Table 4.

Advantages, disadvantages, and context for the main bioinformatic databases for analyzing biological pathways.

Database	Advantages	Disadvantages	Context of Use
WikiPathways [103]	Community-curated content; intuitive user interface; regular updates; open platform.	Limited coverage of less common species in research.	Useful for collaborative research and pathway analysis, particularly suitable for systems biology and omics studies.
KEGG [116], [117]	Extensive integrated data collection; detailed pathway information; analysis and mapping tools; broad species coverage.	Limited access to advanced features for non-registered users; interface not very intuitive.	Extensive use in bioinformatics for pathway analysis and genomic research, metabolomics and multi-omics data integration; used in a wide range of biological and medical studies.
GO [105]	Annotation of genes and proteins in many species; extensive integration with numerous other bioinformatic tools; tripartite structure covering biological processes, cellular components, and molecular functions.	Requires understanding of specific ontological categories for effective use; may not cover all possible gene functions, especially in less-studied species.	Used in a wide range of bioinformatic studies for functional annotation; particularly useful to identify underlying biological mechanisms; applied in comparative and functional studies across different species.
Reactome [120]	High-quality curated data; good data integration and visualization; biological event-oriented approach.	Mainly human-centred coverage; less detail for other species.	Preferred for studies on biological pathways and processes, especially in humans.
STRING [107]	Extensive database of protein interactions; integration of different data sources; user-friendly interface.	Possible false positives in predicted interactions; require experimental validation.	Used for the analysis of protein interaction networks and for proteomics studies.
Panther Pathways [122]	Integration of functional and evolutionary data; based on standardized ontologies; use of familiar gene models.	Limited coverage compared to other databases; more recent data may be missing.	Suitable for evolutionary and functional analyses of genes and proteins.
Biocarta [110]	Specificity in pathway detail; curated data.	Not frequently updated; limited coverage.	Used for detailed analysis of specific biological pathways, especially in biomedical studies.
HumanCyc [111]	Dedicated to human biochemistry; detailed in metabolic pathways; based on curated data.	Focused exclusively on humans; requires an understanding of biochemistry for effective use.	Used for the in-depth study of human metabolic pathways, particularly useful in biochemical and metabolomics research.