Manual alignment of IVS sequences and its implication in multiple sequence alignment



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It is recognized that an iterative comparative analysis of large-scale homologous RNAs significantly promote the understanding of an RNA family. The Gutell lab is renowned for maintaining high quality RNA sequence alignments and accurately predicted RNA secondary structures using this approach. While the current available alignment and structure data are mainly obtained by trained domain experts with extensive manual effort, it is highly desired that this process is automated and replicable given the exponentially growing number of RNA sequence data and the amount of time required for expert training. In this thesis, we learn the processes involved in comparative analysis by manually aligning a non-coding RNA family, IVS sequences, with the supervision of Dr. Gutell. Each process is then simulated by mathematical objective functions and algorithms. We also evaluate the current available RNA analysis packages that aim each of the processes. Finally, a new RNA sequence alignment algorithm incorporating structure information that can be extended for different alignment tasks is proposed.