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rMSA: A Sequence Search and Alignment Algorithm to Improve RNA Structure Modeling.
Zhang, Chengxin; Zhang, Yang; Pyle, Anna Marie.
Affiliation
  • Zhang C; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
  • Zhang Y; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA; Department of Biological Chemistry, University of Michigan, Ann Arbor, MI 48109, USA. Electronic address: zhang@zhanggroup.org.
  • Pyle AM; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Department of Chemistry, Yale University, New Haven, CT 06511, USA. Electronic address: anna.pyle@yale.edu.
J Mol Biol ; 435(14): 167904, 2023 07 15.
Article in En | MEDLINE | ID: mdl-37356900
The multiple sequence alignment (MSA) is the entry point of many RNA structure modeling tasks, such as prediction of RNA secondary structure (rSS) and contacts. However, there are few automated programs for generating high quality MSAs of target RNA molecules. We have developed rMSA, a hierarchical pipeline for sensitive search and accurate alignment of RNA homologs for a target RNA. On a diverse set of 365 non-redundant RNA structures, rMSA significantly outperforms an existing MSA generation method (RNAcmap) by approximately 20% and 5% higher F1-scores for rSS and long-range contact prediction, respectively. rMSA is available at https://zhanggroup.org/rMSA/ and https://github.com/pylelab/rMSA.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / RNA / Nucleic Acid Conformation Type of study: Prognostic_studies Language: En Journal: J Mol Biol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / RNA / Nucleic Acid Conformation Type of study: Prognostic_studies Language: En Journal: J Mol Biol Year: 2023 Document type: Article Affiliation country: United States Country of publication: Netherlands