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Inria Associated Team COMPASSO

Coordinators: Marie-France Sagot (Erable); Susana Vinga (Instituto Superior Técnico (IST), Lisbon, Portugal).
Duration: 2018-2020

Brief description
Microbial communities are ubiquitous in nature and have major impact on every aspect of life in our planet. In spite of its importance, little is known about the principles that determine the functioning, robustness, evolution and control of such communities. The two teams that are partners of this project have some history of collaborating together. So far however, their main direct scientific concerns have been distinct in terms of final goals, while the areas of expertise are concentrated on computer science but with also some distinct characteristics. The main aim of this project is to work together towards establishing a strong link between the different application goals each team has had so far. This is an ambitious project, that will highly depend on further blending together the different expertises that each team has.

The French team has since some ten years now been highly interested in modelling and exploring species interactions. Such interactions indeed appear crucial to understand some if not all of the most fundamental evolutionary and functional questions related to living organisms. They remain however very little explored by computational biologists.

The Portuguese team on the other hand has been involved since a few years in a number of projects related mainly to cancer and rare diseases. The objective has been to develop the statistical and machine learning algorithms that would allow, using multi-omic data, to help propose personalised treatments to these diseases.

The ultimate aim of this project is to start building links between these two aspects, of species interactions and cancer/rare diseases, or more precisely, between infectious diseases and non infectious ones, whether they involve human or animals more in general. The main general questions that will be addressed are the following: (i) Are species interactions really a crucial factor on the development of at least some non infectious diseases as is suspected? (ii) If yes, could this disease be treated in a “non-aggressive” way by exploiting such species interactions? These are highly ambitious questions that will in the first three years be tackled through two angles. One concerns modelling and understanding the system biology of communities, and the second modelling and understanding the co-evolutionary aspects present in such communities. first will in fact cover both synthetic communities and natural ones.

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