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Sequential Extraction of Several Gene-sets with Proper Groups of Individuals for Gene Expression Data Analysis
http://hdl.handle.net/10228/00007652
http://hdl.handle.net/10228/0000765209070a27-be30-43ef-86c3-c795ce8b6ffe
| 名前 / ファイル | ライセンス | アクション |
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SDMBHAE_Proceeding_p117-125.pdf (671.1 kB)
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| アイテムタイプ | 会議発表論文 = Conference Paper(1) | |||||||||||
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| 公開日 | 2020-03-10 | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| タイトル | ||||||||||||
| タイトル | Sequential Extraction of Several Gene-sets with Proper Groups of Individuals for Gene Expression Data Analysis | |||||||||||
| 言語 | en | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 著者 |
Badsha, Md. Bahadur
× Badsha, Md. Bahadur× Jahan, Nusrat× Mollah, Md. Nurul Haque× 倉田, 博之
WEKO
2130
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | One of the ultimate goals of microarray gene expression data analysis in bioinformatics is to identify individual genes or gene-sets which influence the gene expression patterns. There are several research areas in bioinformatics, where data analysis offers a challenging statistical problem due to their high dimensionality with small sample of sizes. Clustering is one of the most popular statistical techniques to addressing these challenges. Nowak and Tibshirani (2008) proposed complementary hierarchical clustering (CHC) for sequential exaction of several gene-sets having relatively low expressions than highly expressed genes. However it produces misleading clustering results for sequential exaction of several gene-sets if there exist some contaminations (outliers) in the gene expression data, which is an important issue in gene expression data analysis research field. Therefore, in this paper we proposed a robust statistical clustering technique based on the value of tuning parameter β, we called β- CHC for sequential extraction of biologically important gene-sets has similar expression patters with proper groups of individuals the genes expression data analysis in bioinformatics from the robustness points of view. The proposed robust method reduces to the traditional method when we put the value of tuning parameter β→0. Simulation gene expression data clustering results show that the performance of the proposed method is better than performance of the traditional method in the case of data contaminations; otherwise, it shows almost equal performance. | |||||||||||
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| 内容記述タイプ | Other | |||||||||||
| 内容記述 | International Conference on Statistical Data Mining for Bioinformatics Health Agriculture and Environment, 21-24 December, 2012, Rajshahi University, Bangladesh | |||||||||||
| 書誌情報 |
Proceedings of International Conference on Statistical Data Mining for Bioinformatics Health Agriculture and Environment (SDMBHAE 2012) p. 117-125, 発行日 2012-12-21 |
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| 出版社 | ||||||||||||
| 出版社 | Higher Education Quality Enhancement Program (HEQEP) | |||||||||||
| ISBN | ||||||||||||
| 識別子タイプ | ISBN | |||||||||||
| 関連識別子 | 978-984-33-5876-9 | |||||||||||
| 著作権関連情報 | ||||||||||||
| 権利情報 | Copyright (c) Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Gene expression | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | complementary hierarchical clustering based on β (β-CHC) | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Minimum β-divergence | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | Robustness | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | VoR | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||
| 査読の有無 | ||||||||||||
| 値 | no | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/265_ja.html | |||||||||||
| 論文ID（連携） | ||||||||||||
| 値 | 10275777 | |||||||||||
| 連携ID | ||||||||||||
| 値 | 5627 | |||||||||||
