Author

Nicolás S. González Foutel

Aarhus UniversityORCID 0000-0002-1579-1699Unclaimed 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· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

A. Keith DunkeriD· 1 shared Ágnes TantosiD· 1 shared Alexander Miguel MonzóniD· 1 shared Alok K. SharmaiD· 1 shared Anastasia ChasapiiD· 1 shared András HatosiD· 1 shared Andrey V. KajavaiD· 1 shared Ankush GargiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

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10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

A. Keith DunkerORCID

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2 papers

Recent·Most cited

Slow diffusion limits phosphorylation in a biomolecular condensate

Nicolás S. González Foutel, Ankush Garg, Evi Setiani Lande, Assia Khalild, Line Mørkholt Lund, Victoria Birkedal, Chloé Martens, Magnus Kjærgaard

The paper shows that slow diffusion in biomolecular condensates limits phosphorylation kinetics, with phosphorylation rates strongly correlated to substrate diffusion coefficients.

bioRxiv · Feb 2, 2026 · PreprintBiophysics

Critical Assessment of Protein Intrinsic Disorder Prediction

Marco Necci, Damiano Piovesan, CAID Predictors, Md Tamjidul Hoque, Ian Walsh, Sumaiya Iqbal, Michele Vendruscolo, Pietro Sormanni, Chen Wang, Daniele Raimondi, Ronesh Sharma, Yaoqi Zhou, Thomas Litfin, Oxana V. Galzitskaya, Michail Yu. Lobanov, , Silvio C. E. Tosatto

The paper evaluates 43 methods for predicting intrinsically disordered regions and binding regions in proteins, finding that deep learning methods outperform older physicochemical approaches but binding prediction remains challenging.

Nature Methods · Apr 19, 2021Peer-reviewedBioinformatics