2020
DOI: 10.3389/fcell.2020.00252
|View full text |Cite
|
Sign up to set email alerts
|

Integrative Analysis for Elucidating Transcriptomics Landscapes of Glucocorticoid-Induced Osteoporosis

Abstract: Osteoporosis is the most common bone metabolic disease, characterized by bone mass loss and bone microstructure changes due to unbalanced bone conversion, which increases bone fragility and fracture risk. Glucocorticoids are clinically used to treat a variety of diseases, including inflammation, cancer and autoimmune diseases. However, excess glucocorticoids can cause osteoporosis. Herein we performed an integrated analysis of two glucocorticoid-related microarray datasets. The WGCNA analysis identified 3 and … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 36 publications
0
2
0
Order By: Relevance
“…Due to the heterogeneity between different datasets, the analysis results of different datasets may have certain differences ( Ying et al, 2020 ). The gene expression in different samples may be different ( Bao et al, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…Due to the heterogeneity between different datasets, the analysis results of different datasets may have certain differences ( Ying et al, 2020 ). The gene expression in different samples may be different ( Bao et al, 2021 ).…”
Section: Resultsmentioning
confidence: 99%
“…PPI network analysis has emerged as a useful approach to identifying potential new targets and mechanisms from a systematic perspective ( Wu et al, 2020 ). PPI network was constructed using the STRING database ( https://string-db.org ) ( Buttacavoli et al, 2020 ; Ying et al, 2020 ). The Cytoscape software was used to analyze the hub genes ( Szklarczyk et al, 2017 ).…”
Section: Methodsmentioning
confidence: 99%