Author

Elena Tea Russo

AREA Science ParkORCID 0000-0002-0061-2328Unclaimed 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 sequence· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Marco PuntaiD· 2 shared Alberto CazzanigaiD· 1 shared Alessandro LaioiD· 1 shared Alessio AnsuiniiD· 1 shared Edith Natalia Villegas GarciaiD· 1 shared Federico BaroneiD· 1 shared Stefano CozziniiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 16 mutual co-author links

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2 shared papersBioinformatics

Marco PuntaORCID

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2 papers

Recent·Most cited

BioinformaticsScientific DataPeer-reviewedJun 1, 2024

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering

Federico Barone, Elena Tea Russo, Edith Natalia Villegas Garcia…·Alberto Cazzaniga

This paper annotates protein families in the Unified Human Gastrointestinal Proteome using DPCfam clustering, improving family coverage over Pfam.

4 citations

humanprotein sequence

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BioinformaticsBMC BioinformaticsPeer-reviewedMar 12, 2021

DPCfam: a new method for unsupervised protein family classification

Elena Tea Russo, Alessandro Laio, Marco Punta

DPCfam classifies protein sequences into homologous families using Density Peak Clustering, showing accuracy in aligning with Pfam families and potential for metagenomics analysis.

4 citations

protein sequencestatistical model

𝕏 PostBluesky