Next Monday, 20 March at 11:30, we will have the pleasure to listen to Jean-Loup Faulon (Micalis, INRA) who will discuss his recent work on information processing in living and synthetic systems. You may join in the Gulliver library, or remotely at the zoom link following the abstract below.
Remote connection details
https://us02web.zoom.us/j/81716487543?pwd=c1IrZWYzTEhvaFFBZmtIK3Z6SmZRUT09 ID de réunion : 817 1648 7543 Code secret : 712938
In vitro and in vivo neural computations with metabolism
Engineering information processing devices in living systems is a long-standing venture of synthetic biology. Yet, the problem of engineering devices that perform basic operations found in machine learning remains largely unexplored. I will first present the in vitro (cell-free) engineering of enzyme catalyzed perceptrons. The performances of the perceptrons will be exemplified with biological samples classification based on their metabolic, protein and RNA compositions. With the goal of engineering in vivo learning devices, I will next show how hybrid mechanistic-neural models can perfectly surrogate classical constraint-based modelling, and make metabolic networks suitable for backpropagation and consequently be used as an architecture for machine learning. The performance of the hybrid models, trained with experimental datasets of E. coli growth rates in different media composition and different gene knockouts, will be showcased on cross-validation sets.
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