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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/10119/15263
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| タイトル: | A semi-supervised tensor regression model for siRNA efficacy prediction |
| 著者: | Thang, Bui Ngoc
Ho, Bao Tu
Kanda, Tatsuo |
| キーワード: | RNAi
siRNA
siRNA design rule
Tensor
Bilinear tensor regression
Semi–supervised learning |
| 発行日: | 2015-03-13 |
| 出版者: | BMC Central |
| 誌名: | BMC Bioinformatics |
| 巻: | 16 |
| 開始ページ: | 80 |
| DOI: | 10.1186/s12859-015-0495-2 |
| 抄録: | Background: Short interfering RNAs (siRNAs) can knockdown target genes and thus have an immense impact on biology and pharmacy research. The key question of which siRNAs have high knockdown ability in siRNA research remains challenging as current known results are still far from expectation.Results: This work aims to develop a generic framework to enhance siRNA knockdown efficacy prediction. The key idea is first to enrich siRNA sequences by incorporating them with rules found for designing effective siRNAs and representing them as enriched matrices, then to employ the bilinear tensor regression to predict knockdown efficacy of those matrices. Experiments show that the proposed method achieves better results than existing models in most cases. Conclusions: Our model not only provides a suitable siRNA representation but also can predict siRNA efficacy more accurate and stable than most of state–of–the–art models. Source codes are freely available on the web at: http://www.jaist.ac.jp/~bao/BiLTR/. |
| Rights: | Thang et al. BMC Bioinformatics (2015) 16:80, DOI : 10.1186/s12859-015-0495-2 © 2015 Thang et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
| URI: | http://hdl.handle.net/10119/15263 |
| 資料タイプ: | publisher |
| 出現コレクション: | a10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| 23948.pdf | | 875Kb | Adobe PDF | 見る/開く |
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