The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19537258

Qian Yan (2022): Transcriptomic analysis of human bronchial epithelium reveals unique immune landscape in severe asthma. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19537258.v1

Dataset

• Medical Biotechnology
• Immunology

Gene set enrichment analysis (GSEA), Immune infiltration, Severe asthma, Single-sample GSEA (ssGSEA), ssGSEA, Weighted gene coexpression network analysis

2022.4.9

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Qian Yan

Airway epithelial transcriptome analysis of severe asthma (SA) patients was used to identify the immune infiltration mechanisms that affect asthma exacerbation, which may contribute to improving asthma therapy. A serises of bioinformatics methods were utilized to identify the hub genes and signaling pathways in SA. 

• 2022-04-13 first online, published, posted

4TU.ResearchData

.zip

• This work was supported by the Science and Technology Program of Guangzhou, China (Grant no. 201904010235), and the National Natural Science Foundation of Guangdong, China (Grant no. 2020A1515010589 and Grant no. 2021A1515010146). This work was also supported by the “Double First-Class” and High-level University Discipline Collaborative Innovation Team Project of Guangzhou University of Chinese Medicine (Grant No.2021XK16), Guangdong Provincial Department of Education Innovation Team Project (Grant No: 2018KCXTD007), the Key-Area Research and Development Program of Guangdong Province (Grant No. 2020B1111100002), the National Natural Science Foundation of China (Grant No. 81973814 and No. 81904132), and the Technology Research of COVID-19 Treatment and Prevention and Special Project of Traditional Chinese Medicine Application-Research on the platform construction for the prevention and treatment of viral infectious diseases with traditional Chinese medicine (Grant No. 2020KJCX-KTYJ-130).

Guangzhou University of Chinese Medicine