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Physical and evolutionary bases of computation in living organisms

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Even unicellular organisms such as bacteria perform a large array of "computations’’ to go through their cell cycle and adapt to changing environmental conditions. These biological computations certainly differ from those of digital computers, but despite spectacular advances in our capacity to characterize and modify many of the underlying molecular processes, we are still far from understanding their principles.

We combine evolutionary and physical approaches to tackle this problem. The evolutionary approach compares different species to identify their common principles. The availability of large and quantitative datasets allows us to do this statistically at the level of complete cells. The results of this approach point towards elementary physical mechanisms that we intend to model mathematically and numerically. The models will be based on notions of statistical mechanics and will mainly describe the interactions between two molecules : the DNA that carries the genetic information and the RNA polymerase that transcribes it.

The objective of the internship is to build and study these models, assess their relevance in light of available data and eventually propose experiments to test them. A good knowledge in statistical physics is required but no prior background in biology is needed if the student has the interest and motivation to learn the subject.

Contacts :

Olivier Rivoire

Ivan Junier