• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    A novel method for cluster analysis of RNA structural data

    Thumbnail
    View/Open
    ROGERS-DISSERTATION-2018.pdf (9.121Mb)
    Date
    2018-05-21
    Author
    Rogers, Emily
    Metadata
    Show full item record
    Abstract
    Functional RNA is known to contribute to a host of important biological pathways, with new discoveries being made daily. Because function is dependent on structure, computational tools that predict secondary structure of RNA are crucial to researchers. By far the most popular method is to predict the minimum free energy structure as the native. However, well-known limitations of this method have led the computational RNA community to move on to Boltzmann sampling. This method predicts an ensemble of structures sampled from the Boltzmann distribution under the Nearest Neighbor Thermodynamic Model (NNTM). Although providing a more thorough view of the folding landscape of a sequence, the Boltzmann sampling method also has the drawback of needing post-processing (i.e. data mining) in order to be meaningful. This dissertation presents a novel method of representing and clustering secondary structures of a Boltzmann sample. In addition, it demonstrates its ability to extract the meaningful structural signal of a Boltzmann sample by identifying significant commonalities and differences. Applications include two outstanding problems in the computational RNA community: investigating the ill-conditioning of thermodynamic optimization under the NNTM, and predicting a consensus structure for a set of sequences. Finally, this dissertation concludes with research performed as an intern for the Department of Defense's Defense Forensic Science Center. This work concerns analyzing the results of a DNA mixture interpretation study, highlighting the current state of forensic interpretation today.
    URI
    http://hdl.handle.net/1853/60232
    Collections
    • College of Computing Theses and Dissertations [1191]
    • Georgia Tech Theses and Dissertations [23877]
    • School of Computational Science and Engineering Theses and Dissertations [100]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology