“A novel General Genome Interpretation Paradigm for Clinical Genetics & Plant Biology”
Daniele RAIMONDI is a senior post-doctoral fellow in Bioinformatics at the STADIUS Center for
Dynamical Systems, Signal Processing & Data Analytics at KU Leuven, with expertise on Neural
Network methods for Genome Interpretation, Clinical genetics and Plant genetics; Machine Learning,
Deep Learning; Data fusion methods for Chemoinformatics and Anti-cancer Drug discovery.
He is developing bioinformatics and deep learning approaches that combine genetic, statistic and
computational layers to better understand how mutations (variants) in genomes lead to the observed
phenotypes. GenGI consists of a data-driven framework of complex, yet biologically meaningful,
problem-specific Deep Learning (DL) models, able to combine Neural Networks architectures with
prior knowledge of biological processes directly in their architecture, with the goal to pave the way
for future Precision Medicine or Agricultural applications.
Registration : https://evento.renater.fr/survey/seminar-a-novel-gene…-3h5d3cmv
Contact: etienne.schwob@igmm.cnrs.fr
