MF-EFP: Predicting Multi-Functional Enzymes Function Using Improved Hybrid Multi-Label Classifier-Reference-Cited by-同舟云学术

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MF-EFP: Predicting Multi-Functional Enzymes Function Using Improved Hybrid Multi-Label Classifier

Published:2020 Issue: Volume:8 Page:50276-50284
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Xiao Xuan,Duan Li-Wen,Xue Guang-Fu^ORCID,Chen Gang,Wang Pu,Qiu Wang-Ren^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangxi Province

Education Department of Jiangxi Province

China-Montenegro Intergovernmental S&T Cooperation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09032150.pdf?arnumber=9032150

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evidential deep learning for trustworthy prediction of enzyme commission number;Briefings in Bioinformatics;2023-11-22

2. iAHTP-LH: Integrating Low-Order and High-Order Correlation Information for Identifying Antihypertensive Peptides;International Journal of Peptide Research and Therapeutics;2022-05-21

3. Boundary Focal Loss for Class Imbalanced Learning;2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI);2021-10-23

4. iAMP-CA2L: a new CNN-BiLSTM-SVM classifier based on cellular automata image for identifying antimicrobial peptides and their functional types;Briefings in Bioinformatics;2021-06-04

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