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

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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Bibliographic Details
Main Authors: Le Thi Phan, Hyun Woo Park, Thejkiran Pitti, Thirumurthy Madhavan, Young-Jun Jeon, Balachandran Manavalan
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Anticancer peptides
Convolutional neural network
Feature encodings
Conventional classifiers
Baseline models
Dataset construction
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037022003245

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