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Massachusetts Institute of Technology

A biological simulator using a stochastic approach for synthetic biology

Abstract

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.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2005

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kim, Daniel D., 1982-
Advisor dc:contributor.advisor
  • Thomas F. Knight, Jr.

Subjects

dc:subject × 1

Rights

dc:rights
Statement 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/33307
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/33307

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kim, Daniel D., 1982-. A biological simulator using a stochastic approach for synthetic biology. Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33307