Author

Emanuele Rodolà

Sapienza University of RomeORCID 0000-0003-0091-7241Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Assay:bulk RNA-seq· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein design· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Adriano SettiiD· 1 shared Alessio ColantoniiD· 1 shared Alexandros ArmaosiD· 1 shared Angelo D’AngeloiD· 1 shared BE Correia· 1 shared Dimitrios Miltiadis VrachnosiD· 1 shared Federico MontiiD· 1 shared Flaminia PellegriniiD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBiochemistry

Adriano SettiORCID

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2 papers

Recent·Most cited

BiochemistrybioRxivPreprintFeb 16, 2025

Decoding RNA-RNA Interactions: The Role of Low-Complexity Repeats and a Deep Learning Framework for Sequence-Based Prediction

Adriano Setti, Giorgio Bini, Flaminia Pellegrini…·Gian Gaetano Tartaglia

This paper identifies low-complexity repeats as key drivers of RNA-RNA interactions and introduces RIME, a deep learning model that outperforms traditional methods in predicting these interactions.

2 citations

bulk RNA-seqdeep learning

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BioinformaticsbioRxivPreprintApr 11, 2019

Deciphering interaction fingerprints from protein molecular surfaces

Pablo Gaínza, Freyr Sverrisson, Federico Monti…·BE Correia

The paper introduces MaSIF, a geometric deep learning framework to predict biomolecular interactions by learning interaction fingerprints from protein molecular surfaces.

14 citations

protein structuredeep learning

𝕏 PostBluesky