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Clustering Rfam 10.1: Clans, Families, and Classes

Department of Computer Science, Institute of Exact Sciences, University of Brasília, Brasília 70910-900, Brazil
Department of Cellular Biology, Institute of Biology, University of Brasília, Brasília 70910-900, Brazil
Department of Mathematics, University of Brasília, Brasília 70910-900, Brazil
Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstraße 16-18, D-04107 Leipzig, Germany
Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, Leipzig D-04103, Germany
Fraunhofer Institut für Zelltherapie und Immunologie–IZI Perlickstraße 1, D-04103 Leipzig, Germany
Institute for Theoretical Chemistry , University of Vienna, Währingerstraße 17, Wien A-1090, Austria
Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, DK-1870 Frederiksberg C, Denmark
Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA
Author to whom correspondence should be addressed.
Genes 2012, 3(3), 378-390;
Received: 5 May 2012 / Revised: 4 June 2012 / Accepted: 15 June 2012 / Published: 5 July 2012
(This article belongs to the Special Issue Feature Paper 2012)
The Rfam database contains information about non-coding RNAs emphasizing their secondary structures and organizing them into families of homologous RNA genes or functional RNA elements. Recently, a higher order organization of Rfam in terms of the so-called clans was proposed along with its “decimal release”. In this proposition, some of the families have been assigned to clans based on experimental and computational data in order to find related families. In the present work we investigate an alternative classification for the RNA families based on tree edit distance. The resulting clustering recovers some of the Rfam clans. The majority of clans, however, are not recovered by the structural clustering. Instead, they get dispersed into larger clusters, which correspond roughly to well-described RNA classes such as snoRNAs, miRNAs, and CRISPRs. In conclusion, a structure-based clustering can contribute to the elucidation of the relationships among the Rfam families beyond the realm of clans and classes. View Full-Text
Keywords: Rfam; non-coding RNA; secondary structure; clans; clusters Rfam; non-coding RNA; secondary structure; clans; clusters
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MDPI and ACS Style

Lessa, F.A.; Raiol, T.; Brigido, M.M.; Martins Neto, D.S.B.; Walter, M.E.M.T.; Stadler, P.F. Clustering Rfam 10.1: Clans, Families, and Classes. Genes 2012, 3, 378-390.

AMA Style

Lessa FA, Raiol T, Brigido MM, Martins Neto DSB, Walter MEMT, Stadler PF. Clustering Rfam 10.1: Clans, Families, and Classes. Genes. 2012; 3(3):378-390.

Chicago/Turabian Style

Lessa, Felipe A., Tainá Raiol, Marcelo M. Brigido, Daniele S. B. Martins Neto, Maria Emília M. T. Walter, and Peter F. Stadler. 2012. "Clustering Rfam 10.1: Clans, Families, and Classes" Genes 3, no. 3: 378-390.

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