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Sign in to add trainee| Rubén Sánchez García | grad student | 2016- | Natl. Center of Biotechnology (CSIC) |
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| Segura J, Rose Y, Bi C, et al. (2023) RCSB Protein Data Bank: visualizing groups of experimentally determined PDB structures alongside computed structure models of proteins. Frontiers in Bioinformatics. 3: 1311287 |
| Mirela Bota P, Hernandez AC, Segura J, et al. (2023) CM2D3: Furnishing the human interactome with structural models of protein complexes derived by comparative modeling and docking. Journal of Molecular Biology. 168055 |
| Bittrich S, Bhikadiya C, Bi C, et al. (2023) RCSB Protein Data Bank: Efficient Searching and Simultaneous Access to One Million Computed Structure Models Alongside the PDB Structures Enabled by Architectural Advances. Journal of Molecular Biology. 167994 |
| Burley SK, Bhikadiya C, Bi C, et al. (2022) RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning. Nucleic Acids Research |
| Sanchez-Garcia R, Segura J, Maluenda D, et al. (2020) MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning. Journal of Structural Biology. 107498 |
| Morris C, Andreetto P, Banci L, et al. (2019) West-Life: A Virtual Research Environment for structural biology. Journal of Structural Biology: X. 1: 100006 |
| Segura J, Sanchez-Garcia R, Sorzano COS, et al. (2019) 3DBIONOTES v3.0: Crossing molecular and structural biology data with genomic variations. Bioinformatics (Oxford, England) |
| Sorzano COS, Jiménez A, Mota J, et al. (2019) Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy. Acta Crystallographica. Section F, Structural Biology Communications. 75: 19-32 |
| Jiménez A, Jonic S, Majtner T, et al. (2018) Validation of Electron Microscopy Initial Models via Small Angle X-Ray Scattering Curves. Bioinformatics (Oxford, England) |
| Sanchez-Garcia R, Segura J, Maluenda D, et al. (2018) , a deep learning-based approach for particle pruning in cryo-electron microscopy. Iucrj. 5: 854-865 |