Thesis (Ph. D.)--University of Chicago, Department of Chemistry, 2001. / Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 138-149). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.) in Biochemistry and Molecular Biology--University of Maine, 2001. / Includes vita. Includes bibliographical references (leaves 71-83).

Not available / text

No description available.

RNA molecules play important roles, including catalysis of chemical reactions and control of gene expression, and their functions largely depend on their folded structures. Since determining these structures by biochemical means is expensive, there is increased demand for computational predictions of RNA structures. One computational approach is to find the secondary structure (a set of base pairs) that minimizes a free energy function for a given RNA conformation. The forces driving RNA folding can be approximated by means of a free energy model, which associates a free energy parameter to a distinct considered feature. The main goal of this thesis is to develop state-of-the-art computational approaches that can significantly increase the accuracy (i.e., maximize the number of correctly predicted base pairs) of RNA secondary structure prediction methods, by improving and refining the parameters of the underlying RNA free energy model. We propose two general approaches to estimate RNA free energy parameters. The Constraint Generation (CG) approach is based on iteratively generating constraints that enforce known structures to have energies lower than other structures for the same molecule. The Boltzmann Likelihood (BL) approach infers a set of RNA free energy parameters which maximize the conditional likelihood of a set of known RNA structures. We discuss several variants and extensions of these two approaches, including a linear Gaussian Bayesian network that defines relationships between features. Overall, BL gives slightly better results than CG, but it is over ten times more expensive to run. In addition, CG requires software that is much simpler to implement. We obtain significant improvements in the accuracy of RNA minimum free energy secondary structure prediction with and without pseudoknots (regions of non-nested base pairs), when measured on large sets of RNA molecules with known structures. For the Turner model, which has been the gold-standard model without pseudoknots for more than a decade, the average prediction accuracy of our new parameters increases from 60% to 71%. For two models with pseudoknots, we obtain an increase of 9% and 6%, respectively. To the best of our knowledge, our parameters are currently state-of-the-art for the three considered models.

The localization, trafficking and regulation of messenger ribonucleic acids (RNA) and viral RNA play crucial roles in cellular homeostasis and disease pathogenesis. In recent years biochemical and molecular biology methods used to study RNA function have made several important advances in the areas of RNA interference, expression of transgenes, and the sequencing of transcriptomes. In contrast, current technologies for imaging RNA in live cells remain in limited use. Previous studies of RNA localization and dynamics have relied primarily on the expression of a reporter RNA and a fluorescent protein fusion that binds to aptamer sequences in the expressed RNA. While these plasmid based systems offer methodological flexibility, there remains a need to develop methods to image native, non-engineered RNA as plasmid derived RNAs may not have the same regulatory elements (3'UTR and introns) or copy number as the native RNA. Additionally, viral pathogenesis is often sensitive to the size and sequence of their genomic RNA and may not be suitable for study using engineered systems. We sought to develop and validate a new method for imaging native, non-engineered RNA with single molecule-sensitivity. These probes have four important properties. They are modular, compatible with fixation and immunostaining, bind quickly and specifically to targets, and do not interfere with RNA function. We built upon the technique of delivering exogenous, linear probes that bind to their target by Watson-Crick base pairing. The probes are multiply labeled and tetramerized to increase their brightness. To validate the probes, targeting and utility was demonstrated in two model systems: beta-actin mRNA to show targeting of an endogenous target and the genomic RNA of human respiratory syncytial virus to show targeting of a viral RNA target. All video files are in QuickTime format.

Thesis (Ph. D.)--University of Oregon, 2007. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 67-80). Also available for download via the World Wide Web; free to University of Oregon users.

Thesis (Ph. D.)--Michigan State University. Dept. of Microbiology and Molecular Genetics, 2006. / Title from PDF t.p. (viewed on Nov. 20, 2008) Includes bibliographical references. Also issued in print.

Thesis (Ph. D.)--University of Oregon, 2007. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 76-84). Also available online in ProQuest, free to University of Oregon users.