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phd
- 19:00 CRI, Learning center extension

IT seminar – Machine Learning approaches to protein generation

IT seminar – Machine Learning approaches to protein generation

Speaker: Cyril Malbranke

Abstract:

The ability to predict the fitness of protein variants and to generate new proteins is a diffcult problem made challenging by the extremely large space of possible chains of amino acids and the difficulty of accurately predicting a protein fold and function from its sequence. We propose to explore novel modeling strategies to this problem. Neural generative models, have recently been successful at modeling diverse kinds of high dimensional data including text, sound and images, allowing the generation of novel realistic samples. Some of these models can also learn useful representation of the data in their latent space be conditioned to enable the controlled generation of samples with desired properties.


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