Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature
We used fuzzy entropy as a feature to optimize the intrinsically disordered protein prediction scheme. The optimization scheme requires computing only five features for each residue of a protein sequence, that is, the Shannon entropy, topological entropy, and the weighted average values of two prope...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/14/4/102 |
| _version_ | 1827696864413089792 |
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| author | Lin Zhang Haiyuan Liu Hao He |
| author_facet | Lin Zhang Haiyuan Liu Hao He |
| author_sort | Lin Zhang |
| collection | DOAJ |
| description | We used fuzzy entropy as a feature to optimize the intrinsically disordered protein prediction scheme. The optimization scheme requires computing only five features for each residue of a protein sequence, that is, the Shannon entropy, topological entropy, and the weighted average values of two propensities. Notably, this is the first time that fuzzy entropy has been applied to the field of protein sequencing. In addition, we used three machine learning to examine the prediction results before and after optimization. The results show that the use of fuzzy entropy leads to an improvement in the performance of different algorithms, demonstrating the generality of its application. Finally, we compare the simulation results of our scheme with those of some existing schemes to demonstrate its effectiveness. |
| first_indexed | 2024-03-10T12:56:19Z |
| format | Article |
| id | doaj.art-9b07b601f1f04271a3772b92b3cec6c9 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T12:56:19Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-9b07b601f1f04271a3772b92b3cec6c92023-11-21T11:51:34ZengMDPI AGAlgorithms1999-48932021-03-0114410210.3390/a14040102Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy FeatureLin Zhang0Haiyuan Liu1Hao He2Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, School of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, ChinaTianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, School of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, ChinaDepartment of Communication Engineering, School of Electronic Information, Hebei University of Technology, Tianjin 300400, ChinaWe used fuzzy entropy as a feature to optimize the intrinsically disordered protein prediction scheme. The optimization scheme requires computing only five features for each residue of a protein sequence, that is, the Shannon entropy, topological entropy, and the weighted average values of two propensities. Notably, this is the first time that fuzzy entropy has been applied to the field of protein sequencing. In addition, we used three machine learning to examine the prediction results before and after optimization. The results show that the use of fuzzy entropy leads to an improvement in the performance of different algorithms, demonstrating the generality of its application. Finally, we compare the simulation results of our scheme with those of some existing schemes to demonstrate its effectiveness.https://www.mdpi.com/1999-4893/14/4/102intrinsically disordered proteinsfuzzy entropymachine learningprediction |
| spellingShingle | Lin Zhang Haiyuan Liu Hao He Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature Algorithms intrinsically disordered proteins fuzzy entropy machine learning prediction |
| title | Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature |
| title_full | Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature |
| title_fullStr | Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature |
| title_full_unstemmed | Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature |
| title_short | Prediction of Intrinsically Disordered Proteins Using Machine Learning Algorithms Based on Fuzzy Entropy Feature |
| title_sort | prediction of intrinsically disordered proteins using machine learning algorithms based on fuzzy entropy feature |
| topic | intrinsically disordered proteins fuzzy entropy machine learning prediction |
| url | https://www.mdpi.com/1999-4893/14/4/102 |
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