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Updated: Jun 20, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Automated seeding of specialised wiki knowledgebases with BioKb
Jonathan R Manning1, Ann Hedley, John J Mullins
1Centres for Cardiovascular Science and Inflammation Research, Queen's Medical Research Institute, University of Edinburgh, EH16 4TJ, UK. jmanning@staffmail.ed.ac.uk
Background:
Wiki technology has become a ubiquitous mechanism for dissemination of information, and places strong emphasis on collaboration. We aimed to leverage wiki technology to allow small groups of researchers to collaborate around a specific domain, for example a biological pathway. Automatically gathered seed data could be modified by the group and enriched with domain specific information.
Results:
We describe a software system, BioKb, implemented as a plugin for the TWiki engine, and designed to facilitate construction of a field-specific wiki containing collaborative and automatically generated content. Features of this system include: query of publicly available resources such as KEGG, iHOP and MeSH, to generate 'seed' content for topics; simple definition of structure for topics of different types via an administration page; and interactive incorporation of relevant PubMed references. An exemplar is shown for the use of this system, in the creation of the RAASWiki knowledgebase on the renin-angiotensin-aldosterone system (RAAS). RAASWiki has been seeded with data by use of BioKb, and will be the subject of ongoing development into an extensive knowledgebase on the RAAS.
Conclusion:
The BioKb system is available from http://www.bioinf.mvm.ed.ac.uk/twiki/bin/view/TWiki/BioKbPlugin as a plugin for the TWiki engine.
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