A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106077

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106077

Title:	A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology
Authors:	王尉任;Chang, Tzu-Hao;Wu, Shih-Lin;Wang, Wei-Jen;Horng, Jorng-Tzong;Chang, Cheng-Wei
Contributors:	資訊電機學院資訊工程學系
Keywords:	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
Date:	2014-02-17
Issue Date:	2026-04-23 13:07:45 (UTC+8)
Publisher:	Hindawi Publishing Corporation;Cairo, Egypt: Hindawi Puplishing Corporation
Abstract:	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
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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