Genus Comparisons in the Topological Analysis of RNA Structures

Abstract

RNA folding prediction remains challenging, but can be also studied using a topological mathematical approach. In the present paper, the mathematical method to compute the topological classification of RNA structures and based on matrix field theory is shortly reviewed, as well as a computational software, McGenus, used for topological and folding predictions. Additionally, two types of analysis are performed: the prediction results from McGenus are compared with topological information extracted from experimentally-determined RNA structures, and the topology of RNA structures is investigated for biological significance, in both evolutionary and functional terms. Lastly, we advocate for more research efforts to be performed at intersection of physics-mathematics and biology, and in particular about the possible contributions that topology can provide to the study of RNA folding and structure.

arXiv comment11 pages, 9 figures

References in corpus (10)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• RNA Folding and Large N Matrix Theory
• Enumeration of RNA structures by Matrix Models
• McGenus: A Monte Carlo algorithm to predict RNA secondary structures with pseudoknots
• Topological recursion for chord diagrams, RNA complexes, and cells in moduli spaces
• A steepest descent calculation of RNA pseudoknots
• The Topology of Pseudoknotted Homopolymers
• Improved RNA pseudoknots prediction and classification using a new topological invariant
• Thermodynamics of a model for RNA folding
• Genus Ranges of Chord Diagrams