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The importance of negative training data for...
Journal article

The importance of negative training data for robust antibody binding prediction

Abstract

Thoughtfully designed negative training datasets may hold the key to more robust machine learning models. Ursu et al. reveal how negative training data composition shapes antibody prediction models and their generalizability. Sometimes, the best way to get better is to train harder.

Authors

Ta W; Stokes JM

Journal

Nature Machine Intelligence, Vol. 7, No. 8, pp. 1192–1194

Publisher

Springer Nature

Publication Date

August 1, 2025

DOI

10.1038/s42256-025-01080-0

ISSN

2522-5839