Prediction of apoptosis protein subcellular location based on amphiphilic pseudo amino acid composition

被引:2
|
作者
Su, Wenxia [1 ]
Deng, Shuyi [2 ]
Gu, Zhifeng [2 ]
Yang, Keli [3 ]
Ding, Hui [2 ]
Chen, Hui [4 ]
Zhang, Zhaoyue [2 ,4 ]
机构
[1] Inner Mongolia Agr Univ, Coll Sci, Hohhot, Peoples R China
[2] Univ Elect Sci & Technol China, Ctr Informat Biol, Sch Life Sci & Technol, Chengdu, Peoples R China
[3] Baoji Univ Arts & Sci, Nonlinear Res Inst, Baoji, Peoples R China
[4] Chengdu Neusoft Univ, Sch Healthcare Technol, Chengdu, Peoples R China
基金
中国国家自然科学基金;
关键词
apoptosis protein; subcellular location; amphiphilic pseudo amino acid composition; support vector machine; jackknife test; NEURAL-NETWORK; LOCALIZATION; MACHINE; PSEAAC; SITES;
D O I
10.3389/fgene.2023.1157021
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Introduction: Apoptosis proteins play an important role in the process of cell apoptosis, which makes the rate of cell proliferation and death reach a relative balance. The function of apoptosis protein is closely related to its subcellular location, it is of great significance to study the subcellular locations of apoptosis proteins. Many efforts in bioinformatics research have been aimed at predicting their subcellular location. However, the subcellular localization of apoptotic proteins needs to be carefully studied.Methods: In this paper, based on amphiphilic pseudo amino acid composition and support vector machine algorithm, a new method was proposed for the prediction of apoptosis proteins' subcellular location.Results and Discussion: The method achieved good performance on three data sets. The Jackknife test accuracy of the three data sets reached 90.5%, 93.9% and 84.0%, respectively. Compared with previous methods, the prediction accuracies of APACC_SVM were improved.
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页数:6
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