MLACP 2.0: An updated machine learning tool for anticancer peptide prediction

Anticancer peptides are emerging anticancer drug that offers fewer side effects and is more effective than chemotherapy and targeted therapy. Predicting anticancer peptides from sequence information is one of the most challenging tasks in immunoinformatics. In the past ten years, machine learning-ba...

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Detalles Bibliográficos
Autores principales: Thi Phan, Le, Woo Park, Hyun, Pitti, Thejkiran, Madhavan, Thirumurthy, Jeon, Young-Jun, Manavalan, Balachandran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421197/
https://www.ncbi.nlm.nih.gov/pubmed/36051870
http://dx.doi.org/10.1016/j.csbj.2022.07.043

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421197/
https://www.ncbi.nlm.nih.gov/pubmed/36051870
http://dx.doi.org/10.1016/j.csbj.2022.07.043

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