دورية أكاديمية
Predicting Self-Interacting Proteins Using a Recurrent Neural Network and Protein Evolutionary Information
| العنوان: | Predicting Self-Interacting Proteins Using a Recurrent Neural Network and Protein Evolutionary Information |
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| المؤلفون: | Ji-Yong An, Yong Zhou, Zi-Ji Yan, Yu-Jun Zhao |
| المصدر: | Evolutionary Bioinformatics, Vol 16 (2020) |
| بيانات النشر: | SAGE Publishing, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Evolution |
| مصطلحات موضوعية: | Evolution, QH359-425 |
| الوصف: | Self-interacting proteins (SIPs) play crucial roles in biological activities of organisms. Many high-throughput methods can be used to identify SIPs. However, these methods are both time-consuming and expensive. How to develop effective computational approaches for identifying SIPs is a challenging task. In the article, we present a novel computational method called RRN-SIFT, which combines the recurrent neural network (RNN) with scale invariant feature transform (SIFT) to predict SIPs based on protein evolutionary information. The main advantage of the proposed RNN-SIFT model is that it uses SIFT for extracting key feature by exploring the evolutionary information embedded in Position-Specific Iterated BLAST–constructed position-specific scoring matrix and employs an RNN classifier to perform classification based on extracted features. Extensive experiments show that the RRN-SIFT obtained average accuracy of 94.34% and 97.12% on the yeast and human dataset, respectively. We also compared our performance with the back propagation neural network (BPNN), the state-of-the-art support vector machine (SVM), and other existing methods. By comparing with experimental results, the performance of RNN-SIFT is significantly better than that of the BPNN, SVM, and other previous methods in the domain. Therefore, we conclude that the proposed RNN-SIFT model is a useful tool for predicting SIPs, as well to solve other bioinformatics tasks. To facilitate widely studies and encourage future proteomics research, a freely available web server called RNN-SIFT-SIPs was developed at http://219.219.62.123:8888/RNNSIFT/ including the source code and the SIP datasets. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1176-9343 11769343 |
| Relation: | https://doaj.org/toc/1176-9343 |
| DOI: | 10.1177/1176934320924674 |
| URL الوصول: | https://doaj.org/article/f146e30aa87f4b42945173f6e958a437 |
| رقم الأكسشن: | edsdoj.f146e30aa87f4b42945173f6e958a437 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 11769343 |
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| DOI: | 10.1177/1176934320924674 |