KMS Of Academy of mathematics and systems sciences, CAS
| Mal-Lys: prediction of lysine malonylation sites in proteins integrated sequence-based features with mRMR feature selection | |
Xu, Yan1; Ding, Ya-Xin1; Ding, Jun1; Wu, Ling-Yun2 ; Xue, Yu3
| |
| 2016-12-02 | |
| Source Publication | SCIENTIFIC REPORTS
 |
| ISSN | 2045-2322 |
| Volume | 6Pages:7 |
| Abstract | 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 |
| Language | 英语 |
| Funding Project | 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 Research Area | Science & Technology - Other Topics |
| WOS Subject | Multidisciplinary Sciences |
| WOS ID | WOS:000389123700001 |
| Publisher | NATURE PUBLISHING GROUP |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/24189 |
| Collection | 应用数学研究所 |
| Corresponding Author | Xue, Yu |
| Affiliation | 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 |
| Recommended Citation 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. |
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