Back to search

Article

Identification of important modules and biomarkers that related to immune cell in severe burns based on weighted gene co-expression network analysis(WGCNA)

2021-11-22

Abstract excerpt

<h4>Background: </h4> Immunosuppression is an important factor inducing infection which is a significant cause of death in severe burns. Nevertheless, the prognostic value of immune-related genes are still unclear. This study was conducted to find biomarkers related to immunosuppression in severe burns. Methods Here, we download the gene expression profile and clinical data of 185 burns and 75 healthy samples fro...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
0b4b8150-4413-5528-9a4d-91117eebd6ed
DOI
10.21203/rs.3.rs-1085273/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Identification of important modules and biomarkers that related to immune cell in severe burns based on weighted gene co-expression network analysis(WGCNA)DOI 10.21203/rs.3.rs-1085273/v1
Screening CEACAM8 and LCN2 as immune-related diagnostic biomarkers after burn to prevent serious complicationsSemantic proximity
Identification of differentially expressed oxidative stress-related genes in major burned patients and potential mechanisms based on hub genesSemantic proximity
Identification of potential hub genes associated with skin wound healing based on time course bioinformatic analysesSemantic proximity
Identification of key genes and immune profile in limited cutaneous systemic sclerosis-associated pulmonary arterial hypertension by bioinformatics analysisSemantic proximity
A burns and COVID-19 shared stress responding gene network deciphers CD1C-CD141-DCs as the key cellular components in septic prognosisSemantic proximity
Identification of Key Genes Related to Ankylosing Spondylitis Using WGCNA and Bioinformatics AnalysisSemantic proximity
Identification of potential hub genes associated with skin wound healing based on time course bioinformatic analysesSemantic proximity
Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) DatabaseSemantic proximity
Characterization of necroptosis and immune landscape in dermatomyositis by bioinformatics analysis and machine learningSemantic proximity
Identification of key genes and pathways associated with spinal cord injurySemantic proximity
Identification of Hub Genes and Key Pathways Associated with Sepsis Progression Using Weighted Gene Co-Expression Network Analysis and Machine LearningSemantic proximity
Identification of genes associated with liver ischemia-reperfusion injury after liver transplantation by WGCNA and PPI network analysesSemantic proximity
Select a neighboring publication to make it the new centre.