Rubén Sánchez-García

IE University — Spain

Biochemistry, Genetics and Molecular Biology · Life Sciences

17h-index2.4kcitations120works1.92yr avg
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Research Topics

Advanced Electron Microscopy Techniques and Applications(31), Electron and X-Ray Spectroscopy Techniques(23), Computational Drug Discovery Methods(14), Immunotherapy and Immune Responses(11), Enzyme Structure and Function(11)

Publications120 total

Dataset for "MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning"
Zenodo (CERN European Organization for Nuclear Research)·2025Open Access
Structure-Activity-Relationships can be directly extracted from high-throughput crystallographic evaluation of fragment elaborations in crude reaction mixtures
2025· 1 citedOpen Access
Supervised Deep Learning for Efficient Cryo-EM Image Alignment in Drug Discovery with cryoPARES
2025Open Access
Author response: Unraveling the power of NAP-CNB’s machine learning-enhanced tumor neoantigen prediction
2025Open Access
Multi-scale structural similarity embedding search across entire proteomes
2025Open Access
Unraveling the power of NAP-CNB’s machine learning-enhanced tumor neoantigen prediction
eLife·2025Open Access
Author response: Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2025Open Access
Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2025Open Access
<i>TomoCPT</i>: a generalizable model for 3D particle detection and localization in cryo-electron tomograms
Acta Crystallographica Section D Structural Biology·2025· 3 citedOpen Access
Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
Journal of Cheminformatics·2025· 6 citedOpen Access
Expanding the scope of a catalogue search to bioisosteric fragment merges using a graph database approach
2024· 3 citedOpen Access
Unraveling the power of NAP-CNB’s machine learning-enhanced tumor neoantigen prediction
eLife·2024· 1 citedOpen Access
Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2024· 1 citedOpen Access
Author response: Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2024Open Access
Reviewer #1 (Public Review): Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2024Open Access
Reviewer #2 (Public Review): Unraveling the Power of NAP-CNB’s Machine Learning-enhanced Tumor Neoantigen Prediction
2024Open Access
CESPED: A benchmark for supervised particle pose estimation in cryo-EM
Physical Review Research·2024· 1 citedOpen Access
Mining higher-order triadic interactions
arXiv (Cornell University)·2024· 1 citedOpen Access
Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation
International Journal of Molecular Sciences·2024· 5 citedOpen Access
Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology
2024· 16 citedOpen Access
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Frequent Co-authors

Carlos Óscar S. Sorzano(28), J.M. Carazo(26), Marta Martínez(14), R. Marabini(13), Joan Segura(12), Erney Ramírez-Aportela(12), Pablo Conesa(12), David Maluenda(11), Javier Vargas(10), Laura del Caño(9), Charlotte M. Deane(9), David Střelák(8), E. Fernández-Giménez(8), José Luis Vilas(7), Roberto Melero(7), José Ramón Macías(7), F. von Delft(7), Ana Cuervo(6), David Herreros(6), Amaya Jiménez-Moreno(6)