Synthetic approaches to understanding biological constraints
Microbes can be readily cultured and their genomes can be easily manipulated. For these reasons, laboratory systems of unicellular organisms are increasingly used to develop and test theories about biological constraints, which manifest themselves at different levels of biological organization, from...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Elsevier B.V.
2014
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| Online Access: | http://hdl.handle.net/1721.1/88494 https://orcid.org/0000-0003-4583-8555 |
| _version_ | 1826197982233493504 |
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| author | Velenich, Andrea Gore, Jeff |
| author2 | Massachusetts Institute of Technology. Department of Physics |
| author_facet | Massachusetts Institute of Technology. Department of Physics Velenich, Andrea Gore, Jeff |
| author_sort | Velenich, Andrea |
| collection | MIT |
| description | Microbes can be readily cultured and their genomes can be easily manipulated. For these reasons, laboratory systems of unicellular organisms are increasingly used to develop and test theories about biological constraints, which manifest themselves at different levels of biological organization, from optimal gene-expression levels to complex individual and social behaviors. The quantitative description of biological constraints has recently advanced in several areas, such as the formulation of global laws governing the entire economy of a cell, the direct experimental measurement of the trade-offs leading to optimal gene expression, the description of naturally occurring fitness landscapes, and the appreciation of the requirements for a stable bacterial ecosystem. |
| first_indexed | 2024-09-23T10:56:48Z |
| format | Article |
| id | mit-1721.1/88494 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:56:48Z |
| publishDate | 2014 |
| publisher | Elsevier B.V. |
| record_format | dspace |
| spelling | mit-1721.1/884942022-10-01T00:06:00Z Synthetic approaches to understanding biological constraints Velenich, Andrea Gore, Jeff Massachusetts Institute of Technology. Department of Physics Gore, Jeff Velenich, Andrea Microbes can be readily cultured and their genomes can be easily manipulated. For these reasons, laboratory systems of unicellular organisms are increasingly used to develop and test theories about biological constraints, which manifest themselves at different levels of biological organization, from optimal gene-expression levels to complex individual and social behaviors. The quantitative description of biological constraints has recently advanced in several areas, such as the formulation of global laws governing the entire economy of a cell, the direct experimental measurement of the trade-offs leading to optimal gene expression, the description of naturally occurring fitness landscapes, and the appreciation of the requirements for a stable bacterial ecosystem. Alfred P. Sloan Foundation (Fellowship) Pew Charitable Trusts (Pew Scholars Program) National Science Foundation (U.S.) (NSF CAREER Award) National Institutes of Health (U.S.) (NIH R00 Pathway to Independence Award) 2014-07-24T19:35:58Z 2014-07-24T19:35:58Z 2012-08 Article http://purl.org/eprint/type/JournalArticle 13675931 http://hdl.handle.net/1721.1/88494 Velenich, Andrea, and Jeff Gore. “Synthetic Approaches to Understanding Biological Constraints.” Current Opinion in Chemical Biology 16, no. 3–4 (August 2012): 323–328. https://orcid.org/0000-0003-4583-8555 en_US http://dx.doi.org/10.1016/j.cbpa.2012.05.199 Current Opinion in Chemical Biology Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Elsevier B.V. PMC |
| spellingShingle | Velenich, Andrea Gore, Jeff Synthetic approaches to understanding biological constraints |
| title | Synthetic approaches to understanding biological constraints |
| title_full | Synthetic approaches to understanding biological constraints |
| title_fullStr | Synthetic approaches to understanding biological constraints |
| title_full_unstemmed | Synthetic approaches to understanding biological constraints |
| title_short | Synthetic approaches to understanding biological constraints |
| title_sort | synthetic approaches to understanding biological constraints |
| url | http://hdl.handle.net/1721.1/88494 https://orcid.org/0000-0003-4583-8555 |
| work_keys_str_mv | AT velenichandrea syntheticapproachestounderstandingbiologicalconstraints AT gorejeff syntheticapproachestounderstandingbiologicalconstraints |