Abstract

Metabolic networks have been studied for several decades, and sophisticated computational frameworks are needed to augment experimental approaches to harness these complex networks. BNICE (Biochemical Network Integrated Computational Explorer), a computational approach for the discovery of novel biochemical pathways that is based on biochemical transformations, overcomes many of the current limitations. BNICE and similar frameworks can be used in several different areas: (i) 'Design' of novel pathways for metabolic engineering; (ii) 'Retrosynthesis' of metabolic compounds; (iii) 'Evolution' analysis between metabolic pathways of different organisms; (iv) 'Analysis' of metabolic pathways; (v) 'Mining' of omics data; and (vi) 'Selection' of targets for enzyme engineering. Here, we discuss the issues and challenges in building such frameworks as well as the gamut of applications in biotechnology, metabolic engineering and synthetic biology.

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