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- Title
蛋白质二级结构在线服务器预测评估.
- Authors
朱树平; 刘毅慧
- Abstract
The prediction of protein secondary structure is of great significance for studying the function of proteins and human life sciences. The prediction of protein secondary structure was put forward in 1951, but the accuracy rate was only 50% in 1983. During years of development, the prediction method has been continuously optimized, and the accuracy rate has already exceeded 80%. However, there are many online servers, and Continuous Automate Model Evaluation (CAMEO) can only provide predictive evaluation of the server's three-level structure, while the secondary structure evaluation has not been realized. Aiming to solve the above problems, PSRSM, MUFOLD, SPIDER, RAPTORX, JPRED, and PSIPRED were selected to evaluate their predicted secondary structure. The latest released protein from the Protein Data Rank (PDR) was applied to ensure that the test set is not included in the training set. In the experiments where the protein homology was 30%, 50% and 70%, the obtained accuracy of PSRSM for Q3 were 91.44%, 88.12%, and 90.17%, respectively. The accuracy was higher than the best prediction server MUFOLD by 3.19%, 1.33%, and 2.19% correspondingly, which proved that PSRSM has better prediction accuracy than other servers for the same kind of homology data and for the Sov. This paper focuses on analyzing the operating methods and corresponding results of various servers, thus it is concluded that the prediction of protein secondary structure should be studied from the perspectives of big data, templates, and in-depth learning.
- Publication
Chinese Journal of Bioinformatics, 2019, Vol 17, Issue 1, p53
- ISSN
1672-5565
- Publication type
Academic Journal
- DOI
10.12113/j.issn.1672-5565.201808002