Towards rule-based metabolic databases: a requirement analysis based on KEGG

Author(s): Richter, S., I. Fetzer, M. Thullner, F. Centler, P. Dittrich
In: International Journal of Data Mining and Bioinformatics 13: 289–319
Year: 2015
Type: Journal / article
Theme affiliation: Patterns of the Anthropocene
Link to centre authors: Fetzer, Ingo
Full reference: Richter, S., I. Fetzer, M. Thullner, F. Centler, P. Dittrich. 2015. Towards rule-based metabolic databases: A requirement analysis based on KEGG. International Journal of Data Mining and Bioinformatics 13: 289–319.


Knowledge of metabolic processes is collected in easily accessible online databases which are increasing rapidly in content and detail. Using these databases for the automatic construction of metabolic network models requires high accuracy and consistency. In this bipartite study we evaluate current accuracy and consistency problems using the KEGG database as a prominent example and propose design principles for dealing with such problems.

In the first half, we present our computational approach for classifying inconsistencies and provide an overview of the classes of inconsistencies we identified. We detected inconsistencies both for database entries referring to substances and entries referring to reactions. In the second part, we present strategies to deal with the detected problem classes.

We especially propose a rule-based database approach which allows for the inclusion of parameterised molecular species and parameterised reactions. Detailed case-studies and a comparison of explicit networks from KEGG with their anticipated rule-based representation underline the applicability and scalability of this approach.


Stockholm Resilience Centre is a collaboration between Stockholm University and the Beijer Institute of Ecological Economics at the Royal Swedish Academy of Sciences

Stockholm Resilience Centre
Stockholm University, Kräftriket 2B
Phone: +46 8 674 70 70

Organisation number: 202100-3062
VAT No: SE202100306201