Journal article Open Access

Furthering genome design using models and algorithms

Rees-Garbutt, Joshua; Rightmyer, Jake; Karr, Jonathan R.; Grierson, Claire; Marucci, Lucia

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Rees-Garbutt, Joshua</dc:creator>
  <dc:creator>Rightmyer, Jake</dc:creator>
  <dc:creator>Karr, Jonathan R.</dc:creator>
  <dc:creator>Grierson, Claire</dc:creator>
  <dc:creator>Marucci, Lucia</dc:creator>

	Models can investigate many more genome designs than laboratory research.
	Algorithms can search for genomes that optimise specific criteria.
	Together, models and algorithms can help engineers to design genomes.
	Algorithm-driven whole-cell model in silico designs could be viable in vivo.
	The genome design ecosystem needs improved modelling and design tools.


Large-scale in silico genome designs are on the brink of being engineered in vivo, offering a potential paradigm shift for cellular research (previous designs relied on fractured available knowledge and in vivo engineering iteration) by integrating computational design, in silico models and algorithms, with laboratory construction. However, several challenges remain. If in vivo engineering is successful, designing genomes can be used to gain new understanding of cellular life, improve the metabolite production process and reduce the risk of unintended genetic modification and release. Here, we review the progress so far. We suggest improvements on recent models and algorithms, illustrate the next steps for integrating computational and laboratory engineering and offer our opinions on the future of the field.</dc:description>
  <dc:source>Current Opinion in Systems Biology 24 120-126</dc:source>
  <dc:title>Furthering genome design using models and algorithms</dc:title>
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