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Verfasst von:Schwingen, Julius [VerfasserIn]   i
 Kaplan, Mustafa [VerfasserIn]   i
 Kurschus, Florian [VerfasserIn]   i
Titel:Review
Titelzusatz:current concepts in inflammatory skin diseases evolved by transcriptome analysis : in-depth analysis of atopic dermatitis and psoriasis
Verf.angabe:Julius Schwingen, Mustafa Kaplan and Florian C. Kurschus
E-Jahr:2020
Jahr:21 January 2020
Teil:volume:21
 year:2020
 number:3
Fussnoten:Gesehen am 11.05.2020
Titel Quelle:Enthalten in: International journal of molecular sciences
Ort Quelle:Basel : Molecular Diversity Preservation International, 2000
Jahr Quelle:2020
Band/Heft Quelle:21(2020,3) Artikel-Nummer 699, 39 Seiten
ISSN Quelle:1422-0067
 1661-6596
Abstract:During the last decades, high-throughput assessment of gene expression in patient tissues using microarray technology or RNA-Seq took center stage in clinical research. Insights into the diversity and frequency of transcripts in healthy and diseased conditions provide valuable information on the cellular status in the respective tissues. Growing with the technique, the bioinformatic analysis toolkit reveals biologically relevant pathways which assist in understanding basic pathophysiological mechanisms. Conventional classification systems of inflammatory skin diseases rely on descriptive assessments by pathologists. In contrast to this, molecular profiling may uncover previously unknown disease classifying features. Thereby, treatments and prognostics of patients may be improved. Furthermore, disease models in basic research in comparison to the human disease can be directly validated. The aim of this article is not only to provide the reader with information on the opportunities of these techniques, but to outline potential pitfalls and technical limitations as well. Major published findings are briefly discussed to provide a broad overview on the current findings in transcriptomics in inflammatory skin diseases.
DOI:doi:10.3390/ijms21030699
URL:Kostenfrei: Volltext ; Verlag: https://doi.org/10.3390/ijms21030699
 Kostenfrei: Volltext: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037913/
 DOI: https://doi.org/10.3390/ijms21030699
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1697873235
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