Bioinformatics for the synthetic biology of natural products: integrating across the Design–Build–Test cycle

@article{Carbonell2016BioinformaticsFT,
  title={Bioinformatics for the synthetic biology of natural products: integrating across the Design–Build–Test cycle},
  author={Pablo Carbonell and Andrew Currin and Adrian J. Jervis and Nicholas J. W. Rattray and Neil Swainston and Cunyu Yan and Eriko Takano and Rainer Breitling},
  journal={Natural Product Reports},
  year={2016},
  volume={33},
  pages={925 - 932}
}
Bioinformatics tools facilitate and accelerate all steps along the Design–Build–Test cycle of synthetic biology, for the enhanced production of natural products in engineered microbes. 

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References

SHOWING 1-10 OF 166 REFERENCES
Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently
Improving enzymes by directed evolution requires the navigation of very large search spaces; we survey how to do this intelligently.
Computational tools for the synthetic design of biochemical pathways
TLDR
Key existing tools for de novo design of biosynthetic pathways and suggestions for how informatics can help to shape the future of synthetic microbiology are offered.
Building biological foundries for next-generation synthetic biology
TLDR
This review summarizes the state-of-the-art technologies for synthetic biology and discusses the challenges to establish such biological foundries.
XTMS: pathway design in an eXTended metabolic space
TLDR
XTMS, a web-based pathway analysis platform available at http://xtms.genopole.fr, provides full access to the set of pathways that can be imported into a chassis organism such as Escherichia coli through the application of an Extended Metabolic Space modeling framework.
Metabolic tinker: an online tool for guiding the design of synthetic metabolic pathways
TLDR
An online tool called Metabolic Tinker, which aims to guide the design of synthetic metabolic pathways between any two desired compounds using a tailored heuristic search strategy, and provides for the first time thermodynamic feasibility information for the discovered paths.
Construction and optimization of synthetic pathways in metabolic engineering.
FindPath: a Matlab solution for in silico design of synthetic metabolic pathways
TLDR
FindPath is a unified system to predict and rank possible pathways according to their metabolic efficiency in the cellular system, which uses a chemical reaction database to generate possible metabolic pathways and exploits constraint-based models (CBMs) to identify the most efficient synthetic pathway.
RobOKoD: microbial strain design for (over)production of target compounds
TLDR
RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets, provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design.
...
...