Reproducibility standards for machine learning in the life sciences.

Abstract:

To make machine learning analyses in the life sciences more computationally reproducible, we propose standards based on data, model, and code publication, programming best practices, and workflow automation. By meeting these standards, the community of researchers applying machine learning methods in the life sciences can ensure that their analyses are worthy of trust.

Authors:

BJ Heil, MM Hoffman, F Markowetz, S-I Lee, CS Greene, SC Hicks

Journal:

Nat Methods

Citation info:

18(10):1132-1135

Publication date:

1st Oct 2021

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