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Bioinformatic analysis of underlying mechanisms of Kawasaki disease via Weighted Gene Correlation Network Analysis (WGCNA) and the Least Absolute Shrinkage and Selection Operator method (LASSO) regression model
BACKGROUND: Kawasaki disease (KD) is a febrile systemic vasculitis involvingchildren younger than five years old. However, the specific biomarkers and precise mechanisms of this disease are not fully understood, which can delay the best treatment time, hence, this study aimed to detect the potential...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9951419/ https://www.ncbi.nlm.nih.gov/pubmed/36829193 http://dx.doi.org/10.1186/s12887-023-03896-4 |