Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection

doi:10.1038/srep38318

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	Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection
	Xu, Yan 1; Ding, Ya-Xin 1; Ding, Jun 1; Wu, Ling-Yun2 ; Xue, Yu 3
	2016-12-02
发表期刊	SCIENTIFIC REPORTS
ISSN	2045-2322
卷号	6 页码:7
摘要	Lysine malonylation is an important post-translational modification (PTM) in proteins, and has been characterized to be associated with diseases. However, identifying malonyllysine sites still remains to be a great challenge due to the labor-intensive and time-consuming experiments. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor Mal-Lys which incorporated residue sequence order information, position-specific amino acid propensity and physicochemical properties was proposed. A feature selection method of minimum Redundancy Maximum Relevance (mRMR) was used to select optimal ones from the whole features. With the leave-one-out validation, the value of the area under the curve (AUC) was calculated as 0.8143, whereas 6-, 8- and 10-fold cross-validations had similar AUC values which showed the robustness of the predictor Mal-Lys. The predictor also showed satisfying performance in the experimental data from the UniProt database. Meanwhile, a user-friendly webserver for Mal-Lys is accessible at http://app.aporc.org/Mal-Lys/.
DOI	10.1038/srep38318
语种	英语
资助项目	Natural Science Foundation of China[11301024] ; Natural Science Foundation of China[11671032] ; Natural Science Foundation of China[31671360] ; Natural Science Foundation of China[81272578] ; Natural Science Foundation of China[J1103514] ; National Basic Research Program (973 project)[2013CB933900] ; Fundamental Research Funds for the Central Universities[FRF-BR-15-029A] ; Fundamental Research Funds for the Central Universities[FRF-BR-15-075A] ; International Science & Technology Cooperation Program of China[2014DFB30020]
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000389123700001
出版者	NATURE PUBLISHING GROUP
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/24189
专题	应用数学研究所
通讯作者	Xue, Yu
作者单位	1.Univ Sci & Technol Beijing, Dept Informat & Comp Sci, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing 100190, Peoples R China 3.Huazhong Univ Sci & Technol, Dept Biomed Engn, Coll Life Sci & Technol, Wuhan 430074, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Xu, Yan,Ding, Ya-Xin,Ding, Jun,et al. Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection[J]. SCIENTIFIC REPORTS,2016,6:7.
APA	Xu, Yan,Ding, Ya-Xin,Ding, Jun,Wu, Ling-Yun,&Xue, Yu.(2016).Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection.SCIENTIFIC REPORTS,6,7.
MLA	Xu, Yan,et al."Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection".SCIENTIFIC REPORTS 6(2016):7.