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| Content Provider | World Health Organization (WHO)-Global Index Medicus |
|---|---|
| Author | Yeu, Yunku Yoon, Youngmi Park, Sanghyun |
| Description | Author Affiliation: Yeu Y ( Department of Computer Science, Yonsei Univertity, 50 Yonsei-Ro, SeoDaeMun-Gu, Seoul 120-749, Republic of Korea. sanghyun@cs.yonsei.ac.kr.) |
| Abstract | Identifying alternative indications for known drugs is important for the pharmaceutical industry. Many computational methods have been proposed for predicting unknown associations between drugs and target proteins associated with diseases. To produce better prediction, researchers should not only develop accurate algorithms but identify good features that reflect intracellular systems. In this paper, we proposed a novel method for exploiting protein localization. We generated localization vectors (LVs) from protein localization and propagated LVs through a protein interaction network to increase the coverage of the localization information. The LVs showed distinct patterns among targets of known drugs as well as independent characteristics compared to existing features. Based on the experimental results, we determined that including LVs improves cross-validation accuracy and, produces better novel predictions with real and independent clinical trial data. Moreover, the propagation of LVs showed a positive result that it can help in increasing the coverage of the prediction results. |
| File Format | HTM / HTML |
| ISSN | 1742206X |
| Issue Number | 7 |
| Volume Number | 11 |
| e-ISSN | 17422051 |
| Journal | Molecular BioSystems |
| Language | English |
| Publisher | Royal Society of Chemistry |
| Publisher Date | 2015-07-01 |
| Publisher Place | Great Britain (UK) |
| Access Restriction | Subscribed |
| Subject Keyword | Discipline Molecular Biology Discipline Biochemistry Drug Repositioning Models, Biological Algorithms Area Under Curve Computational Biology Humans Molecular Targeted Therapy Protein Transport Journal Article Research Support, Non-u.s. Gov't |
| Content Type | Text |
| Resource Type | Article |
| Subject | Molecular Biology Biotechnology |
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