Assessing the behavior of machine learning methods to predict the activity of antimicrobial peptides

This study demonstrates the importance of obtaining statistically stable results when using machine learning methods to predict the activity of antimicrobial peptides, due to the cost and complexity of the chemical processes involved in cases where datasets are particularly small (less than a few hu...

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Détails bibliographiques

Auteurs principaux:	Camacho, Francy Liliana, Torres-Sáez, Rodrigo, Ramos-Pollán, Raúl
Format:	Online
Langue:	eng
Publié:	Universidad Pedagógica y Tecnológica de Colombia 2016
Sujets:	antimicrobial peptides learning curves machine learning statistical stability support vector regression
Accès en ligne:	https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5834