WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research

TLDR

WikiPathways is a collaborative, web‑based pathway database widely used for analyzing experimental data, but until recently it focused mainly on genes and proteins, leaving many metabolites poorly annotated. The authors aim to provide a curated, machine‑readable WikiPathways database that enables omics data analysis and visualization, and to enhance interoperability through OpenAPI documentation and FAIR annotation of resources. The authors achieved this by curating metabolic pathways, linking unmapped metabolites to database identifiers, enriching interaction knowledge, and exposing the data via OpenAPI services with FAIR annotations. As a result, WikiPathways has grown in size and accuracy, doubling its annotated metabolite nodes, and now offers new search options, monthly downloads, expanded database links, and portals that make pathway knowledge more accessible to researchers.

Abstract

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities.