Adventures with RNA Graphs

Abstract

RNA's modular, hierarchical and versatile structure makes possible diverse, essential regulatory and catalytic roles in the cell. It also invites systematic modeling and simulation approaches. Among the diverse computational and theoretical approaches to model RNA structures, graph theory has been applied in various contexts to study RNA structure and function. I will present an overview of recent graph theoretical approaches for predicting and designing RNA topologies using graphical representations of RNA secondary structure, data-mining tools for junction topology prediction, and hierarchical sampling of graphs based on statistical potentials. As evident from the work of many groups in the mathematical and biological sciences, graph theoretical approaches offer a fruitful avenue for designing novel RNA topologies and predicting tertiary structures from given secondary structures.Of possible interest- H.H. Gan, S. Pasquali and T. Schlick, Nucl. Acids Res. 31:2926 (2003)- N. Kim et al., J. Mol. Biol. 341:1129 (2004)- G. Quarta and K. Sin and T. Schlick, PLoS Comput. Biol. 8: e1002368 (2012).- C. Laing, S. Jung, N. Kim, S. Elmetwaly, M. Zharan, and T. Schlick, PLOS One 8(8): e71947 (2013).- N. Kim, C. Laing, S. Elmetwaly, S. Jung, J. Curuksu, and T. Schlick, Proc. Natl. Acad. Sci. USA 111: 4079 (2014).- M. Zharan, C. S. Bayrak, S. Elmetwaly, and T. Schlick, Nuc. Acids Res. 43: 9474 (2015).- N. Baba, S. Elmetwaly, N. Kim, and T. Schlick, J. Mol. Biol. 428: 811 (2016).- L. Hua, Y. Song, N. Kim, C. Laing, J. T. L. Wang, and T. Schlick, PlOS One 11: e0147097 (2016).