Author

Dinko Franceschi

Harvard University

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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Genetic & Genomic Medicine· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:variant effect prediction· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Organism:human· 1 Organism:multiple species· 1 Assay:protein sequence· 1

Frequent Co-Authors

Aaron W. KollaschiD· 2 shared Debora S. MarksiD· 2 shared Jonathan FrazeriD· 2 shared Lood van NiekerkiD· 2 shared Mafalda DiasiD· 2 shared Rose OrenbuchiD· 2 shared Ada Y. ShawiD· 1 shared Aviv D. Spinner· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

Aaron W. KollaschORCID

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2 papers

Recent·Most cited

Proteome-wide model for human disease genetics

Rose Orenbuch, Courtney A. Shearer, Aaron W. Kollasch, Aviv D. Spinner, Thomas A. Hopf, Lood van Niekerk, Dinko Franceschi, Mafalda Dias, Jonathan Frazer, Debora S. Marks

This paper introduces popEVE, a deep generative model for proteome-wide disease variant prediction, identifying 442 genes in a developmental disorder cohort, including 123 novel candidates.

Nature Genetics · Nov 24, 2025Peer-reviewedGenetic & Genomic Medicine

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction

Pascal Notin, Aaron W. Kollasch, Daniel Ritter, Lood van Niekerk, Steffan B. Paul, Hansen Spinner, Nathan J. Rollins, Ada Y. Shaw, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Rose Orenbuch, Yarin Gal, Debora S. Marks

ProteinGym unifies over 250 deep mutational scans and ~65k clinical variants to benchmark over 70 models in zero-shot and supervised settings; TranceptEVE ranks best overall.

bioRxiv · Dec 7, 2023 · PreprintSynthetic Biology✦ In-depth digest