Author

Maria Cristina Aspromonte

University of PaduaORCID 0000-0002-4937-6952Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Damiano PiovesaniD· 2 shared Diego Humberto MiloneiD· 2 shared Mahta MehdiabadiiD· 2 shared Silvio C. E. TosattoiD· 2 shared Aashish JainiD· 1 shared Adrian AltenhoffiD· 1 shared Alberto PaccanaroiD· 1 shared Alessandra GaspariniiD· 1 shared

Activity by Year

2019-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Damiano PiovesanORCID

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Author profile →

3 papers

Recent·Most cited

On the state of protein function prediction: a report on the fourth CAFA challenge

Rashika Ramola, M. Clara De Paolis Kaluza, Damiano Piovesan, Yisu Peng, Parnal Joshi, Mahta Mehdiabadi, Federica Quaglia, Rita Pancsa, Lucia Beatriz Chemes, Hongryul Ahn, Adrian Altenhoff, Ehsaneddin Asgari, Maria Cristina Aspromonte, Volkan Atalay, Giulia Babbi, , Maarten J. M. F. Reijnders

This paper reports on the fourth CAFA challenge, showing improvements in Gene Ontology term prediction but highlighting challenges in new evaluation settings.

bioRxiv · Jun 12, 2026 · PreprintBioinformatics

emb2dis: a novel protein disorder prediction tool based on ResNets, dilated convolutions & protein language models

S. Duarte, Mahta Mehdiabadi, Leandro A. Bugnon, Maria Cristina Aspromonte, Damiano Piovesan, Diego Humberto Milone, Silvio C. E. Tosatto, Georgina S. Stegmayer

emb2dis predicts protein disorder using a deep learning model combining ResNets and dilated convolutions, achieving top performance on benchmark datasets.

bioRxiv · Apr 1, 2026 · PreprintBioinformatics

Characterization of Intellectual disability and Autism comorbidity through gene panel sequencing

Maria Cristina Aspromonte, Mariagrazia Bellini, Alessandra Gasparini, Marco Carraro, Elisa Bettella, Roberta Polli, Federica Cesca, Stefania Bigoni, Stefania Boni, Ombretta Carlet, Susanna Negrin, Isabella Mammi, Donatella Milani, Angela Peron, Stefano Sartori, , Emanuela Leonardi

The paper develops a low-cost NGS gene panel for diagnosing intellectual disability and autism spectrum disorder, achieving a 27% diagnostic yield in 150 patients.

Human Mutation · Jun 18, 2019Peer-reviewedGenetics