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| 題名: | A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology |
| 作者: | 洪炯宗;Chang, Tzu-Hao;Wu, Shih-Lin;Wang, Wei-Jen;Horng, Jorng-Tzong;Chang, Cheng-Wei |
| 貢獻者: | 資訊電機學院資訊工程學系 |
| 關鍵詞: | Algorithms;Breast cancer;Cellular signal transduction;Cloud computing;Computational Biology;Computer science;Datasets;DNA microarrays;Gene expression;Gene Expression Profiling;Genetic aspects;Genomics;Health aspects;Humans;Identification and classification;Informatics;Methods;Oligonucleotide Array Sequence Analysis;Performance evaluation;Software |
| 日期: | 2014-02-17 |
| 上傳時間: | 2026-04-23 13:07:50 (UTC+8) |
| 出版者: | Hindawi Publishing Corporation;Cairo, Egypt: Hindawi Puplishing Corporation |
| 摘要: | 摘要： Microarrays are widely used to assess gene expressions. Most microarray studies focus primarily on identifying differential gene expressions between conditions (e.g., cancer versus normal cells), for discovering the major factors that cause diseases. Because previous studies have not identified the correlations of differential gene expression between conditions, crucial but abnormal regulations that cause diseases might have been disregarded. This paper proposes an approach for discovering the condition-specific correlations of gene expressions within biological pathways. Because analyzing gene expression correlations is time consuming, an Apache Hadoop cloud computing platform was implemented. Three microarray data sets of breast cancer were collected from the Gene Expression Omnibus, and pathway information from the Kyoto Encyclopedia of Genes and Genomes was applied for discovering meaningful biological correlations. The results showed that adopting the Hadoop platform considerably decreased the computation time. Several correlations of differential gene expressions were discovered between the relapse and nonrelapse breast cancer samples, and most of them were involved in cancer regulation and cancer-related pathways. The results showed that breast cancer recurrence might be highly associated with the abnormal regulations of these gene pairs, rather than with their individual expression levels. The proposed method was computationally efficient and reliable, and stable results were obtained when different data sets were used. The proposed method is effective in identifying meaningful biological regulation patterns between conditions.
其他題名： Biomed Res Int
出版者： Cairo, Egypt: Hindawi Puplishing Corporation
出版日期： 2014-01-01
出處： BioMed research international, 2014-01, Vol.2014 (2014), p.1-8
資源來源： Publicly Available Content Database
版權： Copyright © 2014 Tzu-Hao Chang et al.
版權： COPYRIGHT 2014 John Wiley & Sons, Inc.
版權： Copyright © 2014 Tzu-Hao Chang et al. Tzu-Hao Chang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
版權： Copyright © 2014 Tzu-Hao Chang et al. 2014
識別號： ISSN: 2314-6133
識別號： ISSN: 2314-6141
識別號： EISSN: 2314-6141
識別號： DOI: 10.1155/2014/763237
識別號： PMID: 24579087 |
| 顯示於類別: | [資訊工程學系] 期刊論文
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