Honors College Thesis
 

Classification and Analysis of Nucleotide - Nucleotide Interactions in RNA

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https://ir.library.oregonstate.edu/concern/honors_college_theses/4m90f199d

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  • Base-pairing interaction are the fundamental blocks of an RNA structure. With increased ability to determine the structure of RNA molecules, an accurate and informative way of classifying these interactions would help to study RNA structure at many levels. Apart from the well-known complementary base pairs and wobble pairs, other interactions interface the Hoogsteen and Sugar edges. Here, we present a machine learning classifier that accurately identifies the interactions within an RNA molecule. Furthermore, the classifier presents probabilities associated with its predictions, informing potential flexibility or dynamics within a structure. Interactions not described by base-pair like interactions were clustered to reveal other sources of stabilization. Using K-means clustering on predicted unclassified interactions, we have identified potentially stable interactions that could represent new classes of dinucleotide interactions . Our analyses and classifier provide an enhanced view of RNA structure that can be used to further inform biological and structural significance Key Words: RNA Structure, Machine Learning
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