Author

Paolo Elvati

University of MichiganORCID 0000-0002-6882-6023Unclaimed 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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Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Approach:graph neural network· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1

Frequent Co-Authors

Angela VioliiD· 2 shared Jacob C. SaldingeriD· 2 shared Abram MagneriD· 1 shared Alfred O. HeroiD· 1 shared Emine Sumeyra Turali EmreiD· 1 shared J. Scott VanEppsiD· 1 shared Matt RaymondiD· 1 shared Mayank BaranwaliD· 1 shared

Activity by Year

2022-2022 · peak 2/yr

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10 top collaborators · 38 mutual co-author links

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2 shared papersBioinformatics

Angela VioliORCID

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2 papers

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedSep 10, 2022

Struct2Graph: A graph attention network for structure based predictions of protein-protein interactions

Mayank Baranwal, Abram Magner, Jacob C. Saldinger…·Alfred O. Hero

Struct2Graph predicts protein-protein interactions using 3D structural data with high accuracy and identifies key residues involved in interactions.

80 citationstop 2%

protein structuregraph neural network

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BioinformaticsbioRxivPreprintAug 9, 2022

From proteins to nanoparticles: domain-agnostic predictions of nanoscale interactions.

Jacob C. Saldinger, Matt Raymond, Paolo Elvati, Angela Violi

This paper introduces NeCLAS, a machine learning pipeline that predicts nanoscale interactions across domains, outperforming existing models and showing cross-domain validity.

DOI 10.1101/2022.08.09.503361

protein structuremachine learning (classical)

𝕏 PostBluesky