Thesis advisor: Peter Clote / RNA molecules play important roles in living organisms, such as protein translation, gene regulation, and RNA processing. It is known that RNA secondary structure is a scaffold for tertiary structure leading to extensive amount of interest in RNA secondary structure. This thesis is primarily focused on the development of novel algorithms for the analysis of RNA secondary structure evolution and folding kinetics. We describe a software RNAsampleCDS to generate mRNA sequences coding user-specified peptides overlapping in up to six open reading frames. Sampled mRNAs are then analyzed with other tools to provide an estimate of their secondary structure properties. We investigate homology of RNAs with respect to both sequence and secondary structure information as well. RNAmountAlign an efficient software package for multiple global, local, and semiglobal alignment of RNAs using a weighted combination of sequence and structural similarity with statistical support is presented. Furthermore, we approach RNA folding kinetics from a novel network perspective, presenting algorithms for the shortest path and expected degree of nodes in the network of all secondary structures of an RNA. In these algorithms we consider move set MS2 , allowing addition, removal and shift of base pairs used by several widely-used RNA secondary structure folding kinetics software that implement Gillespie’s algorithm. We describe MS2distance software to compute the shortest MS2 folding trajectory between any two given RNA secondary structures. Moreover, RNAdegree software implements the first algorithm to efficiently compute the expected degree of an RNA MS2 network of secondary structures. The source code for all the software and webservers for RNAmountAlign, MS2distance, and RNAdegree are publicly available at http://bioinformatics.bc.edu/clotelab/. / Thesis (PhD) — Boston College, 2018. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.
| Identifer | oai:union.ndltd.org:BOSTON/oai:dlib.bc.edu:bc-ir_108256 |
| Date | January 2018 |
| Creators | Bayegan, Amir Hossein |
| Publisher | Boston College |
| Source Sets | Boston College |
| Language | English |
| Detected Language | English |
| Type | Text, thesis |
| Format | electronic, application/pdf |
| Rights | Copyright is held by the author, with all rights reserved, unless otherwise noted. |
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