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A fork of Deep learning VAE DeepSEM from https://github.com/HantaoShu/DeepSEM.git at 18/03/2024. The idea here is to change the code to be able to extract the models and make goodness of fit with predicted expression

Semi-supervised learning with pseudo-labeling for regulatory sequence prediction

Implementation of the deterministic model of the intestinal including microbiota, as described in Darrigade et al., 'A PDMP model of the epithelial cell turn-over in the intestinal crypt including microbiota-derived regulations.' (2021).

fichiers de support pour EDO Sys Dyn - MAM3 EPU Nice Sophia

On-line doctoral training on EMULSION

Comparative analysis of NLP neural methods for the entity normalization task in the biological field.

Fichiers de la formation Python, Inra de Bourgogne Franche-Compté. Formateur : Arnaud Mounier.

https://lisc.pages.mia.inra.fr/geopat/

Spatial multi-objectives optimization tool for identifying compatibles cultural scenarios for the "Projet Alimentaire Territorial" Grand-Clermont/PNR-Livradois-Forez.

Explores a neo4j database according to some application logic

Contribution à la réalisation du "pilote" INRAE, dans le cadre du programme européen GraspOS

Modifications of GTNash for code readability - readability is entirely subjective! The original functionality should remain the same.

Automatic protocol for the constitution of spatio-temporal and thematic corpora for the Herelles project.