Enrichment analysis is a computational method used in bioinformatics to identify functional categories or biological pathways that are overrepresented in a list of genes or proteins. This approach helps researchers to gain insight into the biological significance of their experimental results, by highlighting potential associations between the input genes and relevant biological functions or processes. Enrichment analysis is widely used in various fields of biological research, including genomics, transcriptomics, proteomics, and metabolomics, to interpret large-scale omics data and prioritize candidate genes or pathways for further investigation.