Constructing an enzyme-centric view of metabolism.

Motivation: The current paradigm for viewing metabolism, such as the Boehringer Chart or KEGG, takes a metabolite-centric view that is not ideal for genomics analysis because the same enzyme can appear in multiple places. Therefore an enzyme-centric view is also required. Results: We have eliminated synonymous compound names taken from the ENZYME database ensuring that it is computationally parseable at all levels. Based on these results, we have written a software to create enzyme-centric graphs from reaction data, and we have created a second dataset with hub molecules removed, allowing a greater depth of information to be extracted from these graphs. We also present a detailed analysis of the various stages of the reconditioning process and the characteristics of the subgraphs resulting from the application of our software to the revised datasets. Availability: Complete datasets and supplementary material may be downloaded from http://helix.ex.ac.uk/metabolism. The software for the creation of enzyme-centric graphs from reaction data is available on request from the authors

The implications for Bioinformatics of integration across physical scales

Bioinformatics blossomed with research developments in molecular biology. But as the focus of research moves back up the physical scale to the biology of whole multicellular organisms, there are new integration challenges. Data integration is a perennial theme that will not be explored here. Rather, we outline a survey of the types of data generated in whole organisms, putting particular emphasis on complex image capture, management and analysis, bio-systems modelling techniques at this higher scale, and approaches to integrating models across these physical scales. This change in biological focus raises certain challenges, one of which may be the need to retrain bioinformaticians in sciences pertaining to whole plants and animals