SEQUENTIAL LINEAR NEIGHBORHOOD PROPAGATION FOR SEMI-SUPERVISED PROTEIN FUNCTION PREDICTION
文献类型：期刊论文
| 作者 | Wang, Jingyan（王靖琰） ; Li, Yongping（李勇平） |
| 刊名 | JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
 |
| 出版日期 | 2011 |
| 卷号 | 9期号:6页码:663 |
| ISSN号 | 0219-7200 |
| 英文摘要 | Predicting protein function is one of the most challenging problems of the post-genomic era. The development of experimental methods for genome scale analysis of molecular interaction networks has provided new approaches to inferring protein function. In this paper we introduce a new graph-based semi-supervised classification algorithm Sequential Linear Neighborhood Propagation (SLNP), which addresses the problem of the classification of partially labeled protein interaction networks. The proposed SLNP first constructs a sequence of node sets according to their shortest distance to the labeled nodes, and then predicts the function of the unlabel proteins from the set closer to labeled one, using Linear Neighborhood Propagation. Its performance is assessed on the Saccharomyces cerevisiae PPI network data sets, with good results compared with three current state-of-the-art algorithms, especially in settings where only a small fraction of the proteins are labeled. |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000297096300002 |
| 公开日期 | 2012-07-04 |
| 源URL | [http://ir.sinap.ac.cn/handle/331007/9584]  |
| 专题 | 上海应用物理研究所_中科院上海应用物理研究所2011-2017年 |
| 推荐引用方式 GB/T 7714 | Wang, Jingyan,Li, Yongping. SEQUENTIAL LINEAR NEIGHBORHOOD PROPAGATION FOR SEMI-SUPERVISED PROTEIN FUNCTION PREDICTION[J]. JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY,2011,9(6):663. |
| APA | Wang, Jingyan,&Li, Yongping.(2011).SEQUENTIAL LINEAR NEIGHBORHOOD PROPAGATION FOR SEMI-SUPERVISED PROTEIN FUNCTION PREDICTION.JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY,9(6),663. |
| MLA | Wang, Jingyan,et al."SEQUENTIAL LINEAR NEIGHBORHOOD PROPAGATION FOR SEMI-SUPERVISED PROTEIN FUNCTION PREDICTION".JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 9.6(2011):663. |
入库方式： OAI收割
来源：上海应用物理研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。