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Background Sepsis represents a complex disease with the dysregulated inflammatory response and high mortality rate. The goal of this study was to identify potential transcriptomic markers in developing pediatric sepsis by a co-expression module analysis of the transcriptomic dataset. Methods Using the R software and Bioconductor packages, we performed a weighted gene co-expression network analysis...
The goal of this study was to identify potential transcriptomic markers in developing asthma by an integrative analysis of multiple public microarray data sets. Using the R software and bioconductor packages, we performed a statistical analysis to identify differentially expressed (DE) genes in asthma, and further performed functional interpretation (enrichment analysis and co-expression network construction)...
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