Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods

	Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods
	Wang, Ping 1; Hu, Lele 2,3; Liu, Guiyou 1; Jiang, Nan 1; Chen, Xiaoyun 1; Xu, Jianyong 1; Zheng, Wen 1; Li, Li 1; Tan, Ming 1; Chen, Zugen 1,4
刊名	PLOS ONE
	2011-04-13
卷号	6 期号:4 页码:e18476
关键词	AMINO-ACID-COMPOSITION PROTEIN STRUCTURAL CLASSES SUBCELLULAR LOCATION PREDICTION SECONDARY STRUCTURE-CONTENT DISCRETE WAVELET TRANSFORM COUPLED RECEPTOR CLASSES SUPPORT VECTOR MACHINE APPROXIMATE ENTROPY APOPTOSIS PROTEINS EVOLUTIONARY INFORMATION
英文摘要	Antimicrobial peptides (AMPs) represent a class of natural peptides that form a part of the innate immune system, and this kind of 'nature's antibiotics' is quite promising for solving the problem of increasing antibiotic resistance. In view of this, it is highly desired to develop an effective computational method for accurately predicting novel AMPs because it can provide us with more candidates and useful insights for drug design. In this study, a new method for predicting AMPs was implemented by integrating the sequence alignment method and the feature selection method. It was observed that, the overall jackknife success rate by the new predictor on a newly constructed benchmark dataset was over 80.23%, and the Mathews correlation coefficient is 0.73, indicating a good prediction. Moreover, it is indicated by an in-depth feature analysis that the results are quite consistent with the previously known knowledge that some amino acids are preferential in AMPs and that these amino acids do play an important role for the antimicrobial activity. For the convenience of most experimental scientists who want to use the prediction method without the interest to follow the mathematical details, a user-friendly web-server is provided at http://amp.biosino.org/.
WOS标题词	Science & Technology
类目[WOS]	Multidisciplinary Sciences
研究领域[WOS]	Science & Technology - Other Topics
关键词[WOS]	AMINO-ACID-COMPOSITION ; PROTEIN STRUCTURAL CLASSES ; SUBCELLULAR LOCATION PREDICTION ; SECONDARY STRUCTURE-CONTENT ; DISCRETE WAVELET TRANSFORM ; COUPLED RECEPTOR CLASSES ; SUPPORT VECTOR MACHINE ; APPROXIMATE ENTROPY ; APOPTOSIS PROTEINS ; EVOLUTIONARY INFORMATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000289458800014
公开日期	2011-07-28
内容类型	期刊论文
源URL	[http://localhost/handle/0/48]
专题	天津工业生物技术研究所_基因组分析实验室陈祖耕_期刊论文
作者单位	1.Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Tianjin, Peoples R China 2.Shanghai Univ, Inst Syst Biol, Shanghai, Peoples R China 3.Shanghai Univ, Coll Sci, Dept Chem, Shanghai, Peoples R China 4.Univ Calif Los Angeles, Dept Human Genet, Los Angeles, CA USA 5.Gordon Life Sci Inst, San Diego, CA USA
推荐引用方式 GB/T 7714	Wang, Ping,Hu, Lele,Liu, Guiyou,et al. Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods[J]. PLOS ONE,2011,6(4):e18476.
APA	Wang, Ping.,Hu, Lele.,Liu, Guiyou.,Jiang, Nan.,Chen, Xiaoyun.,...&Chou, Kuo-Chen.(2011).Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods.PLOS ONE,6(4),e18476.
MLA	Wang, Ping,et al."Prediction of Antimicrobial Peptides Based on Sequence Alignment and Feature Selection Methods".PLOS ONE 6.4(2011):e18476.