Machine learning-guided discovery and design of non-hemolytic peptides

Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biological activities from primary sequences. Their li...

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Detalles Bibliográficos
Autores principales: Plisson, Fabien, Ramírez-Sánchez, Obed, Martínez-Hernández, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538962/
https://www.ncbi.nlm.nih.gov/pubmed/33024236
http://dx.doi.org/10.1038/s41598-020-73644-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538962/
https://www.ncbi.nlm.nih.gov/pubmed/33024236
http://dx.doi.org/10.1038/s41598-020-73644-6

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