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

By D. Slenter, Martina Kutmon, Kristina Hanspers, Anders Riutta, Jacob Windsor, Nuno Nunes, Jonathan Mélius, Elisa Cirillo, S. Coort, Daniela Digles and 12 more. Nucleic Acids Res., 2017

834 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/0d781b636f64d1ef5a68f00d6aff99e4a4cc9a77

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Sunghwan Kim
2. Evan E. Bolton
3. Jian Zhang
4. Bo Yu
5. Yuxing Liao
6. Siqian He
7. Zhiao Shi
8. Martina Kutmon

Citations in the corpus

• PubChem in 2021: new data content and improved web interfaces (2020, background): “All pathway records were integrated from existing pathway resources (34,51–59) without any attempt to merge or combine them, meaning that a pathway may have multiple records within PubChem, with each originating from a different source.”
• Metabolomics and Multi-Omics Integration: A Survey of Computational Methods and Resources (2020, methodology): “Finally, WikiPathways [238] has quality tags that can be used to indicate confidence (e.g., ProposedDeletion, WormBase_Approved, Reactome_Approved, and Hypothetical).”
• gprofiler2 -- an R package for gene list functional enrichment analysis and namespace conversion toolset g:Profiler (2020, methodology): “How is the ordering of pathways in for KEGG, Reactome, and WikiPathways defined?”
• The DisGeNET knowledge platform for disease genomics: 2019 update (2019, methodology): “By performing federated queries to jointly interrogate DisGeNET-RDF and WikiPathways (28), it is possible to identify the pathways associated with the disease (Figure 6D).”
• WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs (2019, methodology): “…updates to upstream data sources, a few new databases were added in WebGestalt 2019 (Table 1), including a cancer-related subset of WikiPathways (7), co-expression network modules derived from cancer proteomics datasets from CPTAC (Clinical Proteomic Tumor Analysis Consortium), the protein…”
• WikiPathways: connecting communities (2020, methodology): “Quality assurance of the WikiPathways content is accomplished continuously, by a combination of a weekly manual curation by a member of an organized team of curators, computer-assisted curation processes (7) and monthly curation cafes.”
• g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update) (2019, background): “We have introduced with this update WikiPathways (21) as a complementary pathway data source.”
• Cellular and inter-cellular rewiring of the human colon during ulcerative colitis (2019, methodology): “, 2015) and the OSM pathway was obtained from WikiPathways (Slenter et al., 2018).”
• MIENTURNET: an interactive web tool for microRNA-target enrichment and network-based analysis (2019, methodology): “For this analysis, currently the choice is among the following annotation databases: KEGG pathways [33], Reactome [34], WikiPathways [35] and Disease Ontology [36] (only with Homo sapiens).”