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Updated: Jun 30, 2026
09:50
Biosynthesis of a Flavonol from a Flavanone by Establishing a One-pot Bienzymatic Cascade
Published on: August 14, 2019
Search extension transforms Wiki into a relational system: a case for flavonoid metabolite database
Masanori Arita1, Kazuhiro Suwa
1Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha 5-1-5 CB05, Kashiwa, Japan. arita@k.u-tokyo.ac.jp
Biodata Mining
|September 30, 2008
Summary
We developed a novel Wiki-based database system for biology, combining flexible data entry with structured querying. This approach enhances biological data management and accessibility for researchers.
Area of Science:
- Computer Science
- Bioinformatics
- Cheminformatics
Background:
- Traditional biological databases often use loosely formatted text files, lacking systematic query mechanisms like SQL.
- Relational database models, established in computer science, offer structured querying but can be rigid for complex biological data.
Purpose of the Study:
- To integrate the flexibility of Wiki-based systems with the structured querying capabilities of relational databases for biological data.
- To develop a novel database system that accommodates both free-formatted and structured biological information.
Main Methods:
- Implementation of embeddable string-search commands within a Wiki-based system.
- Design of a half-formatted database structure.
- Development using PHP as a MediaWiki extension.
- Creation of a flavonoid database with 6902 molecular structures from 1687 plant species.
Main Results:
- A functional Wiki-based database system was created, demonstrating proof of principle.
- The system allows registered users to enter data in arbitrary formats.
- Structured data sections support text-string searches for relational operations.
- The flavonoid database serves as a comprehensive resource.
Conclusions:
- The proposed scheme merges the advantages of free-formatted Wiki style and structured relational database style.
- MediaWiki facilitates multi-user document management, reducing database maintenance costs.
- This approach enhances biological data accessibility and management.
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