Date of Award
Doctor of Philosophy (PhD)
Molecular Biophysics and Biochemistry
This dissertation describes a range of computational efforts to discover novel structured non-coding RNA (ncRNA) motifs in bacteria and generate hypotheses regarding their potential functions. This includes an introductory description of key advances in comparative genomics and RNA structure prediction as well as some of the most commonly found ncRNA candidates. Beyond that, I describe efforts for the comprehensive discovery of ncRNA candidates in 25 bacterial genomes and a catalog of the various functions hypothesized for these new motifs. Finally, I describe the Discovery of Intergenic Motifs PipeLine (DIMPL) which is a new computational toolset that harnesses the power of support vector machine (SVM) classifiers to identify bacterial intergenic regions most likely to contain novel structured ncRNA and automates the bulk of the subsequent analysis steps required to predict function. In totality, the body of work will enable the large scale discovery of novel structured ncRNA motifs at a far greater pace than possible before.
Brewer, Kenneth Ivan, "Computational Discovery of Structured Non-coding RNA Motifs in Bacteria" (2021). Yale Graduate School of Arts and Sciences Dissertations. 21.