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.
EMBL is committed to sharing research advances and sustaining scientific interaction throughout the coronavirus pandemic. We are delighted to announce that this conference is going virtual and invite you to join us online.
Advances in genome sequencing and gene editing tools are providing unprecedented insights into biological mechanisms and evolutionary processes. In parallel, computational and theoretical approaches are providing new insights into our understanding of these new data. A goal for this conference is to unite people across theoretical and experimental backgrounds into a coherent focus on “predicting evolution.”
The conference will explore the evolution of biological systems at different levels: from genes and molecules to organism development and ecology. As such, we have invited leaders in their respective fields across various scales of evolution: molecular, network, microbial, developmental, and community. Particular emphasis for this conference will be placed on understanding evolution through mechanistic biology. We will explore recent advances in experimental and theoretical approaches to study how genetic and non-genetic changes drive and constrain evolution. The meeting will offer a training ground and productive learning experience for attendees, and provide networking opportunities for scientists across disciplines relevant to evolutionary biology. It should be of particular interest to those working at the interface of evolution, quantitative genetics, development, and systems biology.
- Predicting the evolution of molecules
- Predicting regulatory network evolution
- Predicting microbial evolution
- Prediction population evolution
- Predicting community evolution