期刊
CURRENT BIOINFORMATICS
卷 14, 期 3, 页码 234-240出版社
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1574893613666181113131415
关键词
Golgi apparatus; machine learning method; feature vector; feature selection technique; webserver; benchmark dataset
资金
- National Nature Scientific Foundation of China [61772119, 61861036]
- Fundamental Research Funds for the Central Universities of China [ZYGX2015J144, ZYGX2015Z006, ZYGX2016J118, ZYGX2016J126]
- Research program of science and technology at universities of Inner Mongolia Autonomous Region [NJZY17013]
Background: The location of proteins in a cell can provide important clues to their functions in various biological processes. Thus, the application of machine learning method in the prediction of protein subcellular localization has become a hotspot in bioinformatics. As one of key organelles, the Golgi apparatus is in charge of protein storage, package, and distribution. Objective: The identification of protein location in Golgi apparatus will provide in-depth insights into their functions. Thus, the machine learning-based method of predicting protein location in Golgi apparatus has been extensively explored. The development of protein sub-Golgi apparatus localization prediction should be reviewed for providing a whole background for the fields. Method: The benchmark dataset, feature extraction, machine learning method and published results were summarized. Results: We briefly introduced the recent progresses in protein sub-Golgi apparatus localization prediction using machine learning methods and discussed their advantages and disadvantages. Conclusion: We pointed out the perspective of machine learning methods in protein sub-Golgi localization prediction.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据