José Jiménez-Luna

Universidad de Oriente — CU

Computer Science · Physical Sciences

22h-index3.5kcitations66works35.22yr avg
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Research Topics

Computational Drug Discovery Methods(41), Machine Learning in Materials Science(35), Protein Structure and Dynamics(18), Media and Digital Communication(7), Cosmology and Gravitation Theories(4)

Publications66 total

Evaluación del riesgo ergonómico en los trabajadores de Romero´s y Asociados de la ciudad de Guayaquil, 2025
LATAM Revista Latinoamericana de Ciencias Sociales y Humanidades·2025Open Access
Scalable emulation of protein equilibrium ensembles with generative deep learning
Science·2025· 112 cited
Deep Learning Models for Automatic Morphological Evaluation of Endothelial Cells
World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany·2025
Scalable emulation of protein equilibrium ensembles with generative deep learning
2024· 56 citedOpen Access
Improved motif-scaffolding with SE(3) flow matching
PubMed·2024· 8 citedOpen Access
Extracting medicinal chemistry intuition via preference machine learning
Nature Communications·2023· 31 citedOpen Access
Fast protein backbone generation with SE(3) flow matching
arXiv (Cornell University)·2023· 21 citedOpen Access
Explaining compound activity predictions with a substructure-aware loss for graph neural networks
Journal of Cheminformatics·2023· 16 citedOpen Access
Explaining compound activity predictions witha substructure-aware loss for graph neuralnetworks
2023· 1 citedOpen Access
Structure‐Based Drug Discovery with Deep Learning**
ChemBioChem·2023· 58 citedOpen Access
Learning chemical intuition from humans in the loop
2023Open Access
Learning chemical intuition from humans in the loop
2023· 4 citedOpen Access
Explaining compound activity predictions witha substructure-aware loss for graph neuralnetworks
2023Open Access
Structure-based drug discovery with deep learning
arXiv (Cornell University)·2022· 4 citedOpen Access
A substructure-aware loss for feature attribution in drug discovery
2022· 2 citedOpen Access
A substructure-aware loss for feature attribution in drug discovery
2022Open Access
QMugs, quantum mechanical properties of drug-like molecules
Scientific Data·2022· 130 citedOpen Access
Benchmarking Molecular Feature Attribution Methods with Activity Cliffs
Journal of Chemical Information and Modeling·2022· 36 cited
PlayMolecule Glimpse: Understanding Protein–Ligand Property Predictions with Interpretable Neural Networks
Journal of Chemical Information and Modeling·2022· 30 citedOpen Access
Δ-Quantum machine-learning for medicinal chemistry
Physical Chemistry Chemical Physics·2022· 54 citedOpen Access
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Frequent Co-authors

Gisbert Schneider(11), Gianni De Fabritiis(10), Miha Škalič(9), Gerard Martínez-Rosell(8), Clemens Isert(7), Kenneth Atz(7), Nils Weskamp(6), L. Herrera(5), Francesca Grisoni(4), Michael Gastegger(4), Andrew Y. K. Foong(4), Victor García Satorras(4), Bastiaan S. Veeling(4), Andrew M. Campbell(4), Jason Yim(4), Frank Noé(4), Markus N. A. Böcker(4), Laura Pérez‐Benito(3), Simone Sciabola(3), Rubben Torella(3)