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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/7790
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| タイトル: | A Semi-supervised Learning Approach to Disease Gene Prediction |
| 著者: | Nguyen, Thanh Phuong
Ho, Tu Bao |
| 発行日: | 2007-11 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | IEEE International Conference on Bioinformatics and Biomedicine, 2007. BIBM 2007. |
| 開始ページ: | 423 |
| 終了ページ: | 428 |
| DOI: | 10.1109/BIBM.2007.30 |
| 抄録: | Discovering human disease-causing genes (disease genes in short) is one of the most challenging problems in bioinformatics and biomedicine, as most diseases are related in some way to our genes. Various methods have been proposed to exploit existing data sources for solving the problem. We aim to develop a novel method to predict disease genes that takes into account the imbalance between known disease genes and unknown disease genes. To this end, our method makes the best of semi-supervised learning, integrating data of human protein-protein interactions and various biological data extracted from multiple proteomic/genomic databases. Experimental evaluation shows high performance of our proposed method. Also, a considerable number of potential disease genes were discovered. |
| Rights: | Copyright (C) 2007 IEEE. Reprinted from IEEE International Conference on Bioinformatics and Biomedicine, 2007. BIBM 2007. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. |
| URI: | http://hdl.handle.net/10119/7790 |
| 資料タイプ: | publisher |
| 出現コレクション: | a11-1. 会議発表論文 (Conference Papers)
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このアイテムのファイル:
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記述 |
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| A10940.pdf | | 206Kb | Adobe PDF | 見る/開く |
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