Author

Michele Monti

Italian Institute of Technology

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

Biology Disciplines

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Biochemistry· 2 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:bacteria (other)· 1 Organism:human· 1 Research Focus:protein folding & dynamics· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexandros ArmaosiD· 2 shared Dimitrios Miltiadis VrachnosiD· 2 shared Gian Gaetano TartagliaiD· 2 shared Jonathan FiorentinoiD· 2 shared David K. Lubesnky· 1 shared Eulalia Marti Puig· 1 shared Giorgio Bini· 1 shared Lorenzo Di RienzoiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersBiochemistry

Alexandros ArmaosORCID

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Author profile →

3 papers

Recent·Most cited

HERCULES: a deep-learning framework for RNA-binding region localization and mutation-effect prediction

Jonathan Fiorentino, Michele Monti, Alexandros Armaos, Dimitrios Miltiadis Vrachnos, Lorenzo Di Rienzo, Veronica Venturi, Maria Teresa Botta Orfila, Eulalia Marti Puig, Gian Gaetano Tartaglia

HERCULES predicts RNA-binding regions and mutation effects using a deep-learning framework combining language models and physicochemical descriptors.

bioRxiv · Oct 27, 2026 · PreprintBiochemistry

Accurate Predictions of Phase Separating Proteins at Single Amino Acid Resolution

Michele Monti, Jonathan Fiorentino, Dimitrios Miltiadis Vrachnos, Giorgio Bini, Tiziana Cotrufo, Natalia Sánchez de Groot, Alexandros Armaos, Gian Gaetano Tartaglia

This paper introduces catGRANULE 2.0 ROBOT, an algorithm predicting protein LLPS at single amino acid resolution, showing high performance and experimental validation.

Genome biology · Feb 20, 2025Peer-reviewedBiochemistry

Theory of Circadian Metabolism

Michele Monti, David K. Lubesnky, Pieter Rein ten Wolde

The paper extends a framework for quantifying growth and proteome composition to circadian metabolism in cyanobacteria, showing that storing carbon and nitrogen leads to an optimal growth strategy constrained by slow proteome relaxation.

bioRxiv · May 14, 2018 · PreprintSystems Biology