Author

JianJun Tao

Centre National de la Recherche Scientifique

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Biophysics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1 Research Focus:software / tool· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Alaa RegueiiD· 1 shared Antoine TalyiD· 1 shared Beatrice CavigliaiD· 1 shared Carine TisnéiD· 1 shared Chantal PrévostiD· 1 shared Élise Duboué-DijoniD· 1 shared Fabrice LeclerciD· 1 shared Jules MarieniD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBiophysics

Alaa RegueiORCID

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

Deep-learning predictions of biomolecular structures : persistent limitations and new horizons extended by explicit ion addition

Jules Marien, Sujith Sritharan, Beatrice Caviglia, Raphaëlle Versini, Lucas Auclair, Pierre Barraud, Carine Tisné, Alaa Reguei, Samuel Murail, Fabrice Leclerc, Élise Duboué-Dijon, JianJun Tao, Nathalie Basdevant, Marc Baaden, Chantal Prévost, , Antoine Taly

This paper evaluates limitations of deep learning in biomolecular structure prediction, highlighting the benefits of explicit ion modeling for improving conformational accuracy.

bioRxiv · Jul 26, 2026 · PreprintBiophysics