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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\u20133[Formula: see text]mins and performs well by achieving precision rate 47.2% and sensitivity 54.6%. <\/jats:p>","DOI":"10.1142\/s021972001650013x","type":"journal-article","created":{"date-parts":[[2016,4,7]],"date-time":"2016-04-07T04:26:36Z","timestamp":1460003196000},"page":"1650013","source":"Crossref","is-referenced-by-count":1,"title":["NES-REBS: A novel nuclear export signal prediction method using regular expressions and biochemical properties"],"prefix":"10.1142","volume":"14","author":[{"given":"Tingfang","family":"Wu","sequence":"first","affiliation":[{"name":"School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P.\u00a0R.\u00a0China"}]},{"given":"Xun","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P.\u00a0R.\u00a0China"}]},{"given":"Zheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, P.\u00a0R.\u00a0China"}]},{"given":"Faming","family":"Gong","sequence":"additional","affiliation":[{"name":"College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P.\u00a0R.\u00a0China"}]},{"given":"Tao","family":"Song","sequence":"additional","affiliation":[{"name":"College of Computer and Communication Engineering, China University of Petroleum, Qingdao 266580, Shandong, P.\u00a0R.\u00a0China"},{"name":"Faculty of Engineering, Computing and Science Swinburne University of Technology, Sarawak Campus Kuching 93350, Malaysia"}]},{"given":"Zhihua","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, 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