Weizmann Institute of Science
The Weizmann Institute of Science (WIS), located in Rehovot, Israel, is one of the top-ranking multidisciplinary research institutions in the world. Noted for its wide-ranging exploration of the sciences and technology, the Institute gathers together over 240 research laboratories focused on biological sciences, chemistry, physics, mathematics, and computer sciences, with over 2,500 scientists, technicians, and research students. Leading researchers at the Weizmann Institute have been awarded the Turing, Wolf and Nobel prizes for their accomplishments. The institute's long history has positioned it at the forefront of scientific research in multiple disciplines.
Of most relevance to this proposal, Weizmann is widely recognized as an international leader in the area of systems and computational biology. The Weizmann team is leading the development of single-cell multiomics for large patient cohorts (10k and others) to define the genes, pathways, and biomarkers associated with immune dysfunction with the goal of developing the next frontiers of immunotherapies.
Role within miGut-Health
In the miGut-Health project, the Weizmann Institute of Science (WIS), led by Principal Investigator Eran Segal, plays a crucial role in Work Package 4 (WP4) focusing on systems-level biology analysis of gut health. WIS will employ a comprehensive computational pipeline to generate a broad set of bacterial features, including bacterial abundances, diversity, growth rates, gene and biological pathway abundances, SNPs, structural variations, and bacterial strain abundances. The institute will also continue developing methods to address the high similarity between bacterial genomes, using algorithms such as expectation-minimization (EM) for strain differentiation. WIS's expertise in advanced statistical methods, probabilistic models, thermodynamic models, and machine learning will be leveraged to analyze metagenomic samples, compute bacterial growth rates, determine gene abundances, and evaluate biological pathway abundances. Additionally, WIS will conduct metagenome-wide association studies (MWAS) to identify associations between microbiome features and inflammatory bowel disease (IBD) parameters. The aim is to develop predictive models for IBD risk using machine learning techniques and to discover new biomarkers for disease risk and progression through deep molecular phenotypic profiling.
