Evidence map›Paper›PMID 30928508›Full record

ArticleMethods (San Diego, Calif.)2019

An extended dual graph library and partitioning algorithm applicable to pseudoknotted RNA structures.

Swati Jain, Sera Saju, Louis Petingi, Tamar Schlick

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
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  4. Evolution of coronavirus frameshifting elements: Competing stem networks explain conservation and variability.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
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  8. Article
  9. Article
  10. A Fiedler Vector Scoring Approach for Novel RNA Motif Selection.The journal of physical chemistry. B · 2021
    Article
  11. The Multiscale Future of RNA Modeling.Biophysical journal · 2020
    Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Swati JainDepartment of Chemistry, New York University, 1021 Silver, 100 Washington Square East, New York, NY 10003, USA.
Sera SajuDepartment of Chemistry, New York University, 1021 Silver, 100 Washington Square East, New York, NY 10003, USA.
Louis PetingiComputer Science Department, College of Staten Island, City University of New York, Staten Island, New York, NY 10314, USA.
Tamar SchlickDepartment of Chemistry, New York University, 1021 Silver, 100 Washington Square East, New York, NY 10003, USA; Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012, USA; NYU-East China Normal University Center for Computational Chemistry at New York University Shanghai, Room 340, Geography Building, North Zhongshan Road, 3663 Shanghai, China. Electronic address: schlick@nyu.edu.

Funding

Bridging Disparate Structural/Functional Scales: Multiscale Modeling of the Chromatin Fiber and RNA Tertiary StructuresR35GM122562 · NIGMS · NEW YORK UNIVERSITY · PI Tamar Schlick · 2017 to 2026
$4.6M
Modeling RNA Tertiary Structure Folding by a Hierarchical FrameworkR01GM100469 · NIGMS · NEW YORK UNIVERSITY · PI SCHLICK, TAMAR · 2011 to 2014
$1.5M
NIGMS NIH HHS R01 GM100469NIGMS NIH HHS R35 GM122562
6 · The paper itself

Abstract

Exploring novel RNA topologies is imperative for understanding RNA structure and pursuing its design. Our RNA-As-Graphs (RAG) approach exploits graph theory tools and uses coarse-grained tree and dual graphs to represent RNA helices and loops by vertices and edges. Only dual graphs represent pseudoknotted RNAs fully. Here we develop a dual graph enumeration algorithm to generate an expanded library of dual graph topologies for 2-9 vertices, and extend our dual graph partitioning algorithm to identify all possible RNA subgraphs. Our enumeration algorithm connects smaller-vertex graphs, using all possible edge combinations, to build larger-vertex graphs and retain all non-isomorphic graph topologies, thereby more than doubling the size of our prior library to a total of 110,667 dual graph topologies. We apply our dual graph partitioning algorithm, which keeps pseudoknots and junctions intact, to all existing RNA structures to identify all possible substructures up to 9 vertices. In addition, our expanded dual graph library assigns graph topologies to all RNA graphs and subgraphs, rectifying prior inconsistencies. We update our RAG-3Dual database of RNA atomic fragments with all newly identified substructures and their graph IDs, increasing its size by more than 50 times. The enlarged dual graph library and RAG-3Dual database provide a comprehensive repertoire of graph topologies and atomic fragments to study yet undiscovered RNA molecules and design RNA sequences with novel topologies, including a variety of pseudoknotted RNAs.

Indexed as

Gene LibraryNucleic Acid ConformationAlgorithmsComputational BiologyDatabases, Nucleic AcidModels, MolecularRNARNADual graph libraryGraph enumerationGraph partitioningRAG-3Dual databaseRNA As GraphsRNA subgraphs

Identifiers

PMID30928508
PMCPMC6612455

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.