UniBioPAN: A Novel Universal Classification Architecture for Bioactive Peptides Inspired by Video Action Recognition.
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| Title: | UniBioPAN: A Novel Universal Classification Architecture for Bioactive Peptides Inspired by Video Action Recognition. |
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| Authors: | Wang R; Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, China., Liang X; Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, China., Zhao Y; Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, China., Xue W; Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, China., Liang G; Key Laboratory of Biorheological Science and Technology (Chongqing University), Ministry of Education, Bioengineering College, Chongqing University, Chongqing 400044, China.; Bioengineering College of Chongqing University, No. 174, Shazheng Street, Shapingba District, Chongqing 400030, China. |
| Source: | Journal of chemical information and modeling [J Chem Inf Model] 2024 Dec 23; Vol. 64 (24), pp. 9276-9285. Date of Electronic Publication: 2024 Nov 21. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Washington, D.C. : American Chemical Society, c2005- |
| MeSH Terms: | Peptides*/chemistry, Neural Networks, Computer ; Amino Acid Sequence ; Software ; Video Recording |
| Abstract: | The classification of bioactive peptides is of great importance in protein biology, but there is still a lack of a universal and effective classifier. Inspired by video action recognition, we developed the UniBioPAN architecture to create a universal peptide classifier to solve this problem. The architecture treats the peptide sequence as a video sequence and the molecular image of each amino acid in the peptide sequence as a video frame, enabling feature extraction and classification using convolutional neural networks, bidirectional long short-term memory networks, and fully connected networks. As a novel peptide classification architecture, UniBioPAN significantly outperforms other universal architecture in ACC, AUC and MCC across 11 data sets, and F1 score in 9 data sets. UniBioPAN is available in three ways: python script, jupyter notebook script and web server (https://gzliang.cqu.edu.cn/software/UniBioPAN.html). In summary, UniBioPAN is a universal, convenient, and high-performance peptide classification architecture. UniBioPAN holds significant importance in the discovery of bioactive peptides and the advancement of peptide classifiers. All the codes and data sets are publicly available at https://github.com/sanwrh/UniBioPAN. |
| Substance Nomenclature: | 0 (Peptides) |
| Entry Date(s): | Date Created: 20241121 Date Completed: 20241223 Latest Revision: 20241223 |
| Update Code: | 20250114 |
| DOI: | 10.1021/acs.jcim.4c01599 |
| PMID: | 39571078 |
| Database: | MEDLINE |
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