Literature DB >> 22710180

Perspectives on the automatic design of regulatory systems for synthetic biology.

Guillermo Rodrigo1, Javier Carrera, Thomas E Landrain, Alfonso Jaramillo.   

Abstract

Automatic design is based on computational modeling and optimization methods to provide prototype designs to targeted problems in an unsupervised manner. For biological circuits, we need to produce quantitative predictions of cell behavior for a given genotype as consequence of the different molecular interactions. Automatic design techniques aim at solving the inverse problem of finding the sequences of nucleotides that better fit a targeted behavior. In the post-genomic era, our molecular knowledge and modeling capabilities have allowed to start using such methodologies with success. Herein, we describe how the emergence of this new type of tools could enable novel synthetic biology applications. We highlight the essential elements to develop automatic design procedures for synthetic biology pointing out their advantages and bottlenecks. We discuss in detail the experimental difficulties to overcome in the in vivo implementation of designed networks. The use of automatic design to engineer biological networks is starting to emerge as a new technique to perform synthetic biology, which should not be neglected in the future.
Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22710180     DOI: 10.1016/j.febslet.2012.02.031

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  4 in total

1.  Towards a behavioral-matching based compilation of synthetic biology functions.

Authors:  Adrien Basso-Blandin; Franck Delaplace
Journal:  Acta Biotheor       Date:  2015-07-05       Impact factor: 1.774

2.  Multi-objective optimization framework to obtain model-based guidelines for tuning biological synthetic devices: an adaptive network case.

Authors:  Yadira Boada; Gilberto Reynoso-Meza; Jesús Picó; Alejandro Vignoni
Journal:  BMC Syst Biol       Date:  2016-03-11

3.  Computational design of host transcription-factors sets whose misregulation mimics the transcriptomic effect of viral infections.

Authors:  Javier Carrera; Santiago F Elena
Journal:  Sci Rep       Date:  2012-12-19       Impact factor: 4.379

4.  Full design automation of multi-state RNA devices to program gene expression using energy-based optimization.

Authors:  Guillermo Rodrigo; Thomas E Landrain; Eszter Majer; José-Antonio Daròs; Alfonso Jaramillo
Journal:  PLoS Comput Biol       Date:  2013-08-01       Impact factor: 4.475

  4 in total

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