DOME is a set of community-wide recommendations for reporting supervised machine learning-based analyses applied to biological studies. Broad adoption of these recommendations will help improve machine learning assessment and reproducibility.

DOME: recommendations for supervised machine learning validation in biology / I. Walsh, D. Fishman, D. Garcia-Gasulla, T. Titma, G. Pollastri, E. Capriotti, R. Casadio, S. Capella-Gutierrez, D. Cirillo, A. Del Conte, A.C. Dimopoulos, V.D. Del Angel, J. Dopazo, P. Fariselli, J.M. Fernandez, F. Huber, A. Kreshuk, T. Lenaerts, P.L. Martelli, A. Navarro, P.O. Broin, J. Pinero, D. Piovesan, M. Reczko, F. Ronzano, V. Satagopam, C. Savojardo, V. Spiwok, M.A. Tangaro, G. Tartari, D. Salgado, A. Valencia, F. Zambelli, J. Harrow, F.E. Psomopoulos, S.C.E. Tosatto. - In: NATURE METHODS. - ISSN 1548-7091. - (2021). [Epub ahead of print] [10.1038/s41592-021-01205-4]

DOME: recommendations for supervised machine learning validation in biology

F. Zambelli;
2021

Abstract

DOME is a set of community-wide recommendations for reporting supervised machine learning-based analyses applied to biological studies. Broad adoption of these recommendations will help improve machine learning assessment and reproducibility.
Settore BIO/11 - Biologia Molecolare
Settore BIO/10 - Biochimica
Settore INF/01 - Informatica
27-lug-2021
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/860286
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