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Comparative analysis of genome code complexity and manufacturability with engineering benchmarks
When knowledge has advanced to a state that includes a predictive understanding of the relationship between genome sequence and organism phenotype it will be possible for future engineers to design and produce synthetic organisms. However, the possibility of synthetic biology does not necessarily gu...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857313/ https://www.ncbi.nlm.nih.gov/pubmed/35181687 http://dx.doi.org/10.1038/s41598-022-06723-5 |
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author | Riolo, Joseph Steckl, Andrew J. |
author_facet | Riolo, Joseph Steckl, Andrew J. |
author_sort | Riolo, Joseph |
collection | PubMed |
description | When knowledge has advanced to a state that includes a predictive understanding of the relationship between genome sequence and organism phenotype it will be possible for future engineers to design and produce synthetic organisms. However, the possibility of synthetic biology does not necessarily guarantee its feasibility, in much the same way that the possibility of a brute force attack fails to ensure the timely breaking of robust encryption. The size and range of natural genomes, from a few million base pairs for bacteria to over 100 billion base pairs for some plants, suggests it is necessary to evaluate the practical limits of designing genomes of similar complexity. This analysis characterizes the complexity of natural genomes, compares them to existing engineering benchmarks, and shows that existing large software programs are on similar scale with the genome of complex natural organisms. |
format | Online Article Text |
id | pubmed-8857313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88573132022-02-22 Comparative analysis of genome code complexity and manufacturability with engineering benchmarks Riolo, Joseph Steckl, Andrew J. Sci Rep Article When knowledge has advanced to a state that includes a predictive understanding of the relationship between genome sequence and organism phenotype it will be possible for future engineers to design and produce synthetic organisms. However, the possibility of synthetic biology does not necessarily guarantee its feasibility, in much the same way that the possibility of a brute force attack fails to ensure the timely breaking of robust encryption. The size and range of natural genomes, from a few million base pairs for bacteria to over 100 billion base pairs for some plants, suggests it is necessary to evaluate the practical limits of designing genomes of similar complexity. This analysis characterizes the complexity of natural genomes, compares them to existing engineering benchmarks, and shows that existing large software programs are on similar scale with the genome of complex natural organisms. Nature Publishing Group UK 2022-02-18 /pmc/articles/PMC8857313/ /pubmed/35181687 http://dx.doi.org/10.1038/s41598-022-06723-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Riolo, Joseph Steckl, Andrew J. Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title | Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title_full | Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title_fullStr | Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title_full_unstemmed | Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title_short | Comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
title_sort | comparative analysis of genome code complexity and manufacturability with engineering benchmarks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8857313/ https://www.ncbi.nlm.nih.gov/pubmed/35181687 http://dx.doi.org/10.1038/s41598-022-06723-5 |
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