FuncExplorer

FuncExplorer performs hierarchical clustering and functional enrichment analysis of high-throughput genomic datasets to identify functionally related gene groups and annotate clusters using ontology and pathway databases.

Key Features:

• Automated Hierarchical Clustering: Performs hierarchical clustering of gene expression profiles to identify co-expressed and functionally related gene groups.
• Functional Enrichment Analysis: Conducts enrichment analysis of clusters using structured knowledge from Gene Ontology (GO), KEGG, Reactome, Human Protein Atlas, and Human Phenotype Ontology.

Scientific Applications:

• Gene Expression Studies: Identify clusters of co-expressed genes and infer their potential biological roles from enrichment results.
• Pathway Analysis: Map gene clusters to KEGG and Reactome pathways to interpret underlying molecular mechanisms.
• Comparative Genomics: Compare cluster annotations with published datasets for validation and refinement of findings.

Methodology:

Combines hierarchical clustering with enrichment analysis using structured knowledge from Gene Ontology (GO), KEGG, Reactome, Human Protein Atlas, and Human Phenotype Ontology.