WikiPathways aims to capture the full diversity of biological pathway information as both human readable diagrams and computational models. Our pioneering approach, especially among biomedical databases, has been to dramatically decentralize collection and curation, opening the process up to any interested researcher or citizen scientist, while maintaining multiple tiers of quality assurance prior to distribution. The approach is working. In the midst of an already exceptional growth curve, we are now targeting new sources of published pathway information yet to be modeled by any other database and new onramps for researchers to become contributors. Further, we intend to make pathway information more accessible and relevant by supplying multiple image and data formats, and also by taking the time to integrate our pathway data with public and user datasets, semantic resources, publications, and bioinformatics workflows. These new inputs and output also depend on stable, scalable infrastructure, thus our aims: 1. To target new content streams from published figures and consortia, while also expanding the potential base of contributors and curators through innovative training systems and improved web-based pathway modeling tools. 2. To enhance research results through the integration of pathway information with specific datasets, resources and workflows, enabling custom visualizations, semantic queries, and enrichment analyses. 3. To provide researchers with a reliable set of services through specific software hardening and modularizing steps that will support scalable and sustainable hardware options. Over the next 5 years, we will redefine (yet again) what is expected from a pathway database by capturing the full diversity of biological pathway models and providing dynamic and integrated views of these pathway data.
Our aim to include more researchers in our collaborative pathway collection and curation process serves the database, and also will expose researchers to the direct benefits of open science practices. Ultimately, our goal remains to support and enhance efforts across all areas of biomedical and disease research. A comprehensive collection of pathway models continuously maintained by an open, collaborative process will provide valuable context and connections for diverse datasets.
Pathways are our best means of communicating the biology behind biomedical breakthroughs, drug activities, tumor types, aging, infection, heart disease and all other forms of disease. The WikiPathways project captures intuitive depictions of biological pathways by means of a collaborative wiki platform that simultaneous generates computational models for downstream data integration and analysis workflows. In this way, new ideas and revisions can be rapidly incorporated into diverse biomedical research efforts as hybrid models that convey pathway information equally well to data scientists, biologists, physicians, patients and students.
| Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina et al. (2018) WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res 46:D661-D667 |
| Bohler, Anwesha; Wu, Guanming; Kutmon, Martina et al. (2016) Reactome from a WikiPathways Perspective. PLoS Comput Biol 12:e1004941 |
| Waagmeester, Andra; Kutmon, Martina; Riutta, Anders et al. (2016) Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources. PLoS Comput Biol 12:e1004989 |
| Kutmon, Martina; Riutta, Anders; Nunes, Nuno et al. (2016) WikiPathways: capturing the full diversity of pathway knowledge. Nucleic Acids Res 44:D488-94 |
| Kutmon, Martina; van Iersel, Martijn P; Bohler, Anwesha et al. (2015) PathVisio 3: an extendable pathway analysis toolbox. PLoS Comput Biol 11:e1004085 |
| Kutmon, Martina; Lotia, Samad; Evelo, Chris T et al. (2014) WikiPathways App for Cytoscape: Making biological pathways amenable to network analysis and visualization. F1000Res 3:152 |
