Persistent Homology Analysis of RNA

• Autorzy: Adane L. Mamuye , Matteo Rucco , Luca Tesei , Emanuela Merelli
• Języki publikacji: EN

Abstrakty

EN

Topological data analysis has been recently used to extract meaningful information frombiomolecules. Here we introduce the application of persistent homology, a topological data analysis tool, for computing persistent features (loops) of the RNA folding space. The scaffold of the RNA folding space is a complex graph from which the global features are extracted by completing the graph to a simplicial complex via the notion of clique and Vietoris-Rips complexes. The resulting simplicial complexes are characterised in terms of topological invariants, such as the number of holes in any dimension, i.e. Betti numbers. Our approach discovers persistent structural features, which are the set of smallest components to which the RNA folding space can be reduced. Thanks to this discovery, which in terms of data mining can be considered as a space dimension reduction, it is possible to extract a new insight that is crucial for understanding the mechanism of the RNA folding towards the optimal secondary structure. This structure is composed by the components discovered during the reduction step of the RNA folding space and is characterized by minimum free energy.

Słowa kluczowe

EN

RNA folding space; persistent homology; persistent structural features

• Wydawca: De Gruyter Open
• Czasopismo: Molecular Based Mathematical Biology
• Rocznik: 2016
• Tom: 4
• Numer: 1

Daty

otrzymano

2016-09-14

zaakceptowano

2016-11-20

online

2016-12-05

Twórcy

autor

Adane L. Mamuye

• School of Science and Technology, Computer Science Division, University of Camerino, 62032, Camerino (MC), Italy

autor

Matteo Rucco

• School of Science and Technology, Computer Science Division, University of Camerino, 62032, Camerino (MC), Italy
• Italian National Council of Research, Institute of Applied Mathematics and Information Technologies, 16149, Genova (Ge), Italy,

autor

Luca Tesei

• School of Science and Technology, Computer Science Division, University of Camerino, 62032, Camerino (MC), Italy

autor

Emanuela Merelli

• School of Science and Technology, Computer Science Division, University of Camerino, 62032, Camerino (MC), Italy

Identyfikatory

DOI

10.1515/mlbmb-2016-0002