Pseudo-188D: Phage Protein Prediction Based on a Model of Pseudo-188D

Frontiers in Genetics

Lina Guo¹  Bo Liao⁵  Qinghua Jiang⁵  Xiaomei Gu⁵ 

[1] Beidahuang Industry Group General Hospital, Harbin, China;Institute of Yangtze River Delta, University of Electronic Science and Technology of China, Haikou, China;Key Laboratory of Computational Science and Application of Hainan Province, Haikou, China;Key Laboratory of Data Science and Intelligence Education, Hainan Normal University, Ministry of Education, Haikou, China;School of Mathematics and Statistics, Hainan Normal University, Haikou, China;

关键词: model pseudo-188D;    phage;    stochastic gradient descent;    dimensional disaster;    digital characteristics;   

DOI  :  10.3389/fgene.2021.796327

来源: DOAJ

【 摘 要 】

Phages have seriously affected the biochemical systems of the world, and not only are phages related to our health, but medical treatments for many cancers and skin infections are related to phages; therefore, this paper sought to identify phage proteins. In this paper, a Pseudo-188D model was established. The digital features of the phage were extracted by PseudoKNC, an appropriate vector was selected by the AdaBoost tool, and features were extracted by 188D. Then, the extracted digital features were combined together, and finally, the viral proteins of the phage were predicted by a stochastic gradient descent algorithm. Our model effect reached 93.4853%. To verify the stability of our model, we randomly selected 80% of the downloaded data to train the model and used the remaining 20% of the data to verify the robustness of our model.

【 授权许可】

Unknown