José Jiménez-Luna

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Gianni De FabritiisComputational Science Laboratory, Icrea Research Professor, Acellera twitter:@gdefabritiisVerified email at upf.edu
Miha SkalicBoehringer IngelheimVerified email at boehringer-ingelheim.com
Gisbert SchneiderETH ZurichVerified email at ethz.ch
Francesca GrisoniAssistant Professor, Molecular Machine Learning at Eindhoven University of TechnologyVerified email at tue.nl
Stefan DoerrAcellera LtdVerified email at upf.edu
Davide SabbadinRoivant SciencesVerified email at roivant.com
Kenneth AtzAI Scientist at Roche | PhD AI/ML ETH ZürichVerified email at ethz.ch
Clemens IsertAI Scientist @ VantAIVerified email at vant.ai
Gary TresadernComputational chemistry, Janssen R&D, Pharmaceutical companies of Johnson and JohnsonVerified email at its.jnj.com
Laura Perez-BenitoSenior Scientist Computational Chemistry JanssenVerified email at its.jnj.com
Rıza ÖzçelikPh.D. Candidate, Biomedical Engineering, Eindhoven University of TechnologyVerified email at tue.nl
Derek van TilborgEindhoven University of TechnologyVerified email at tue.nl
Josep GinebraPolytechnic University of CataloniaVerified email at upc.edu
Andrew CampbellPhD Student, University of OxfordVerified email at stats.ox.ac.uk
Noe FrankMicrosoft ResearchVerified email at fu-berlin.de
Bastiaan S. VeelingMicrosoft Research AmsterdamVerified email at uva.nl
Victor Garcia SatorrasUniversity of AmsterdamVerified email at uva.nl
Michael GasteggerMicrosoft Research AI4ScienceVerified email at microsoft.com
Andrew Y. K. FoongSenior Researcher, Microsoft ResearchVerified email at microsoft.com
Oh-Hyeon ChoungComputational Neuroscientist, Ph.D., EPFLVerified email at epfl.ch

José Jiménez-Luna

Other namesJose Jimenez

Microsoft Research

Verified email at microsoft.com - Homepage

AI4Science Structural Biology Chemoinformatics Explainable AI


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KDEEP: Protein-ligand absolute binding affinity prediction via 3D-convolutional neural networks. J Jiménez, M Skalic, G Martinez-Rosell, G De Fabritiis Journal of chemical information and modeling 58 (2), 287–296, 2018	761	2018
Drug discovery with explainable artificial intelligence J Jiménez-Luna, F Grisoni, G Schneider Nature Machine Intelligence 2 (10), 573-584, 2020	592	2020
DeepSite: Protein binding site predictor using 3D-convolutional neural networks J Jiménez, S Doerr, G Martínez-Rosell, AS Rose, G De Fabritiis Bioinformatics 33 (19), 3036–3042, 2017	511	2017
Shape-based generative modeling for de novo drug design M Skalic, J Jiménez, D Sabbadin, G De Fabritiis Journal of chemical information and modeling 59 (3), 1205-1214, 2019	211	2019
Artificial intelligence in drug discovery: recent advances and future perspectives J Jiménez-Luna, F Grisoni, N Weskamp, G Schneider Expert opinion on drug discovery 16 (9), 949-959, 2021	184	2021
Coloring Molecules with Explainable Artificial Intelligence for Preclinical Relevance Assessment J Jimenez-Luna, M Skalic, N Weskamp, G Schneider Journal of chemical information and modeling 61 (3), 1083-1094, 2021	67	2021
LigVoxel: inpainting binding pockets using 3D-convolutional neural networks M Skalic, A Varela-Rial, J Jiménez, G Martínez-Rosell, G De Fabritiis Bioinformatics 35 (2), 243-250, 2019	66	2019
DeltaDelta neural networks for lead optimization of small molecule potency J Jiménez-Luna, L Pérez-Benito, G Martinez-Rosell, S Sciabola, R Torella, ... Chemical science 10 (47), 10911-10918, 2019	61	2019
QMugs, quantum mechanical properties of drug-like molecules C Isert, K Atz, J Jiménez-Luna, G Schneider Scientific Data 9 (1), 273, 2022	59	2022
PlayMolecule BindScope: large scale CNN-based virtual screening on the web M Skalic, G Martínez-Rosell, J Jiménez, G De Fabritiis Bioinformatics 35 (7), 1237-1238, 2019	55	2019
pyGPGO: Bayesian Optimization for Python J Jiménez, J Ginebra Journal of Open Source Software 2 (19), 431, 2017	45	2017
Δ-Quantum machine-learning for medicinal chemistry K Atz, C Isert, MNA Böcker, J Jiménez-Luna, G Schneider Physical Chemistry Chemical Physics 24 (18), 10775-10783, 2022	33	2022
PathwayMap: molecular pathway association with self-normalizing neural networks J Jimenez, D Sabbadin, A Cuzzolin, G Martinez-Rosell, J Gora, ... Journal of chemical information and modeling 59 (3), 1172-1181, 2018	28	2018
Benchmarking molecular feature attribution methods with activity cliffs J Jiménez-Luna, M Skalic, N Weskamp Journal of Chemical Information and Modeling 62 (2), 274-283, 2022	22	2022
Structure‐Based Drug Discovery with Deep Learning R Özçelik, D van Tilborg, J Jiménez‐Luna, F Grisoni ChemBioChem 24 (13), e202200776, 2023	20	2023
A deep-learning approach toward rational molecular docking protocol selection J Jiménez-Luna, A Cuzzolin, G Bolcato, M Sturlese, S Moro Molecules 25 (11), 2487, 2020	19	2020
PlayMolecule glimpse: Understanding protein–ligand property predictions with interpretable neural networks A Varela-Rial, I Maryanow, M Majewski, S Doerr, N Schapin, ... Journal of chemical information and modeling 62 (2), 225-231, 2022	12	2022
Fast protein backbone generation with SE (3) flow matching J Yim, A Campbell, AYK Foong, M Gastegger, J Jiménez-Luna, S Lewis, ... arXiv preprint arXiv:2310.05297, 2023	8	2023
Extracting medicinal chemistry intuition via preference machine learning OH Choung, R Vianello, M Segler, N Stiefl, J Jiménez-Luna Nature Communications 14 (1), 6651, 2023	7*	2023
Explaining compound activity predictions with a substructure-aware loss for graph neural networks K Amara, R Rodríguez-Pérez, J Jiménez-Luna Journal of cheminformatics 15 (1), 67, 2023	3	2023

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