A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2017
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| Online Access: | http://hdl.handle.net/1721.1/111712 |
| _version_ | 1826207107150512128 |
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| author | McBride, Cameron D |
| author2 | Domitilla Del Vecchio. |
| author_facet | Domitilla Del Vecchio. McBride, Cameron D |
| author_sort | McBride, Cameron D |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017. |
| first_indexed | 2024-09-23T13:44:13Z |
| format | Thesis |
| id | mit-1721.1/111712 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T13:44:13Z |
| publishDate | 2017 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1117122019-04-12T22:51:15Z A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks McBride, Cameron D Domitilla Del Vecchio. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 73-76). In this thesis, a framework is developed to investigate the effect of resource sharing on the performance of genetic networks. A model of a genetic system with shared resources for protein degradation is developed that captures resource sharing effects and is subsequently analyzed to discover ways in which this form of resource sharing effects genetic networks. It is shown that sharing of degradation resources may cancel undesirable effects due to resource sharing of protein production resources. Next, a theoretical framework is developed to find conditions in which a genetic network may exhibit a change in its number of equilibria due to resource sharing effects. Finally, metrics and an experimental method are proposed to estimate the quantity of resources a genetic network uses and the sensitivity of the network to disturbances in resource availability. These measures may be utilized to inform design choices in genetic networks in which resource sharing plays a significant role. These effects become increasingly important in more complex genetic networks. Quantification of such resource sharing effects are an important step in increasing the predictability of genetic networks. by Cameron D. McBride. S.M. 2017-10-04T15:05:01Z 2017-10-04T15:05:01Z 2017 2017 Thesis http://hdl.handle.net/1721.1/111712 1004225636 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 76 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. McBride, Cameron D A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title | A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title_full | A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title_fullStr | A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title_full_unstemmed | A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title_short | A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks |
| title_sort | mathematical and engineering framework to predict the effect of resource sharing on genetic networks |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/111712 |
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