Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides

Abstract Background Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational...

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Detalles Bibliográficos

Principais autores:	Kyle Boone, Cate Wisdom, Kyle Camarda, Paulette Spencer, Candan Tamerler
Formato:	Artigo
Idioma:	Inglês
Publicado:	BMC 2021-05-01
Series:	BMC Bioinformatics
Assuntos:	Antibacterial Antimicrobial peptide Machine learning Rough set theory Genetic algorithm
Acceso en liña:	https://doi.org/10.1186/s12859-021-04156-x
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