2012
DOI: 10.1038/nrmicro2717
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Computational tools for the synthetic design of biochemical pathways

Abstract: As the field of synthetic biology is developing, the prospects for de novo design of biosynthetic pathways are becoming more and more realistic. Hence, there is an increasing need for computational tools that can support these efforts. A range of algorithms has been developed that can be used to identify all possible metabolic pathways and their corresponding enzymatic parts. These can then be ranked according to various properties and modelled in an organism-specific context. Finally, design software can aid … Show more

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Cited by 207 publications
(125 citation statements)
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“…Some computational prediction tools are involved in changing the metabolic pathway by using knockouts or by adding new catalytic enzymes, and this may help in increasing biofuel production. One important tool for the prediction of metabolic pathway is From Metabolite to Metabolite (FMM)-freely available software (Medema et al, 2012). It compiles the KEGG map and KEGG ligand data to obtain a combined pathway.…”
Section: Optimization Of Production Pathways and Hostmentioning
confidence: 99%
“…Some computational prediction tools are involved in changing the metabolic pathway by using knockouts or by adding new catalytic enzymes, and this may help in increasing biofuel production. One important tool for the prediction of metabolic pathway is From Metabolite to Metabolite (FMM)-freely available software (Medema et al, 2012). It compiles the KEGG map and KEGG ligand data to obtain a combined pathway.…”
Section: Optimization Of Production Pathways and Hostmentioning
confidence: 99%
“…By way of comparison, TeseleGen estimates that direct DNA synthesis of the same 240 constructs would cost $540,000 at current prices. Although peer-reviewed data are not yet available to evaluate the TeseleGen claims, it is clear that these kinds of improvements in model-driven synthetic biology [other recent advances are reviewed in (Koeppl 2011) (Blount et al 2012), (Medema et al 2012) and (Shiue and Prather 2012)] will reduce the number of cycles of design, construction and analysis needed to engineer systems that meet performance goals.…”
Section: Progress Toward Design-driven Synthetic Biologymentioning
confidence: 99%
“…Several recent reviews describe and compare the different drag and drop tools developed for the synthetic biology community in the last few years [Alterovitz et al 2009;Marchisio et al 2009;Clancy et al 2010;MacDonald et al 2011;Medema et al 2012]. All of these tools have the same goal, i.e.…”
Section: Drag and Drop Toolsmentioning
confidence: 99%