Jan H. Jensen

University of Copenhagen — Denmark

Computer Science · Physical Sciences

56h-index41.6kcitations326works5.12yr avg
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Research Topics

Computational Drug Discovery Methods(79), Machine Learning in Materials Science(58), Advanced Chemical Physics Studies(44), Protein Structure and Dynamics(43), Free Radicals and Antioxidants(38)

Publications326 total

CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2
Journal of Chemical Information and Modeling·2026Open Access
Computational prediction of C-H hydricities and their use in predicting the regioselectivity of electron rich C-H functionalisation reactions
2025Open Access
CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson’s Disease Associated Protein
UNC Libraries·2025Open Access
CACHE Challenge #3: Targeting the Nsp3 Macrodomain of SARS-CoV-2
2025Open Access
Finding Drug Candidate Hits With A Hundred Samples: Ultralow Data Screening With Active Learning
ChemistryEurope·2025Open Access
CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13
Journal of Chemical Information and Modeling·2025· 8 citedOpen Access
Enhancing chemical synthesis planning: automated quantum mechanics-based regioselectivity prediction for C–H activation with directing groups
Beilstein Journal of Organic Chemistry·2025· 1 citedOpen Access
SMILES all around: structure to SMILES conversion for transition metal complexes
Journal of Cheminformatics·2025· 11 citedOpen Access
A Deep Generative Model for the Inverse Design of Transition Metal Ligands and Complexes
JACS Au·2025· 22 citedOpen Access
Finding Drug Candidate Hits With a Hundred Samples: Ultra-low Data Screening With Active Learning
2025Open Access
The need to implement FAIR principles in biomolecular simulations
Nature Methods·2025· 38 citedOpen Access
CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13
2025Open Access
CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13
2025· 2 citedOpen Access
CACHE Challenge #2: Targeting the RNA Site of the SARS-CoV-2 Helicase Nsp13
2025· 1 citedOpen Access
A Deep Generative Model for the Inverse Design of Transition Metal Ligands and Complexes
2025Open Access
Author response for "Atom-Based Machine Learning for Estimating Nucleophilicity and Electrophilicity with Applications to Retrosynthesis and Chemical Stability"
2025
Enhancing Chemical Synthesis Planning: Automated Quantum Mechanics-Based Regioselectivity Prediction for C-H Activation with Directing Groups
2025· 1 citedOpen Access
Beyond predefined ligand libraries: a genetic algorithm approach for <i>de novo</i> discovery of catalysts for the Suzuki coupling reactions
PeerJ Physical Chemistry·2025· 5 citedOpen Access
Atom-based machine learning for estimating nucleophilicity and electrophilicity with applications to retrosynthesis and chemical stability
Chemical Science·2025· 4 citedOpen Access
SMILES All Around: Structure to SMILES conversion for Transition Metal Complexes
2024· 3 citedOpen Access
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Frequent Co-authors

Mark S. Gordon(15), Andrew D. Robertson(4), Dmitri G. Fedorov(4), Mats H. M. Olsson(3), Chresten R. Søndergaard(3), Michał Rostkowski(3), Visvaldas Kairys(3), Walter J. Stevens(3), Hui Li(3), Jonas Baltrušaitis(3), Vicki H. Grassian(3), Kazuo Kitaura(3), Hui Li(3), Casper Steinmann(3), Jimmy Kromann(3), Kim K. Baldridge(2), Mark A. Freitag(2), Simon P. Webb(2), Hui Li(2), Jennifer D. Schuttlefield(2)