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HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis

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dc.contributor.authorAhn, Hongryul-
dc.contributor.authorJung, Inuk-
dc.contributor.authorChae, Heejoon-
dc.contributor.authorKang, Dongwon-
dc.contributor.authorJung, Woosuk-
dc.contributor.authorKim, Sun-
dc.date.available2021-02-22T05:36:22Z-
dc.date.issued2019-12-
dc.identifier.issn1471-2105-
dc.identifier.urihttps://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2707-
dc.description.abstractBackground Integrated analysis that uses multiple sample gene expression data measured under the same stress can detect stress response genes more accurately than analysis of individual sample data. However, the integrated analysis is challenging since experimental conditions (strength of stress and the number of time points) are heterogeneous across multiple samples. Results HTRgene is a computational method to perform the integrated analysis of multiple heterogeneous time-series data measured under the same stress condition. The goal of HTRgene is to identify "response order preserving DEGs" that are defined as genes not only which are differentially expressed but also whose response order is preserved across multiple samples. The utility of HTRgene was demonstrated using 28 and 24 time-series sample gene expression data measured under cold and heat stress in Arabidopsis. HTRgene analysis successfully reproduced known biological mechanisms of cold and heat stress in Arabidopsis. Also, HTRgene showed higher accuracy in detecting the documented stress response genes than existing tools. Conclusions HTRgene, a method to find the ordering of response time of genes that are commonly observed among multiple time-series samples, successfully integrated multiple heterogeneous time-series gene expression datasets. It can be applied to many research problems related to the integration of time series data analysis.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherBMC-
dc.titleHTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1186/s12859-019-3072-2-
dc.identifier.scopusid2-s2.0-85075842535-
dc.identifier.wosid000499935900003-
dc.identifier.bibliographicCitationBMC BIOINFORMATICS, v.20, pp 1 - 14-
dc.citation.titleBMC BIOINFORMATICS-
dc.citation.volume20-
dc.citation.startPage1-
dc.citation.endPage14-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.subject.keywordPlusTRANSCRIPTION FACTOR-
dc.subject.keywordPlusRNA-SEQ-
dc.subject.keywordPlusBIOCONDUCTOR PACKAGE-
dc.subject.keywordPlusFUNCTIONAL-ANALYSIS-
dc.subject.keywordPlusEXPRESSION-
dc.subject.keywordPlusTHERMOTOLERANCE-
dc.subject.keywordPlusACCLIMATION-
dc.subject.keywordPlusDOWNSTREAM-
dc.subject.keywordPlusGENOMICS-
dc.subject.keywordPlusDROUGHT-
dc.subject.keywordAuthorIntegration analysis-
dc.subject.keywordAuthorMultiple time-series gene expression data-
dc.subject.keywordAuthorStress response-
dc.subject.keywordAuthorResponse order preserving DEG-
dc.identifier.urlhttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-3072-2-
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공과대학 (소프트웨어학부(첨단))
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