Engineering Models to Scale
Main Text The physicist Richard Feynman famously wrote, “What I cannot create, I do not understand,” at the top of his final blackboard. This philosophy has inspired many in the emerging field of synthetic biology, which harnesses the power of biology to rationally engineer biomolecular systems for...
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| Format: | Article |
| Language: | en_US |
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Elsevier B.V.
2017
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| Online Access: | http://hdl.handle.net/1721.1/108578 https://orcid.org/0000-0003-0319-5416 https://orcid.org/0000-0002-5560-8246 |
| _version_ | 1826207045685084160 |
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| author | Dy, Aaron James Collins, James J. |
| author2 | Massachusetts Institute of Technology. Institute for Medical Engineering & Science |
| author_facet | Massachusetts Institute of Technology. Institute for Medical Engineering & Science Dy, Aaron James Collins, James J. |
| author_sort | Dy, Aaron James |
| collection | MIT |
| description | Main Text
The physicist Richard Feynman famously wrote, “What I cannot create, I do not understand,” at the top of his final blackboard. This philosophy has inspired many in the emerging field of synthetic biology, which harnesses the power of biology to rationally engineer biomolecular systems for a variety of purposes, such as whole-cell biosensing and in vivo diagnostics (Slomovic et al., 2015). The “build-to-understand” approach (Elowitz and Lim, 2010) is complementary to top-down systems biology approaches and borrows concepts and techniques from engineering and computer science. By creating biological systems with desired architectures and functions, it aims to test design principles in relative isolation by exploring how biology’s building blocks, such as DNA-encoded genes, can be rearranged and altered to produce different phenotypes. In this issue, Cao et al. use this approach to tackle the question of how self-organizing systems maintain a constant ratio of physical pattern features with changing size, a property known as scale invariance (Cao et al., 2016). |
| first_indexed | 2024-09-23T13:42:38Z |
| format | Article |
| id | mit-1721.1/108578 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:42:38Z |
| publishDate | 2017 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | mit-1721.1/1085782024-03-20T20:27:09Z Engineering Models to Scale Dy, Aaron James Collins, James J. Massachusetts Institute of Technology. Institute for Medical Engineering & Science Massachusetts Institute of Technology. Synthetic Biology Center Massachusetts Institute of Technology. Department of Biological Engineering Collins, James J. Dy, Aaron James Collins, James J. Main Text The physicist Richard Feynman famously wrote, “What I cannot create, I do not understand,” at the top of his final blackboard. This philosophy has inspired many in the emerging field of synthetic biology, which harnesses the power of biology to rationally engineer biomolecular systems for a variety of purposes, such as whole-cell biosensing and in vivo diagnostics (Slomovic et al., 2015). The “build-to-understand” approach (Elowitz and Lim, 2010) is complementary to top-down systems biology approaches and borrows concepts and techniques from engineering and computer science. By creating biological systems with desired architectures and functions, it aims to test design principles in relative isolation by exploring how biology’s building blocks, such as DNA-encoded genes, can be rearranged and altered to produce different phenotypes. In this issue, Cao et al. use this approach to tackle the question of how self-organizing systems maintain a constant ratio of physical pattern features with changing size, a property known as scale invariance (Cao et al., 2016). 2017-05-02T15:21:34Z 2017-05-02T15:21:34Z 2016-04 Article http://purl.org/eprint/type/JournalArticle 00928674 http://hdl.handle.net/1721.1/108578 Dy, Aaron J., and James J. Collins. “Engineering Models to Scale.” Cell 165, no. 3 (April 2016): 516–517. https://orcid.org/0000-0003-0319-5416 https://orcid.org/0000-0002-5560-8246 en_US http://dx.doi.org/10.1016/j.cell.2016.04.017 Cell Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier B.V. Prof. Collins via Howard Silver |
| spellingShingle | Dy, Aaron James Collins, James J. Engineering Models to Scale |
| title | Engineering Models to Scale |
| title_full | Engineering Models to Scale |
| title_fullStr | Engineering Models to Scale |
| title_full_unstemmed | Engineering Models to Scale |
| title_short | Engineering Models to Scale |
| title_sort | engineering models to scale |
| url | http://hdl.handle.net/1721.1/108578 https://orcid.org/0000-0003-0319-5416 https://orcid.org/0000-0002-5560-8246 |
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