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A Method for RNA Structure Prediction Shows Evidence for Structure in lncRNAs.
Delli Ponti, Riccardo; Armaos, Alexandros; Marti, Stefanie; Tartaglia, Gian Gaetano.
Afiliación
  • Delli Ponti R; Centre for Genomic Regulation, Bioinformatics and Genomics Programme, The Barcelona Institute for Science and Technology, Barcelona, Spain.
  • Armaos A; Universitat Pompeu Fabra, Barcelona, Spain.
  • Marti S; Centre for Genomic Regulation, Bioinformatics and Genomics Programme, The Barcelona Institute for Science and Technology, Barcelona, Spain.
  • Tartaglia GG; Universitat Pompeu Fabra, Barcelona, Spain.
Front Mol Biosci ; 5: 111, 2018.
Article en En | MEDLINE | ID: mdl-30560136
ABSTRACT
To compare the secondary structure profiles of RNA molecules we developed the CROSSalign method. CROSSalign is based on the combination of the Computational Recognition Of Secondary Structure (CROSS) algorithm to predict the RNA secondary structure profile at single-nucleotide resolution and the Dynamic Time Warping (DTW) method to align profiles of different lengths. We applied CROSSalign to investigate the structural conservation of long non-coding RNAs such as XIST and HOTAIR as well as ssRNA viruses including HIV. CROSSalign performs pair-wise comparisons and is able to find homologs between thousands of matches identifying the exact regions of similarity between profiles of different lengths. In a pool of sequences with the same secondary structure CROSSalign accurately recognizes repeat A of XIST and domain D2 of HOTAIR and outperforms other methods based on covariance modeling. The algorithm is freely available at the webpage http//service.tartaglialab.com//new_submission/crossalign.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Mol Biosci Año: 2018 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Mol Biosci Año: 2018 Tipo del documento: Article País de afiliación: España