title: NES-REBS: A novel nuclear export signal prediction method using regular expressions and biochemical properties.
abstract: A nuclear export signal (NES) is a protein localization signal, which is involved in binding of cargo proteins to nuclear export receptor, thus contributes to regulate localization of cellular proteins. Consensus sequences of NES have been used to detect NES from protein sequences, but suffer from poor predictive power. Some recent peering works were proposed to use biochemical properties of experimental verified NES to refine NES candidates. Those methods can achieve high prediction rates, but their execution time will become unacceptable for large-scale NES searching if too much properties are involved. In this work, we developed a novel computational approach, named NES-REBS, to search NES from protein sequences, where biochemical properties of experimental verified NES, including secondary structure and surface accessibility, are utilized to refine NES candidates obtained by matching popular consensus sequences. We test our method by searching 262 experimental verified NES from 221 NES-containing protein sequences. It is obtained that NES-REBS runs in 2-3[Formula: see text]mins and performs well by achieving precision rate 47.2% and sensitivity 54.6%.
authors.affiliation: * School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
authors.forename: Tingfang
authors.initials: T
authors.lastname: Wu
authors.affiliation: † College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P. R. China.
authors.forename: Xun
authors.initials: X
authors.lastname: Wang
authors.affiliation: * School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Zhang
authors.affiliation: † College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P. R. China.
authors.forename: Faming
authors.initials: F
authors.lastname: Gong
authors.affiliation: † College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P. R. China.|‡ Faculty of Engineering, Computing and Science Swinburne University of Technology, Sarawak Campus Kuching 93350, Malaysia.
authors.forename: Tao
authors.initials: T
authors.lastname: Song
authors.affiliation: * School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
authors.forename: Zhihua
authors.initials: Z
authors.lastname: Chen
authors.affiliation: * School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
authors.forename: Pan
authors.initials: P
authors.lastname: Zhang
authors.affiliation: * School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P. R. China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D049790:Nuclear Export Signals; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012984:Software
chemical_list: D049790:Nuclear Export Signals; D011506:Proteins
keywords: Nuclear export signal; biochemical properties; consensus sequences; secondary structure; surface accessibility