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

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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Bibliographic Details
Main Authors: Francy Liliana Camacho, Rodrigo Torres-Sáez, Raúl Ramos-Pollán
Format: Article
Language:English
Published: Universidad Pedagógica y Tecnológica de Colombia 2016-12-01
Series:Revista Facultad de Ingeniería
Subjects:
antimicrobial peptides
learning curves
machine learning
statistical stability
support vector regression
Online Access:http://revistas.uptc.edu.co/index.php/ingenieria/article/view/5834

Internet

http://revistas.uptc.edu.co/index.php/ingenieria/article/view/5834

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