Tommaso Mazza

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 4 papers. Top paper: “APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants”.

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

Nature Communications(2023)10.1038/s41467-023-40797-7

N/A

0.550DataRank · unranked

38 citations

Luca Parca, Francesco Petrizzelli, Tommaso Biagini, Agnese Giovannetti, Niccolò Liorni +10 more

Gain of Function of Malate Dehydrogenase 2 and Familial Hyperglycemia

The Journal of Clinical Endocrinology & Metabolism(2021)10.1210/clinem/dgab790

N/A

0DataRank · unranked

17 citations

Antonella Marucci, Luca Pannone, Amélie Bonnefond, Serena Pezzilli, Tommaso Biagini +21 more

Novel genome‐wide associations for effort valuation and psychopathology in children and adults

American Journal of Medical Genetics Part B Neuropsychiatric Genetics(2023)10.1002/ajmg.b.32964

N/A

0DataRank · unranked

2 citations

Tommaso Mazza, Jonathan Hess, Avery B. Albert, Sarah Elfstrom, Patricia Forken +5 more

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.06.18.545476

N/A

0DataRank · unranked

0 citations

Luca Parca, Francesco Petrizzelli, Tommaso Biagini, Agnese Giovannetti, Niccolò Liorni +10 more