Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7562605 | Chemometrics and Intelligent Laboratory Systems | 2016 | 9 Pages |
Abstract
Subcellular location is very useful to understand the mechanism and functions of apoptosis proteins. Various efficient methods have been proposed to predict subcellular location prediction, but challenges still exist. In this paper, we proposed a segmentation based model to improve subcellular location prediction. In three experiments, the proposed model reported robust results and demonstrated better performance compared with existing methods, which can be contributed to the introduction of the segmentation because it makes the N-segment and C-segment of the proteins gotten differential treatment in subcellular location prediction. This understanding can be useful to design more powerful method for predicting subcellular location. The software, data and supplement material are freely available at http://bioinfo.zstu.edu.cn/GoldenP/.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Qi Dai, Sheng Ma, Yabin Hai, Yuhua Yao, Xiaoqing Liu,