Background: Global or untargeted metabolomics is widely used to comprehensively
investigate metabolic profiles under various pathophysiological conditions such as …

Gene set analysis methods are widely used to provide insight into high-throughput gene
expression data. There are many gene set analysis methods available. These methods rely …

Gene set enrichment (GSE) analysis plays an essential role in extracting biological insight
from genome-scale experiments. ORA (overrepresentation analysis), FCS (functional class …

WebGestalt is a popular tool for the interpretation of gene lists derived from large scale-
omics studies. In the 2019 update, WebGestalt supports 12 organisms, 342 gene identifiers …

Biological data analysis often deals with lists of genes arising from various studies. The g:
Profiler toolset is widely used for finding biological categories enriched in gene lists …

Pathway enrichment analysis helps researchers gain mechanistic insight into gene lists
generated from genome-scale (omics) experiments. This method identifies biological …

Abstract The Gene Ontology resource (GO; http://geneontology. org) provides structured,
computable knowledge regarding the functions of genes and gene products. Founded in …

Motivation Gene lists are routinely produced from various omic studies. Enrichment analysis
can link these gene lists with underlying molecular pathways and functional categories such …

With the rapid adoption of high-throughput omic approaches to analyze biological samples
such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can …

Functional enrichment analysis has played a key role in the biological interpretation of high-
throughput omics data. As a long-standing and widely used web application for functional …