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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yu, Fengying Yang, Zhihao Hu, Xiaohua Sun, Yuanyuan Lin, Hongfei Wang, Jian |
| Copyright Year | 2014 |
| Description | Author affiliation: College of Computer Science and Technology, Dalian University of Technology, Dalian, China 116024 (Yu, Fengying; Yang, Zhihao; Sun, Yuanyuan; Lin, Hongfei; Wang, Jian) || College of Computing & Informatics, Drexel University, Philadelphia, PA 19104 USA (Hu, Xiaohua) |
| Abstract | The rapidly growing biomedical literature provides a significantly large and readily available source of PPI data. In this paper, we present supervised learning and data integration based complex detection approach. In this approach, a sophisticated natural language processing system, PPIExtractor, is employed to extract new PPI interactions from biomedical literature which are then integrated into original PPI networks. Then a supervised learning model, built by via of the information of available known complexes, is used in the multiple complex detection stages, e.g. the cliques filtering, growth, and candidate complex filtering. The experimental results on three yeast PPI networks demonstrate the effectiveness of our approach. |
| Starting Page | 144 |
| Ending Page | 149 |
| File Size | 222458 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479956692 |
| DOI | 10.1109/BIBM.2014.6999143 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-11-02 |
| Publisher Place | United Kingdom |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Proteins Protein engineering Gold Protein-protein interaction network Noise reduction Supervised learning Reliability Standards Gene Ontology Electronics packaging Protein complexes |
| Content Type | Text |
| Resource Type | Article |
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