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Computational analysis of ribonucleic acid basepairs in RNA structure and RNA-RNA interactions Lai, Daniel

Abstract

Ribonucleic acids (RNA), are an essential part of cellular function, transcribed from DNA and translated into protein. Rather than a passive informational medium, RNA can also be highly functional and regulatory. Certain RNAs fold into specific structures giving it enzymatic properties, while others bind to specific targets to guide regulatory processes. With the advent of next-generation sequencing, a large number of novel non-coding RNAs have been discovered through whole-transcriptome sequencing. Many efforts have been made to study the structure and binding partners of these novel RNAs, in order to determine their function and roles. This work begins with a description of my R package R4RNA for manipulating RNA basepair data, the building blocks of RNA structure and RNA binding. The package deals with the input/output and manipulation of RNA basepair and sequence data, along with statistical and visualization methods for evaluation, interpretation and presentation. We also describe R-chie, a visualization tool and web server built on R4RNA that visualizes complex RNA basepairs in conjunction with sequence alignments. We then conduct the largest known evaluation of RNA-RNA interaction methods to date, running state-of-the-art tools on curated experimentally validated datasets. We end with a review of cotranscriptional RNA basepair formation, summarizing biological, theoretical and computational methods for the process, and future directions for improving classical methods in RNA structure prediction. All content chapters of this thesis has been peer-reviewed and published. The work on R4RNA has led to two publications, with the package used to great visual effect by various publications and also adopted by the RNA structure database Rfam. My assessment of RNA-RNA interaction is at present the only published evaluation of its kind, and will hopefully become a benchmark for future tool development and a guide to selecting appropriate tools and algorithms. Our published review on RNA cotranscriptional folding is well-received, being the first review specifically on its topic.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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