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Design and assembly of DNA molecules using multi-objective optimization
Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524653/ https://www.ncbi.nlm.nih.gov/pubmed/34676304 http://dx.doi.org/10.1093/synbio/ysab026 |
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author | Gaeta, Angelo Zulkower, Valentin Stracquadanio, Giovanni |
author_facet | Gaeta, Angelo Zulkower, Valentin Stracquadanio, Giovanni |
author_sort | Gaeta, Angelo |
collection | PubMed |
description | Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the best tradeoff between design requirements and manufacturing constraints. We developed a new open-source algorithm for DNA engineering, called Multi-Objective Optimisation algorithm for DNA Design and Assembly, available as a Python and Anaconda package, as well as a Docker image. Experimental results show that our method provides near-optimal constructs and scales linearly with design complexity, effectively paving the way to rational engineering of DNA molecules from genes to genomes. |
format | Online Article Text |
id | pubmed-8524653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-85246532021-10-20 Design and assembly of DNA molecules using multi-objective optimization Gaeta, Angelo Zulkower, Valentin Stracquadanio, Giovanni Synth Biol (Oxf) Research Article Rapid engineering of biological systems is currently hindered by limited integration of manufacturing constraints into the design process, ultimately reducing the yield of many synthetic biology workflows. Here we tackle DNA engineering as a multi-objective optimization problem aiming at finding the best tradeoff between design requirements and manufacturing constraints. We developed a new open-source algorithm for DNA engineering, called Multi-Objective Optimisation algorithm for DNA Design and Assembly, available as a Python and Anaconda package, as well as a Docker image. Experimental results show that our method provides near-optimal constructs and scales linearly with design complexity, effectively paving the way to rational engineering of DNA molecules from genes to genomes. Oxford University Press 2021-10-11 /pmc/articles/PMC8524653/ /pubmed/34676304 http://dx.doi.org/10.1093/synbio/ysab026 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gaeta, Angelo Zulkower, Valentin Stracquadanio, Giovanni Design and assembly of DNA molecules using multi-objective optimization |
title | Design and assembly of DNA molecules using multi-objective optimization |
title_full | Design and assembly of DNA molecules using multi-objective optimization |
title_fullStr | Design and assembly of DNA molecules using multi-objective optimization |
title_full_unstemmed | Design and assembly of DNA molecules using multi-objective optimization |
title_short | Design and assembly of DNA molecules using multi-objective optimization |
title_sort | design and assembly of dna molecules using multi-objective optimization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524653/ https://www.ncbi.nlm.nih.gov/pubmed/34676304 http://dx.doi.org/10.1093/synbio/ysab026 |
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