Summary:
- This article describes a new method for analyzing gene expression data using a novel computational approach called "Differential Gene Expression Analysis with Hierarchical Clustering" (DGEAHC).
- The DGEAHC method combines differential gene expression analysis with hierarchical clustering to identify clusters of genes that are co-expressed and differentially expressed between different experimental conditions.
- The authors demonstrate the effectiveness of the DGEAHC method by applying it to several publicly available gene expression datasets, showing that it can identify biologically relevant gene clusters and pathways that are associated with specific phenotypes or disease states.