An Insightful Recollection for Predicting Protein Subcellular Locations in Multi-Label Systems  

作　　者：Kuo-Chen Chou Kuo-Chen Chou(Gordon Life Science Institute, Boston, Massachusetts 02478, United States of America)

机构地区：[1]Gordon Life Science Institute, Boston, Massachusetts 02478, United States of America

出　　处：《Natural Science》2020年第7期441-469,共29页自然科学期刊（英文）

摘　　要：A systematic introduction has been presented for the recent advances in predicting protein subcellular localization in the multi-label systems, where the constituent proteins may simultaneously occur or move between two or more location sites and hence have exceptional biological functions worthy of our special notice. All the predictors included in this review each have a user-friendly web-server, by which the majority of experimental scientists can very easily acquire their desired data without the need to go through the complicated mathematics involved.A systematic introduction has been presented for the recent advances in predicting protein subcellular localization in the multi-label systems, where the constituent proteins may simultaneously occur or move between two or more location sites and hence have exceptional biological functions worthy of our special notice. All the predictors included in this review each have a user-friendly web-server, by which the majority of experimental scientists can very easily acquire their desired data without the need to go through the complicated mathematics involved.

关 键 词：Chou’s 5-Steps Rule Chou’s PseAAC Web-Server GO Approach FunD Approach 

分 类 号：O17[理学—数学]