud computing, machine learning and visual analytics to gain deep insights into complex omics data. To date, Dr. Xia has authored >120 journal publications and 8 book chapters. He is the 2019 McGill Principal’s Prize for Outstanding Emerging Researchers. Since 2019, he has been ranked among the Global Highly Cited Researchers (citations: >44,000, H-index: 57) by the Web of Science.