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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Categorization of RNA Molecules Using Graph Methods
verfasst von : Richard C. Wilson, Enes Algul
Erschienen in: Structural, Syntactic, and Statistical Pattern Recognition
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Abstract
RNA molecules are a group of biologically active molecules which have a similar structure to DNA. Graph-based methods for classification have shown promise on other biological compounds such as protein. In this paper, we investigate the use of graph representations of RNA, graph-feature based methods and their role in classifying RNA into particular categories. We describe a number of possible graph representations of RNA structure and how useful information can be encoded in the graph. We show how graph-kernel and graph-feature methods can be used to provide descriptors for the molecules. Finally, on a moderately-sized database of 419 RNA structures, we explore how these methods can be used to classify RNA into high-level categories provided by the biological context or function of the molecules. We find that graph descriptors give state-of-the-art performance on sequence classification, but that the graph elements of the description do not add useful information above the base-sequence.