Synthetic biology: applications come of age

By Ahmad S. Khalil, James J. Collins. Nature reviews genetics, 2010

1,392 citations recorded by the source corpus.

Synthetic biology is bringing together engineers and biologists to design and build novel biomolecular components, networks and pathways, and to use these constructs to rewire and reprogram organisms. These re-engineered organisms will change our lives over the coming years, leading to cheaper drugs, 'green' means to fuel our cars and targeted therapies for attacking 'superbugs' and diseases, such as cancer. The de novo engineering of genetic circuits, biological modules and synthetic pathways is beginning to address these crucial problems and is being used in related practical applications.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/4f7e8f9a1fc3e9e66f78fc4248c2feab7eb60b6b

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Citations in the corpus

RNA-Guided Human Genome Engineering via Cas9 (2013, background): “We expect that RNA-guided genome targeting will have broad implications for synthetic biology (22, 23), the direct and multiplexed perturbation of gene networks (13, 24), and targeted ex vivo (25-27) and in vivo gene therapy (28).”
A Modular Cloning System for Standardized Assembly of Multigene Constructs (2011, background): “Applications include the microbial production of chemical precursors, novel antibiotics and biofuels [1], the creation of synthetic attenuated viruses for use as vaccines [2] and the engineering of a minimal free living cell [3].”
A Synthetic Biology Framework for Programming Eukaryotic Transcription Functions (2012, background): “A framework for eukaryotic transcription regulation would also be broadly valuable to synthetic biology efforts, which seek to uncover the design principles of gene regulatory networks and program novel biological functions for a range of biotechnological and industrial applications (Andrianantoandr”
The ribosome binding site calculator. (2011, background): “Genetic circuits have been engineered to exhibit bistability, oscillations, pattern formation, traveling waves, and Boolean logic (Danino et al., 2010; Ellis et al., 2009; Khalil and Collins, 2010; Lu et al., 2009; Purnick and Weiss, 2009; Stricker et al., 2008; Tabor et al., 2009).”
Next-Generation Machine Learning for Biological Networks. (2018, positive): “, health, agriculture, energy, environment) (Khalil and Collins, 2010), there is a growing need to take on these challenges so as to make biological design more predictable, straightforward, and time efficient; this creates marvelous opportunities for deep learning approaches, as we highlight below.”
Genetic programs constructed from layered logic gates in single cells (2012, methodology): “The three inducers used for the on (1) input are Ara (5mM), IPTG (0.”