A knowledge-based approach for modelling biochemical reaction networks

The modelling of biochemical systems requires knowledge of which species are present and which reactions can take place. If this knowledge is incomplete and there are reactions or species which are not considered then the models built will not accurately represent the physics and chemistry underlying the system. Known reactions can be found from databases for organisms (such as e. coli) from which pathways are built [1]. However these databases do not contain all possible reactions and the unknown reactions can form new pathways or fill gaps in existing pathways. This work aims to construct computer-based methods for generating reactions and pathways for metabolic networks. This is especially important for new/unknown systems where reaction pathways, binding species, reaction inhibitors and intermediate products are not necessarily known and consequently have not been tabulated in databases.