AI Article Synopsis

  • Significant advancements in RNA 3D structure prediction methods have emerged from the RNA-Puzzles competition, which evaluates the blind prediction of RNA structures.
  • The competition highlights the importance of good benchmark datasets and structure comparison algorithms, as no systematic benchmarks or decoy structures currently exist for RNA modeling.
  • The RNA-Puzzles toolkit offers a comprehensive set of resources, including generated decoy sets, analysis tools, and standard assessment protocols to improve RNA structure prediction within the research community.

Article Abstract

Significant improvements have been made in the efficiency and accuracy of RNA 3D structure prediction methods during the succeeding challenges of RNA-Puzzles, a community-wide effort on the assessment of blind prediction of RNA tertiary structures. The RNA-Puzzles contest has shown, among others, that the development and validation of computational methods for RNA fold prediction strongly depend on the benchmark datasets and the structure comparison algorithms. Yet, there has been no systematic benchmark set or decoy structures available for the 3D structure prediction of RNA, hindering the standardization of comparative tests in the modeling of RNA structure. Furthermore, there has not been a unified set of tools that allows deep and complete RNA structure analysis, and at the same time, that is easy to use. Here, we present RNA-Puzzles toolkit, a computational resource including (i) decoy sets generated by different RNA 3D structure prediction methods (raw, for-evaluation and standardized datasets), (ii) 3D structure normalization, analysis, manipulation, visualization tools (RNA_format, RNA_normalizer, rna-tools) and (iii) 3D structure comparison metric tools (RNAQUA, MCQ4Structures). This resource provides a full list of computational tools as well as a standard RNA 3D structure prediction assessment protocol for the community.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7145511PMC
http://dx.doi.org/10.1093/nar/gkz1108DOI Listing

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