pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning

pACP-HybDeep: predicting anticancer peptides using binary tree growth based transformer and structural feature encoding with deep-hybrid learning

Abstract Worldwide, Cancer remains a significant health concern due to its high mortality rates. Despite numerous traditional therapies and wet-laboratory methods for treating cancer-affected cells, these approaches often face limitations, including high costs and substantial side effects. Recently...

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Bibliographic Details
Main Authors: Shahid, Maqsood Hayat, Wajdi Alghamdi, Shahid Akbar, Ali Raza, Rabiah Abdul Kadir, Mahidur R. Sarker
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Anticancer peptides
Transformer encoder
Physiochemical properties
Deep Hybrid neural network
Binary tree growth feature selection
Online Access:https://doi.org/10.1038/s41598-024-84146-0
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https://doi.org/10.1038/s41598-024-84146-0

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