Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning
Deep learning models have been successfully applied in a wide range of fields. The creation of a deep learning framework for analyzing high-performance sequence data have piqued the research community’s interest. N4 acetylcytidine (ac4C) is a post-transcriptional modification in mRNA, is an mRNA com...
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| Format: | Article |
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MDPI AG
2022-01-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/3/1344 |
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| author | Muhammad Shahid Iqbal Rashid Abbasi Md Belal Bin Heyat Faijan Akhtar Asmaa Sayed Abdelgeliel Sarah Albogami Eman Fayad Muhammad Atif Iqbal |
| author_facet | Muhammad Shahid Iqbal Rashid Abbasi Md Belal Bin Heyat Faijan Akhtar Asmaa Sayed Abdelgeliel Sarah Albogami Eman Fayad Muhammad Atif Iqbal |
| author_sort | Muhammad Shahid Iqbal |
| collection | DOAJ |
| description | Deep learning models have been successfully applied in a wide range of fields. The creation of a deep learning framework for analyzing high-performance sequence data have piqued the research community’s interest. N4 acetylcytidine (ac4C) is a post-transcriptional modification in mRNA, is an mRNA component that plays an important role in mRNA stability control and translation. The ac4C method of mRNA changes is still not simple, time consuming, or cost effective for conventional laboratory experiments. As a result, we developed DL-ac4C, a CNN-based deep learning model for ac4C recognition. In the alternative scenario, the model families are well-suited to working in large datasets with a large number of available samples, especially in biological domains. In this study, the DL-ac4C method (deep learning) is compared to non-deep learning (machine learning) methods, regression, and support vector machine. The results show that DL-ac4C is more advanced than previously used approaches. The proposed model improves the accuracy recall area by 9.6 percent and 9.8 percent, respectively, for cross-validation and independent tests. More nuanced methods of incorporating prior bio-logical knowledge into the estimation procedure of deep learning models are required to achieve better results in terms of predictive efficiency and cost-effectiveness. Based on an experiment’s acetylated dataset, the DL-ac4C sequence-based predictor for acetylation sites in mRNA can predict whether query sequences have potential acetylation motifs. |
| first_indexed | 2024-03-10T00:12:40Z |
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| id | doaj.art-06b6ec79b3be4da0af4e5adbf59a3470 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T00:12:40Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-06b6ec79b3be4da0af4e5adbf59a34702023-11-23T15:56:05ZengMDPI AGApplied Sciences2076-34172022-01-01123134410.3390/app12031344Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep LearningMuhammad Shahid Iqbal0Rashid Abbasi1Md Belal Bin Heyat2Faijan Akhtar3Asmaa Sayed Abdelgeliel4Sarah Albogami5Eman Fayad6Muhammad Atif Iqbal7School of Computer Science and Technology, Anhui University, Hefei 230039, ChinaSchool of Information and Communication Engineering, University of Electronics Science and Technology of China, Chengdu 610056, ChinaIoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610056, ChinaDepartment of Botany & Microbiology, South Valley University, Qena 83523, EgyptDepartment of Biotechnology, College of Science, Taif University, Taif 21944, Saudi ArabiaDepartment of Biotechnology, College of Science, Taif University, Taif 21944, Saudi ArabiaDepartment of Computer Science, Air University, Islamabad 44000, PakistanDeep learning models have been successfully applied in a wide range of fields. The creation of a deep learning framework for analyzing high-performance sequence data have piqued the research community’s interest. N4 acetylcytidine (ac4C) is a post-transcriptional modification in mRNA, is an mRNA component that plays an important role in mRNA stability control and translation. The ac4C method of mRNA changes is still not simple, time consuming, or cost effective for conventional laboratory experiments. As a result, we developed DL-ac4C, a CNN-based deep learning model for ac4C recognition. In the alternative scenario, the model families are well-suited to working in large datasets with a large number of available samples, especially in biological domains. In this study, the DL-ac4C method (deep learning) is compared to non-deep learning (machine learning) methods, regression, and support vector machine. The results show that DL-ac4C is more advanced than previously used approaches. The proposed model improves the accuracy recall area by 9.6 percent and 9.8 percent, respectively, for cross-validation and independent tests. More nuanced methods of incorporating prior bio-logical knowledge into the estimation procedure of deep learning models are required to achieve better results in terms of predictive efficiency and cost-effectiveness. Based on an experiment’s acetylated dataset, the DL-ac4C sequence-based predictor for acetylation sites in mRNA can predict whether query sequences have potential acetylation motifs.https://www.mdpi.com/2076-3417/12/3/1344CNN (convolutional neural network)deep Learningsequence dataN4-acetylcytidine (ac4C) |
| spellingShingle | Muhammad Shahid Iqbal Rashid Abbasi Md Belal Bin Heyat Faijan Akhtar Asmaa Sayed Abdelgeliel Sarah Albogami Eman Fayad Muhammad Atif Iqbal Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning Applied Sciences CNN (convolutional neural network) deep Learning sequence data N4-acetylcytidine (ac4C) |
| title | Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning |
| title_full | Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning |
| title_fullStr | Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning |
| title_full_unstemmed | Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning |
| title_short | Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning |
| title_sort | recognition of mrna n4 acetylcytidine ac4c by using non deep vs deep learning |
| topic | CNN (convolutional neural network) deep Learning sequence data N4-acetylcytidine (ac4C) |
| url | https://www.mdpi.com/2076-3417/12/3/1344 |
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