DOME Registry: implementing community-wide recommendations for reporting supervised machine learning in biology

Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The Data Optimization Model Evaluation (DOME) recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data handling and processing,...

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Veröffentlicht in:	Gigascience 2024-01, Vol.13
Hauptverfasser:	Attafi, Omar Abdelghani, Clementel, Damiano, Kyritsis, Konstantinos, Capriotti, Emidio, Farrell, Gavin, Fragkouli, Styliani-Christina, Castro, Leyla Jael, Hatos, András, Lenaerts, Tom, Mazurenko, Stanislav, Mozaffari, Soroush, Pradelli, Franco, Ruch, Patrick, Savojardo, Castrense, Turina, Paola, Zambelli, Federico, Piovesan, Damiano, Monzon, Alexander Miguel, Psomopoulos, Fotis, Tosatto, Silvio C E
Format:	Artikel
Sprache:	eng
Schlagworte:	Annotations Biology Databases, Factual Domes Humans Learning algorithms Machine learning Optimization models Registries Reproducibility Reproducibility of Results Review Supervised learning Supervised Machine Learning
Online-Zugang:	Volltext
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