CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers
N7-methylguanosine (m7G) modifications play a pivotal role in RNA stability, mRNA export, and protein translation. They are closely associated with ribosome function and the regulation of gene expression. Dysregulation of m7G has been implicated in various diseases, including cancers and neurodegene...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025000595 |
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| author | Peilin Xie Jiahui Guan Xuxin He Zhihao Zhao Yilin Guo Zhenglong Sun Lantian Yao Tzong-Yi Lee Ying-Chih Chiang |
| author_facet | Peilin Xie Jiahui Guan Xuxin He Zhihao Zhao Yilin Guo Zhenglong Sun Lantian Yao Tzong-Yi Lee Ying-Chih Chiang |
| author_sort | Peilin Xie |
| collection | DOAJ |
| description | N7-methylguanosine (m7G) modifications play a pivotal role in RNA stability, mRNA export, and protein translation. They are closely associated with ribosome function and the regulation of gene expression. Dysregulation of m7G has been implicated in various diseases, including cancers and neurodegenerative disorders, where the loss of m7G can lead to genomic instability and uncontrolled cell proliferation. Accurate identification of m7G sites is thus essential for elucidating these mechanisms. Due to the high cost of experimentally validating m7G sites, several artificial intelligence models have been developed to predict these sites. However, the performance of these models is not yet optimal, and a user-friendly web server is still needed. To address these issues, we developed CAP-m7G, an innovative model that integrates Chaos Game Representation, Capsule Networks, and reconstruction layers. CAP-m7G achieved an accuracy of 96.63%, a specificity of 95.07%, and a Matthews correlation coefficient (MCC) of 0.933 on independent test data. Our results demonstrate that the integration of Chaos Game Representation with Capsule Network can effectively capture the crucial sequence information associated with m7G sites. The web server can be accessed at https://awi.cuhk.edu.cn/~biosequence/CAP-m7G/index.php. |
| format | Article |
| id | doaj-art-281ea9b83c4f42ebb00540fe50a66dbf |
| institution | DOAJ |
| issn | 2001-0370 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj-art-281ea9b83c4f42ebb00540fe50a66dbf2025-08-20T03:05:07ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-012780481210.1016/j.csbj.2025.02.029CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layersPeilin Xie0Jiahui Guan1Xuxin He2Zhihao Zhao3Yilin Guo4Zhenglong Sun5Lantian Yao6Tzong-Yi Lee7Ying-Chih Chiang8Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaSchool of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaSchool of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, ChinaKobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; Corresponding authors at: Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan; Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan; Corresponding author at: Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China; Corresponding authors at: Kobilka Institute of Innovative Drug Discovery, School of Medicine, The Chinese University of Hong Kong, Shenzhen, 2001 Longxiang Blvd, Longgang District, 518172, Shenzhen, China.N7-methylguanosine (m7G) modifications play a pivotal role in RNA stability, mRNA export, and protein translation. They are closely associated with ribosome function and the regulation of gene expression. Dysregulation of m7G has been implicated in various diseases, including cancers and neurodegenerative disorders, where the loss of m7G can lead to genomic instability and uncontrolled cell proliferation. Accurate identification of m7G sites is thus essential for elucidating these mechanisms. Due to the high cost of experimentally validating m7G sites, several artificial intelligence models have been developed to predict these sites. However, the performance of these models is not yet optimal, and a user-friendly web server is still needed. To address these issues, we developed CAP-m7G, an innovative model that integrates Chaos Game Representation, Capsule Networks, and reconstruction layers. CAP-m7G achieved an accuracy of 96.63%, a specificity of 95.07%, and a Matthews correlation coefficient (MCC) of 0.933 on independent test data. Our results demonstrate that the integration of Chaos Game Representation with Capsule Network can effectively capture the crucial sequence information associated with m7G sites. The web server can be accessed at https://awi.cuhk.edu.cn/~biosequence/CAP-m7G/index.php.http://www.sciencedirect.com/science/article/pii/S2001037025000595N7-methylguanosineBioinformaticsCGR encodingCapsule network |
| spellingShingle | Peilin Xie Jiahui Guan Xuxin He Zhihao Zhao Yilin Guo Zhenglong Sun Lantian Yao Tzong-Yi Lee Ying-Chih Chiang CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers Computational and Structural Biotechnology Journal N7-methylguanosine Bioinformatics CGR encoding Capsule network |
| title | CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers |
| title_full | CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers |
| title_fullStr | CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers |
| title_full_unstemmed | CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers |
| title_short | CAP-m7G: A capsule network-based framework for specific RNA N7-methylguanosine site identification using image encoding and reconstruction layers |
| title_sort | cap m7g a capsule network based framework for specific rna n7 methylguanosine site identification using image encoding and reconstruction layers |
| topic | N7-methylguanosine Bioinformatics CGR encoding Capsule network |
| url | http://www.sciencedirect.com/science/article/pii/S2001037025000595 |
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