Multi-label Learning for Predicting the Activities of Antimicrobial Peptides
文献类型：期刊论文
| 作者 | Pu Wang; Ruiquan Ge; Liming Liu; Xuan Xiao; Ye Li; Yunpeng Cai |
| 刊名 | Scientific Reports
 |
| 出版日期 | 2017 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Antimicrobial peptides (AMPs) are peptide antibiotics with a broad spectrum of antimicrobial activities. Activity prediction of AMPs from their amino acid sequences is of great therapeutic importance but imposes challenges on prediction methods due to label interactions. In this paper we propose a novel multi-label learning model to address this problem. A weighted K-nearest neighbor classifier is adopted for efficient representation learning of the sequence data. A multiple linear regression model is then employed to learn a mapping from the classifier score vectors to the target labels, with label correlations considered. Several popular multi-label learning algorithms and feature extraction methods were tested on a comprehensive, up-to-date AMP dataset with twelve biological activities covered and its filtered version with five activities covered. The experimental results showed that our proposed method has competitive performance with previous works and could be used as a powerful engine for activity prediction of AMPs. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/12602]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | Scientific Reports |
| 推荐引用方式 GB/T 7714 | Pu Wang,Ruiquan Ge,Liming Liu,et al. Multi-label Learning for Predicting the Activities of Antimicrobial Peptides[J]. Scientific Reports,2017. |
| APA | Pu Wang,Ruiquan Ge,Liming Liu,Xuan Xiao,Ye Li,&Yunpeng Cai.(2017).Multi-label Learning for Predicting the Activities of Antimicrobial Peptides.Scientific Reports. |
| MLA | Pu Wang,et al."Multi-label Learning for Predicting the Activities of Antimicrobial Peptides".Scientific Reports (2017). |
入库方式： OAI收割
来源：深圳先进技术研究院
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