← back to search

Gilles Marcou

Institut de Chimie · FR
Area of research
Computational Theory and Mathematics · Spectroscopy
Research interest
Research interests include Computational Drug Discovery Methods, Analytical Chemistry and Chromatography, Machine Learning in Materials Science, and Metabolomics and Mass Spectrometry Studies.
h-index
36
citations
5,391
works
222
NIH funding
primary concept
email

Recent publications

Current Insights on Skin Permeability Data and Quantitative Structure-Property Relationship Modeling.
2026cited by 0position: contributordoi
Machine Learning-Based Thermodynamic Modeling of Acid Gas Absorption in Aqueous Methyldiethanolamine and Aqueous Piperazine.
2026cited by 0position: contributordoi
Design of Highly Potent Antibiofilm, Antimicrobial Peptides Using Explainable Artificial Intelligence.
2026cited by 0position: contributordoi
From High Dimensions to Human Insight: Exploring Dimensionality Reduction for Chemical Space Visualization.
2025cited by 21position: contributordoi
What Works, What Doesn't, and Why? An Industrial Perspective on Absorption Modeling.
2025cited by 1position: contributordoi
Spherical GTM: A New Proposition for Visualization of Chemical Data.
2025cited by 0position: contributordoi
Harnessing Medicinal Chemical Intuition from Collective Intelligence.
2025cited by 0position: contributordoi
Will we ever be able to accurately predict solubility?
2024cited by 27position: contributordoi
An update of skin permeability data based on a systematic review of recent research.
2024cited by 26position: contributordoi
A community effort in SARS-CoV-2 drug discovery.
2024cited by 14position: contributordoi
Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.
2024cited by 5position: contributordoi
The freedom space - a new set of commercially available molecules for hit discovery.
2024cited by 4position: contributordoi
An affordable, programmable and interactive continuous flow Photoreactor setup for undergraduate organic synthetic teaching labs
Journal of Flow Chemistry 2024cited by 3position: middledoi
Kinetic solubility: Experimental and machine-learning modeling perspectives.
2024cited by 2position: contributordoi
Implementation of a soft grading system for chemistry in a Moodle plugin: reaction handling.
2024cited by 0position: contributordoi
GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.
2023cited by 17position: contributordoi
Chemical Library Space: Definition and DNA-Encoded Library Comparison Study Case.
2023cited by 8position: contributordoi
Meta-GTM: Visualization and Analysis of the Chemical Library Space.
2023cited by 6position: contributordoi
French dispatch: GTM-based analysis of the Chimiothèque Nationale Chemical Space.
2023cited by 2position: contributordoi
Predicting S. aureus antimicrobial resistance with interpretable genomic space maps
2023cited by 0position: contributordoi
A Close-up Look at the Chemical Space of Commercially Available Building Blocks for Medicinal Chemistry.
2022cited by 62position: contributordoi
SynthI: A New Open-Source Tool for Synthon-Based Library Design.
2022cited by 19position: contributordoi
Computational screening methodology identifies effective solvents for CO<sub>2</sub> capture.
2022cited by 16position: contributordoi
Exploration of the Chemical Space of DNA-encoded Libraries.
2022cited by 14position: contributordoi
Comprehensive analysis of commercial fragment libraries.
2022cited by 14position: contributordoi
Chemspace Atlas: Multiscale Chemography of Ultralarge Libraries for Drug Discovery.
2022cited by 13position: contributordoi
Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera.
2022cited by 10position: contributordoi
HIV-1 drug resistance profiling using amino acid sequence space cartography.
2022cited by 8position: contributordoi
Inverse QSAR: Reversing Descriptor-Driven Prediction Pipeline Using Attention-Based Conditional Variational Autoencoder.
2022cited by 6position: contributordoi
Molecular Similarity Perception Based on Machine-Learning Models.
2022cited by 5position: contributordoi

Grants

No grants ingested yet.

Frequent collaborators

Alexandre Varnek · Chimie de la Matière Complexe48 papers (2019–2026) · 35 papers (2019–2026)Dragos Horvath · Chimie Moléculaire, Macromoléculaire, Matériaux25 papers (2019–2026)Igor I. Baskin · Technion – Israel Institute of Technology6 papers (2019–2022)E. Van Miert · Institut des Arts de Diffusion4 papers (2020–2021)P. Azam · Solvay (France)4 papers (2020–2021)A. D. Biswas · Dompé (Italy)4 papers (2020–2021)M.H. Enrici · AFSSET3 papers (2020–2021)Alexey Orlov · Skolkovo Institute of Science and Technology3 papers (2021–2026)Serhiy V. Ryabukhin · American Chemical Society3 papers (2022–2022)Zhongyu Wang · Kunming University of Science and Technology2 papers (2020–2021)Yurii Moroz · John Wiley & Sons (United States)2 papers (2022–2024)Petra Hellwig · American Chemical Society2 papers (2019–2022)Frédérick de Meyer · American Chemical Society2 papers (2022–2026)Claire Minoletti · Sanofi (France)2 papers (2025–2025)Tagir Akhmetshin · Hokkaido University2 papers (2025–2026)Fanny Bonachera · Centre National de la Recherche Scientifique2 papers (2021–2024)Youssef El Khoury · Public Library of Science2 papers (2019–2022)Alexander Tropsha · University of Toronto2 papers (2020–2021)Ayikoé-Guy Mensah-Nyagan · Elsevier, Inc.2 papers (2019–2022)