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dc.contributor.authorFuchs, Maximilian
dc.contributor.authorKreutzer, Fabian Philipp
dc.contributor.authorKapsner, Lorenz A
dc.contributor.authorMitzka, Saskia
dc.contributor.authorJust, Annette
dc.contributor.authorPerbellini, Filippo
dc.contributor.authorTerracciano, Cesare M
dc.contributor.authorXiao, Ke
dc.contributor.authorGeffers, Robert
dc.contributor.authorBogdan, Christian
dc.contributor.authorProkosch, Hans-Ulrich
dc.contributor.authorFiedler, Jan
dc.contributor.authorThum, Thomas
dc.contributor.authorKunz, Meik
dc.date.accessioned2020-07-29T11:19:56Z
dc.date.available2020-07-29T11:19:56Z
dc.date.issued2020-07-02
dc.identifier.citationInt J Mol Sci. 2020;21(13):4727. Published 2020 Jul 2. doi:10.3390/ijms21134727.en_US
dc.identifier.pmid32630753
dc.identifier.doi10.3390/ijms21134727
dc.identifier.urihttp://hdl.handle.net/10033/622371
dc.description.abstractIntegrative bioinformatics is an emerging field in the big data era, offering a steadily increasing number of algorithms and analysis tools. However, for researchers in experimental life sciences it is often difficult to follow and properly apply the bioinformatical methods in order to unravel the complexity and systemic effects of omics data. Here, we present an integrative bioinformatics pipeline to decipher crucial biological insights from global transcriptome profiling data to validate innovative therapeutics. It is available as a web application for an interactive and simplified analysis without the need for programming skills or deep bioinformatics background. The approach was applied to an ex vivo cardiac model treated with natural anti-fibrotic compounds and we obtained new mechanistic insights into their anti-fibrotic action and molecular interplay with miRNAs in cardiac fibrosis. Several gene pathways associated with proliferation, extracellular matrix processes and wound healing were altered, and we could identify micro (mi) RNA-21-5p and miRNA-223-3p as key molecular components related to the anti-fibrotic treatment. Importantly, our pipeline is not restricted to a specific cell type or disease and can be broadly applied to better understand the unprecedented level of complexity in big data research.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectalgorithmen_US
dc.subjectbig dataen_US
dc.subjectcardiac fibrosisen_US
dc.subjectintegrative bioinformaticsen_US
dc.subjectmiRNAsen_US
dc.subjectnatural compoundsen_US
dc.subjecttranscriptomicsen_US
dc.subjectweb applicationen_US
dc.titleIntegrative Bioinformatic Analyses of Global Transcriptome Data Decipher Novel Molecular Insights into Cardiac Anti-Fibrotic Therapies.en_US
dc.typeArticleen_US
dc.identifier.eissn1422-0067
dc.contributor.departmentHZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.en_US
dc.identifier.journalInternational journal of molecular sciencesen_US
dc.source.volume21
dc.source.issue13
refterms.dateFOA2020-07-29T11:19:57Z
dc.source.journaltitleInternational journal of molecular sciences
dc.source.countrySwitzerland


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