Author

Nicolas Portal

Centre National de la Recherche ScientifiqueORCID 0009-0002-5772-7684Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:graph neural network· 1

Frequent Co-Authors

Massimiliano BonomiiD· 2 shared Vincent MalletiD· 1 shared Vincent SchnapkaiD· 1 shared Wissam KarrouchaiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersBioinformatics

Massimiliano BonomiORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 11, 2026

Leveraging state-of-the-art AI structure predictors to generate atomic resolution ensembles of intrinsically disordered proteins

Vincent Schnapka, Nicolas Portal, Massimiliano Bonomi

The paper extends a framework to generate atomic resolution ensembles of intrinsically disordered proteins using six AI structure predictors and compares their performance against experimental data and simulations.

DOI 10.64898/2026.11.10.765624

protein structuredeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 14, 2026

✦ In-depth digest

Learning Dynamic Protein Representations at Scale with Distograms

Nicolas Portal, Wissam Karroucha, Vincent Mallet, Massimiliano Bonomi

Adding Boltz2 distogram edges and features to protein and RNA graph networks beats MD-correlation graphs on binding tasks and improves stability, interaction and RNA predictions without simulation.

2 citations

protein structuregraph neural network

𝕏 PostBluesky