iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods

doi:10.1016/j.compbiomed.2018.07.006

	iAcet-Sumo: Identification of lysine acetylation and sumoylation sites in proteins by multi-class transformation methods
	Yang, Yingxi 1; Wang, Hui 2; Ding, Jun 1; Xu, Yan 1,3
	2018-09-01
发表期刊	COMPUTERS IN BIOLOGY AND MEDICINE
ISSN	0010-4825
卷号	100 页码:144-151
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.
DOI	10.1016/j.compbiomed.2018.07.006
收录类别	SCI
语种	英语
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
WOS类目	Biology ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Mathematical & Computational Biology
WOS记录号	WOS:000442704300017
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/5034
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.Univ Sci & Technol Beijing, Dept Informat & Comp Sci, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, 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.