Deep Capsule Neural Network for Identifying Anticancer Peptides Using Sequence to Image Transformation based Local Embedded Features
Abstract
-pACP-CapsNet is a deep learning framework for anticancer peptide (ACP) prediction.- The method combines peptide-to-2D embedding image transformation with a deep Capsule Neural Network.- Feature extraction is performed using SMR- and RECM-based descriptors, followed by SFLA-based feature selection.
Fields of Study & Subjects
Machine Learning in Bioinformatics
Computational Drug Discovery Methods
Antimicrobial Peptides and Activities
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 3 February 2026
- Language
- EN
- Document type
- Dataset