Dataset Information

Nonparametric clustering for studying RNA conformations.

ABSTRACT: The local conformation of RNA molecules is an important factor in determining their catalytic and binding properties. The analysis of such conformations is particularly difficult due to the large number of degrees of freedom, such as the measured torsion angles per residue and the interatomic distances among interacting residues. In this work, we use a nearest-neighbor search method based on the statistical mechanical Potts model to find clusters in the RNA conformational space. The proposed technique is mostly automatic and may be applied to problems, where there is no prior knowledge on the structure of the data space in contrast to many other clustering techniques. Results are reported for both single residue conformations, where the parameter set of the data space includes four to seven torsional angles, and base pair geometries, where the data space is reduced to two dimensions. Moreover, new results are reported for base stacking geometries. For the first two cases, i.e., single residue conformations and base pair geometries, we get a very good match between the results of the proposed clustering method and the known classifications with only few exceptions. For the case of base stacking geometries, we validate our classification with respect to geometrical constraints and describe the content, and the geometry of the new clusters.

SUBMITTER: Le Faucheur X

PROVIDER: S-EPMC3679554 | biostudies-literature | 2011 Nov-Dec

REPOSITORIES: biostudies-literature

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Nonparametric clustering for studying RNA conformations.

Le Faucheur Xavier X Hershkovits Eli E Tannenbaum Rina R Tannenbaum Allen A

IEEE/ACM transactions on computational biology and bioinformatics 20111101 6

The local conformation of RNA molecules is an important factor in determining their catalytic and binding properties. The analysis of such conformations is particularly difficult due to the large number of degrees of freedom, such as the measured torsion angles per residue and the interatomic distances among interacting residues. In this work, we use a nearest-neighbor search method based on the statistical mechanical Potts model to find clusters in the RNA conformational space. The proposed tec ...[more]

PMID: 21173460

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Dataset Information

Nonparametric clustering for studying RNA conformations.

Publications

Nonparametric clustering for studying RNA conformations.

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