Integrative bioinformatic analyses of global transcriptome data decipher novel molecular insights into cardiac anti-fibrotic therapies

Fuchs M, Kreutzer FP, Kapsner L, Mitzka S, Just A, Perbellini F, Terracciano CM, Xiao K, Geffers R, Bogdan C, Prokosch HU, Fiedler J, Thum T, Kunz M (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Book Volume: 21

Pages Range: 1-11

Article Number: 4727

Journal Issue: 13

DOI: 10.3390/ijms21134727

Abstract

Integrative 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 backgroundThe 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. Importantlyour 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.

Authors with CRIS profile

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine United Kingdom (GB) Medizinische Hochschule Hannover (MHH) / Hannover Medical School Germany (DE) Helmholtz-Zentrum für Infektionsforschung (HZI) Germany (DE)

How to cite

APA:

Fuchs, M., Kreutzer, F.P., Kapsner, L., Mitzka, S., Just, A., Perbellini, F.,... Kunz, M. (2020). Integrative bioinformatic analyses of global transcriptome data decipher novel molecular insights into cardiac anti-fibrotic therapies. International Journal of Molecular Sciences, 21(13), 1-11. https://doi.org/10.3390/ijms21134727

MLA:

Fuchs, Maximilian, et al. "Integrative bioinformatic analyses of global transcriptome data decipher novel molecular insights into cardiac anti-fibrotic therapies." International Journal of Molecular Sciences 21.13 (2020): 1-11.

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