iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods
文献类型：期刊论文
| 作者 | Yang, Yingxi2; Wang, Hui1; Ding, Jun2; Xu, Yan2,3 |
| 刊名 | COMPUTERS IN BIOLOGY AND MEDICINE
 |
| 出版日期 | 2018-09-01 |
| 卷号 | 100页码:144-151 |
| ISSN号 | 0010-4825 |
| DOI | 10.1016/j.compbiomed.2018.07.006 |
| 英文摘要 | Motivation: Posttranslational modification (PTM) is a biological mechanism involved in the enzymatic modification of proteins after translation by ribosomes. Two or more modifications occurring at one residue can be transformed into a multi-label system. Two or more simultaneous modifications on a residue is more common than single PTMs. Lysine residues in proteins can be subjected to a variety of PTMs, such as ubiquitination, acetylation, sumoylation, methylation, and succinylation. Identification of uncharacterized sequences in proteins is a highly significant and state-of-the-art issue. Notably, in order to provide a method of processing multi-label sequences of lysine residues, it is highly desirable to develop computational methods to predict lysine acetylation and sumoylation modifications. Results: In this paper, we first launched an integrated approach, known as the five-step prediction method (FSPM), to solve the problem effectively by (1) using one-sided selection (OSS) to deal with imbalanced data, (2) extracting binary features from protein sequences, (3) incorporating binary relevance, classifier chains and multi-class transformation methods to simplify multi-label problems, (4) constructing different classifiers, and (5) implementing cross-validation and evaluating these classifiers. In 10-fold cross-validation, FSPM achieved an accuracy of 61.49% and an absolute-true rate of 60.17%. The results showed that FSPM is accurate and could be used as a powerful engine in multi-label systems. We also conducted a variety of statistical analyses of the predicted results to discuss the biological functions of lysine acetylation and sumoylation. |
| 资助项目 | Natural Science Foundation of China[11671032] ; Natural Science Foundation of China[11371365] ; Fundamental Research Funds for the Central Universities[FRF-TP-17-024A2] |
| WOS研究方向 | Life Sciences & Biomedicine - Other Topics ; Computer Science ; Engineering ; Mathematical & Computational Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:000442704300017 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5033]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Xu, Yan |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China 2.Univ Sci & Technol Beijing, Dept Informat & Comp Sci, Beijing 100083, Peoples R China 3.Univ Sci & Technol Beijing, Beijing Key Lab Magnetophotoelect Composites & In, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Yingxi,Wang, Hui,Ding, Jun,et al. iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods[J]. COMPUTERS IN BIOLOGY AND MEDICINE,2018,100:144-151. |
| APA | Yang, Yingxi,Wang, Hui,Ding, Jun,&Xu, Yan.(2018).iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods.COMPUTERS IN BIOLOGY AND MEDICINE,100,144-151. |
| MLA | Yang, Yingxi,et al."iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods".COMPUTERS IN BIOLOGY AND MEDICINE 100(2018):144-151. |
入库方式： OAI收割
来源：计算技术研究所
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