Paper Info
Title
Building the Library of Rna 3D Nucleotide Conformations Using the Clustering Approach
Abstract
AbstractAbstract An increasing number of known RNA 3D structures contributes to the recognition of various RNA families and identification of their features. These tasks are based on an analysis of RNA conformations conducted at different levels of detail. On the other hand, the knowledge of native nucleotide conformations is crucial for structure prediction and understanding of RNA folding. However, this knowledge is stored in structural databases in a rather distributed form. Therefore, only automated methods for sampling the space of RNA structures can reveal plausible conformational representatives useful for further analysis. Here, we present a machine learning-based approach to inspect the dataset of RNA three-dimensional structures and to create a library of nucleotide conformers. A median neural gas algorithm is applied to cluster nucleotide structures upon their trigonometric description. The clustering procedure is two-stage: i backbone- and ii ribose-driven. We show the resulting library that contains RNA nucleotide representatives over the entire data, and we evaluate its quality by computing normal distribution measures and average RMSD between data points as well as the prototype within each cluster.
Year
DOI
Venue
2015
10.1515/amcs-2015-0050
Periodicals
Keywords
Field
DocType
RNA nucleotides, conformer library, torsion angles, clustering, neural gas
Data point,RNA,Mathematical optimization,RNA Conformation,Rna folding,Computational biology,Nucleotide,Cluster analysis,Neural gas,Mathematics,Structural engineering
Journal
Volume
Issue
ISSN
25
3
1641-876X
Citations 
PageRank 
References 
3
0.43
15
Authors
8
Name
Order
Citations
PageRank
Tomasz Zok1262.89
Maciej Antczak2306.41
M. Riedel3122.28
David Nebel4416.52
Thomas Villmann51279118.19
Piotr Lukasiak6132.13
Jacek Blazewicz71064154.23
Marta Szachniuk89712.33