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VERONIQUE STOVEN
Professor,
Professeur Mines Paris Tech
Recherche - Paris
Spécialités / domaines
Bioinformatics,
Biologie structurale
Functions within Institut Curie:
Présentation
I am a Professor at Mines-ParisTech. My research activity concerns the study of protein-ligand interactions, using computational biology approaches including docking and machine-learning technologies. The goal is to predict/understand these molecular recognition mechanisms in their functional context, or in the context of the design of drug candidates. My research also concerns the joint use of machine-learning and systems biology approaches to the study of so-called "triple negative" breast cancer (TNBC) and respiratory epithelial cells in cystic fibrosis, in order to identify new therapeutic targets.
Publications
Differential CFTR-Interactome Proximity Labeling Procedures Identify Enrichment in Multiple SLC Transporters
International Journal of Molecular Sciences
Drug Target Identification with Machine Learning: How to Choose Negative Examples
International Journal of Molecular Sciences
Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificity
Journal of Cheminformatics
Urinary Exosomes of Patients with Cystic Fibrosis Unravel CFTR-Related Renal Disease
International Journal of Molecular Sciences
LOTUS: A single- and multitask machine learning algorithm for the prediction of cancer driver genes
PLOS Computational Biology
Kernel Multitask Regression for Toxicogenetics
Molecular Informatics