Towards a more accurate and reliable evaluation of machine learning protein–protein interaction prediction model performance in the presence of unavoidable dataset biases

The characterization of protein-protein interactions (PPIs) is fundamental to understand cellular functions. Although machine learning methods in this task have historically reported prediction accuracies up to 95 %, including those only using raw protein sequences, it has been highlighted that this...

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Autori principali:	Nogueira-Rodríguez Alba, Glez-Peña Daniel, Vieira Cristina P., Vieira Jorge, López-Fernández Hugo
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	De Gruyter 2025-04-01
Serie:	Journal of Integrative Bioinformatics
Soggetti:	protein–protein interaction prediction machine learning biased datasets model evaluation sequence embedding
Accesso online:	https://doi.org/10.1515/jib-2024-0054
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