Authors: Zhihua Chen Pan Zhang Xun Wang Xiaolong Shi Tingfang Wu Pan Zheng
Publish Date: 2016/07/19
Volume: 29, Issue: 3, Pages: 695-705
Abstract
Nuclear export signal NES is a nuclear targeting signal within cargo proteins which is involved in signal transduction and cell cycle regulation NES is believed to be “born to be weak” hence it is a challenge in computational biology to identify it from highthroughput data of amino acid sequences This work endeavors to tackle the challenge by proposing a computational approach to identifying NES using spiking neural P SN P systems Specifically secondary structure elements of 30 experimentally verified NES are randomly selected for training an SN P system and then 1224 amino acid sequences containing 1015 regular amino acid sequences and 209 experimentally verified NES abstracted from 221 NEScontaining protein sequences randomly in NESdb are selected to test our method Experimental results show that our method achieves a precision rate 7541 better than NESREBS 472 Wregex 254 ELM and NetNES 374 The results of this study are promising in terms of the fact that it is the first feasible attempt to use SN P systems in computational biology after many theoretical advancementsThis work was supported by National Natural Science Foundation of China 61272152 61370105 61402187 61502535 61572522 and 61572523 China Postdoctoral Science Foundation funded project 2016M592267 Program for New Century Excellent Talents in University NCET131031 863 Program 2015AA020925 and Fundamental Research Funds for the Central Universities R1607005A
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