Predicting Drug-Target Interactions between New Drugs and New Targets via Pairwise K-Nearest Neighbor and Automatic Similarity Selection
文献类型：会议论文
| 作者 | Jianyu Shi; Jaixin Li; Huimeng Lu; Yong Zhang |
| 出版日期 | 2015 |
| 会议名称 | IScIDE 2015 |
| 会议地点 | Suzhou, China |
| 英文摘要 | Predicting drug-target interaction (DTI) by computational methods has gained more and more concerns in both drug discovery and repositioning. However, several inherent difficulties in DTI data have not yet been addressed appropriately, including the powerless prediction of interactions for new drugs and/or new targets, the biased predicting model derived from imbalanced samples and the inadequate solution to missing interactions and multiple similarities. Moreover, assessed on inappropriate scenarios, existing methods may generate over-optimistic predictions. In this paper, we predict the potential interactions between new drugs and new targets based on pairwise K-nearest neighbor. With lower computational complexity, the proposed approach is able to obtain the less biased prediction and to relax the difficulty caused by missing interactions. Moreover, we develop a strategy to automatically select the best among multiple similarities to train classifiers. Based on four benchmark datasets, the effectiveness of our approach is demonstrated by an appropriate cross validation. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/6974]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2015 |
| 推荐引用方式 GB/T 7714 | Jianyu Shi,Jaixin Li,Huimeng Lu,et al. Predicting Drug-Target Interactions between New Drugs and New Targets via Pairwise K-Nearest Neighbor and Automatic Similarity Selection[C]. 见:IScIDE 2015. Suzhou, China. |
入库方式： OAI收割
来源：深圳先进技术研究院
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