Bioinformatics and Big Data Analytics

生物信息学和大数据分析

• 批准号: CRC-2021-00259
• 负责人: Xia, Jianguo
• 金额: $ 7.29万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=757578
• 关键词: Bioinformatics; Big; Data; Analytics

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.

我们的基因组成和环境因素之间的相互作用在我们的健康和保健中起着关键作用。代谢组学是对生物系统中存在的小化合物（代谢组）的综合研究。代谢物组包括内源性代谢物和来源于食物、肠道微生物组、化学暴露等的化合物，代表复杂的基因-环境-微生物组（GEM）相互作用的最终产物。基于高分辨率质谱（HRMS）的全球代谢组学越来越多地与下一代测序技术一起应用，以了解复杂的GEM相互作用，并有望改变医学，公共和环境健康。夏博士研究的中心主题是开发强大而高度可访问的生物信息学解决方案，以解决代谢组学，微生物组学和多组学中当前的大数据挑战。未来五年的主要研究目标是开发，验证和应用基于HRMS系统的高通量和灵敏的代谢组学活性分析和可疑筛选，并将全球代谢组学与其他组学数据整合，以获得系统见解。特别是，他的团队将1）整合数据驱动和知识驱动的方法，以实现快速和敏感的全球代谢组学; 2）开发可扩展的方法，用于代谢组学和多组学数据分析和可视化; 3）利用最新的数字技术简化和民主化大数据分析。这些解决方案将使许多研究人员获得深入的见解，为制定更好的治疗策略提供信息，并改善公众和环境健康。