Connect biological knowledge

This part treats GO, KEGG, Reactome, disease, MeSH, pathway collections, and custom annotations as knowledge sources for one common analysis system. The analysis engine from Part 1 remains the same while the vocabulary, annotation coverage, update schedule, and biological interpretation change.

How to choose a knowledge source

Need	Start with
Broad ontology-based functional coverage	GO
Curated pathways, modules, or compounds	KEGG or Reactome
Disease or phenotype concepts	Disease enrichment
Literature-oriented biomedical concepts	MeSH
A project-specific, unsupported, or multi-resource collection	Universal enrichment and GSON
Genomic regions that must first be mapped to genes	Genomic coordination enrichment

The shared knowledge contract

Every source should make its term-to-gene mapping, term names, identifier type, organism, release, and filtering rules explicit. A two-column TERM2GENE table is enough for an exploratory analysis; a versioned GSON object is preferable when the knowledge will be reused, shared, combined, or cited.

The domain chapters use the same pattern:

biological question → source and identifier contract → ORA/GSEA
                   → result object → visualization → limitations

Knowledge sources are not interchangeable evidence. GO terms, KEGG pathways, disease terms, and WikiPathways entries can differ in granularity and coverage. Combined plots should keep the source identity visible.