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dc.contributor.advisorThomas F. Knight, Jr.en_US
dc.contributor.authorKim, Daniel D., 1982-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2006-07-13T15:14:07Z
dc.date.available2006-07-13T15:14:07Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/33307
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.en_US
dc.descriptionIncludes bibliographical references (leaves 58-59).en_US
dc.description.abstractSynthetic 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.statementofresponsibilityby Daniel D. Kim.en_US
dc.format.extent59 leavesen_US
dc.format.extent2523967 bytes
dc.format.extent2525434 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleA biological simulator using a stochastic approach for synthetic biologyen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc62296074en_US


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