Systematic Comparative Analysis of Pathway Databases from a User’s Perspective

Pathway Databases are essential particularly in the post-genomic era as they provide organized information about biological pathways and processes. However, there are too many pathway databases with varying features. These variations, stemming from multiple factors, create challenges for users in making objective selections among the databases. Hence, there is a need to systematically compare these databases from a user’s perspective. Indeed, there is a need to compile all such databases first. We first compiled pathway databases through a thorough literature search and shortlisted those suitable for human pathway studies. We designed a query set consisting of genes, pathways, and conditions and performed a quantitative comparison of the output from these shortlisted databases. Furthermore, to assess update frequency among the pathway databases, we curated potential novel genes involved in the MAPK pathway and compared them with the information available in pathway databases. The quantitative comparison of pathway databases showed that PathDIP yielded the highest number of pathways when queried with gene and condition names, followed by other databases. However, when queried for pathway names, Reactome yielded the highest number of pathways, followed by PathDIP, KEGG, and others. The results also support the notion that most scientists may have been making very arbitrary choice of pathway databases.