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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Autores:
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
eng
OAI Identifier:
oai:repositorio.uptc.edu.co:001/14173
Acceso en línea:
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/5834
https://repositorio.uptc.edu.co/handle/001/14173
Palabra clave:
antimicrobial peptides
learning curves
machine learning
statistical stability
support vector regression
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License
http://purl.org/coar/access_right/c_abf191