RAG-Web: RNA structure prediction/design using RNA-As-Graphs

Grace Meng, Marva Tariq, Swati Jain, Shereef Elmetwaly, Tamar Schlick, Yann Ponty

Research output: Contribution to journalArticle

Abstract

Summary: We launch a webserver for RNA structure prediction and design corresponding to tools developed using our RNA-As-Graphs (RAG) approach. RAG uses coarse-grained tree graphs to represent RNA secondary structure, allowing the application of graph theory to analyze and advance RNA structure discovery. Our webserver consists of three modules: (a) RAG Sampler: samples tree graph topologies from an RNA secondary structure to predict corresponding tertiary topologies, (b) RAG Builder: builds three-dimensional atomic models from candidate graphs generated by RAG Sampler, and (c) RAG Designer: designs sequences that fold onto novel RNA motifs (described by tree graph topologies). Results analyses are performed for further assessment/selection. The Results page provides links to download results and indicates possible errors encountered. RAG-Web offers a user-friendly interface to utilize our RAG software suite to predict and design RNA structures and sequences.

Original languageEnglish (US)
Pages (from-to)647-648
Number of pages2
JournalBioinformatics
Volume36
Issue number2
DOIs
StatePublished - Jan 15 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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