ArticleInternational journal of experimental pathology2015
Microarray profiling analysis of long non-coding RNAs expression in tendinopathy: identification for potential biomarkers and mechanisms.
Article in International journal of experimental pathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Advances in non-coding RNA in tendon injuries.Frontiers in genetics · 2024Review
- LncRNA XIST Prevents Tendon Adhesion and Promotes Tendon Repair Through the miR-26a-5p/COX2 Pathway.Molecular biotechnology · 2022Article
- Analysis of the lncRNA-Associated Competing Endogenous RNA (ceRNA) Network for Tendinopathy.Genetics research · 2022Article
- Screening of key biomarkers of tendinopathy based on bioinformatics and machine learning algorithms.PloS one · 2021Article
- [Circular RNA expression pattern and competing endogenous RNA network involved in rotator cuff tendinopathy].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2020Article
- LncRNA TUG1 promoted osteogenic differentiation through promoting bFGF ubiquitination.In vitro cellular & developmental biology. Animal · 2020Article
- Identification of lncRNAs involved in biological regulation in early age-related macular degeneration.International journal of nanomedicine · 2017Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The role of lncRNAs in pathologies of tendinopathy has not been researched so far, this study aims to identify the role and potent mechanism of lncRNAs in tendinopathy with a bioinformatic analysis. The gene profile of GSE26051 based on the platform of Affymetrix Human Genome U133B Array condensed was downloaded from Gene Expression Omnibus. A total of 46 specimens (including 23 normal samples and 23 tendinopathy specimens) were available. Compared with the control samples, differentially expressed genes (DEGs) of tendinopathy was identified the by packages in R. The selected DEGs were further analysed using bioinformatics methods including co-expression and enrichment analysis to detect the potential role of lncRNAs. A total of 40 different expressed lncRNAs were identified. However, most of the identified lncRNAs have not been researched before. And this study only annotate one of the identified lncRNAs successfully, the LOC100507027 (myoregulin), with the potential role in regulating skeletal muscle tissue development and skeletal muscle organ development.
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