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EMBL Courses and Conferences during the Coronavirus pandemic
With the onsite programme paused, many of our events are now being offered in virtual formats.
Registration is open as usual for many events, with back-up plans in place to move further courses and conferences online as necessary. Registration fees for any events affected by the COVID-19 disruption are fully refundable.
More information for participants of events at EMBL Heidelberg can be found here.
The course will introduce state-of-the art modelling and experimental tools for discovering and analysing species interactions in microbial communities, with a particular focus on metabolic dependencies.
The course will run over a period of five days, each day divided between a morning session with theory and an afternoon session with practical work. In the morning session, a leading expert in the field presents background information, key concepts and computational/experimental methods. This lecture module is followed by a meet the speaker coffee break. The concepts are then introduced in more detail by the speaker or by one of the organizing instructors. Afternoon sessions, supervised by the instructors and teaching assistants, are dedicated to extensive practical work in wet as well as dry lab.
The faculty’s expertise includes constrained based modelling, spatio-temporal dynamics, metagenomics, highthroughput phenotyping and metabolomics.
The course is tailored for PhD students and post-docs with interest in analysing species interactions in natural or synthetic microbial communities. We expect both biologists interested in learning/using modelling and mathematicians/physicists/computer scientists with little biology exposure. Attendance is limited to 20 and the teacher-student ratio is excellent.
The modelling component will cover constraint-based steady-state models as well as dynamic models. Experimental techniques will include high-throughput interaction mapping and metabolomics.
The unique combination of wet-lab experiments with mathematical modelling will give the participants an all-round exposure to key methods required to go from hypothesis to the bench and back. The course will further provide a platform for discussion of the key questions and challenges in the field, and improve communication between the bench and computational scientists.