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A biological simulator using a stochastic approach for synthetic biology

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dc.contributor.advisor Thomas F. Knight, Jr. en_US
dc.contributor.author Kim, Daniel D., 1982- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.date.accessioned 2006-07-13T15:14:07Z
dc.date.available 2006-07-13T15:14:07Z
dc.date.copyright 2005 en_US
dc.date.issued 2005 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/33307
dc.description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005. en_US
dc.description Includes bibliographical references (leaves 58-59). en_US
dc.description.abstract Synthetic Biology is a new engineering discipline created by the development of genetic engineering technology. Part of a new engineering discipline is to create new tools to build an integrated engineering environment. In this thesis, I designed and implemented a biological system simulator that will enable synthetic biologists to simulate their systems before they put time into building actual physical cells. Improvements to the current simulators in use include a design that enables extensions in functionality, external input signals, and a GUI that allows user interaction. The significance of the simulation results was tested by comparing them to actual live cellular experiments. The results showed that the new simulator can successfully simulate the trends of a simple synthetic cell. en_US
dc.description.statementofresponsibility by Daniel D. Kim. en_US
dc.format.extent 59 leaves en_US
dc.format.extent 2523967 bytes
dc.format.extent 2525434 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582
dc.subject Electrical Engineering and Computer Science. en_US
dc.title A biological simulator using a stochastic approach for synthetic biology en_US
dc.type Thesis en_US
dc.description.degree M.Eng. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.identifier.oclc 62296074 en_US


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