Enhancing Protein Sequence Classification with a Fuzzy Neural Network: A Study in Anticancer Peptide Identification

Nguyen Quoc Khanh Le, Van Nui Nguyen, Thi Tuyen Nguyen, Thi Xuan Tran, Trang Thi Ho

研究成果: 書貢獻/報告類型會議貢獻

摘要

In bioinformatics, classifying protein sequences into anticancer peptides (ACPs) and non-ACPs is crucial yet challenging due to the inherent uncertainties of biological data. This study introduces a novel fuzzy neural network (FNN) model that integrates fuzzy logic within neural network architectures, enhancing the handling of ambiguity and improving classification accuracy. Our model, tested against several conventional machine learning models and recent studies, demonstrated superior specificity (83.28%) and overall accuracy (79.14%), marking a significant advancement in the identification of therapeutically relevant peptides. The integration of fuzzy logic not only optimized the performance but also increased the interpretability of the results, making it a valuable tool for complex bioinformatic analyses. These findings underscore the potential of fuzzy systems to refine predictive capabilities in computational biology, aligning perfectly with the themes of enhancing fuzzy theory applications in practical and impactful ways.
原文英語
主出版物標題2024 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2024
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350352788
DOIs
出版狀態已發佈 - 2024
事件2024 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2024 - Kagawa, 日本
持續時間: 8月 10 20248月 13 2024

出版系列

名字2024 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2024

會議

會議2024 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2024
國家/地區日本
城市Kagawa
期間8/10/248/13/24

ASJC Scopus subject areas

  • 邏輯
  • 人工智慧
  • 應用數學
  • 建模與模擬
  • 控制和優化

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