Computers are aiding biotechnology researchers to rapidly develop new engineered strains of organisms with favorable product accumulation. The organisms being engineered can be represented as constraint based metabolic models. These models are analyzed using computational methods to find optimal genetic manipulation strategies such as gene knockouts. Due to growing biological knowledge, there has been a corresponding increase in the size and complexity of the $in>silico$ metabolic models. Therefore the biotechnology research community needs access to an effective computational method and an efficient implementation of the method that reasonably quickly solves the problem of searching for genetic manipulations. Furthermore, the biotechnology researchers are of diverse backgrounds and their computer skills are different. This should not hinder the community from using these computational techniques. In order to address the above requirements, an efficient and user-friendly software solution has been proposed and developed for discovering strategies that may enhance the yield of chemical compounds of interest.
Subject (authority = RUETD)
Topic
Computer Science
Subject (authority = ETD-LCSH)
Topic
Biotechnology--Research
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_5003
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
ix, 74 p. : ill.
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Brahmaji Mutthoju
Subject (authority = ETD-LCSH)
Topic
Biotechnology--Computer simulation
Subject (authority = ETD-LCSH)
Topic
Genetic engineering--Computer simulation
RelatedItem (type = host)
TitleInfo
Title
Camden Graduate School Electronic Theses and Dissertations
Identifier (type = local)
rucore10005600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.