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StackAPP: Advancing autophagy protein identification with ensemble learning
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DOI：10.1016/j.ab.2025.115981.png)
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Abstract
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• A novel method is proposed for autophagy protein prediction by combining stacking classifiers. • Protein sequences are used to extract AAC and APAAC features. • The proposed method achieves an impressive accuracy of 0.9191 and a Matthews's correlation coefficient (MCC) of 0.7580. • Proposed approach outperforms existing methods in terms of predictive accuracy, as shown through comparative analysis.
Keywords:
Autophagy protein
Ensemble learning
Machine learning
Feature extraction
StackAPP model
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