Cargando…
Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides
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 outcome...
Autores principales: | Boone, Kyle, Wisdom, Cate, Camarda, Kyle, Spencer, Paulette, Tamerler, Candan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111958/ https://www.ncbi.nlm.nih.gov/pubmed/33975547 http://dx.doi.org/10.1186/s12859-021-04156-x |
Ejemplares similares
-
Antimicrobial peptide similarity and classification through rough set theory using physicochemical boundaries
por: Boone, Kyle, et al.
Publicado: (2018) -
Peptide Mediated Antimicrobial Dental Adhesive System
por: Xie, Sheng-Xue, et al.
Publicado: (2019) -
Engineered Peptides Enable Biomimetic Route for Collagen Intrafibrillar Mineralization
por: Cloyd, Aya K., et al.
Publicado: (2023) -
Peptide-Enabled Nanocomposites Offer Biomimetic Reconstruction of Silver Diamine Fluoride-Treated Dental Tissues
por: Woolfolk, Sarah Kay, et al.
Publicado: (2022) -
Reconfigurable Dual Peptide Tethered Polymer System Offers a Synergistic Solution for Next Generation Dental Adhesives
por: Yuca, Esra, et al.
Publicado: (2021)