Author

Roberto Tejero

Universitat de ValènciaORCID 0000-0003-2504-5988Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Research Focus:database / resource· 2 Assay:protein structure· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Gaetano Thomas MontelioneiD· 3 shared Theresa A. RamelotiD· 3 shared Benjamin BardiauxiD· 2 shared Charles D. SchwietersiD· 2 shared Eliza PłoskońiD· 2 shared Ezra PeisachiD· 2 shared Geerten W. VuisteriD· 2 shared Genji KurisuiD· 2 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Gaetano Thomas MontelioneORCID

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3 papers

Recent·Most cited

BiochemistrybioRxivPreprintApr 24, 2026

The NMR Exchange Format (NEF): Specification and Applications

Eliza Płoskoń, Kumaran Baskaran, Roberto Tejero…·Geerten W. Vuister

The paper introduces NEF, a standard for NMR data exchange, and demonstrates its application in structure determination, metabolomics, and ligand screening.

DOI 10.64898/2026.04.22.715536

experimental assaydatabase / resource

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BioinformaticsStructurePeer-reviewedMar 14, 2024

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Kumaran Baskaran, Eliza Płoskoń, Roberto Tejero…·Jasmine Y. Young

The paper develops a standardized system for validating biomolecular structures against NMR restraints using NEF and NMR-STAR formats, implemented in the wwPDB OneDep system.

9 citations

protein structurestatistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 22, 2023

Blind Assessment of Monomeric AlphaFold2 Protein Structure Models with Experimental NMR Data

Ethan H. Li, Laura E. Spaman, Roberto Tejero…·Gaetano Thomas Montelione

The paper assesses AlphaFold2 models against experimental NMR data for 9 monomeric proteins not used in training, finding they fit the data as well as or better than existing NMR structures.

6 citations

protein structuredeep learning

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