Evidence map›Paper›PMID 28558664›Full record

ArticleBMC bioinformatics2017

Numerical integration methods and layout improvements in the context of dynamic RNA visualization.

Boris Shabash, Kay C Wiese

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Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

2 authors.

Boris ShabashSchool of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada.
Kay C WieseSchool of Computing Science, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada. wiese@sfu.ca.ORCID http://orcid.org/0000-0003-4507-1892

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRNA visualization software tools have traditionally presented a static visualization of RNA molecules with limited ability for users to interact with the resulting image once it is complete. Only a few tools allowed for dynamic structures. One such tool is jViz.RNA. Currently, jViz.RNA employs a unique method for the creation of the RNA molecule layout by mapping the RNA nucleotides into vertexes in a graph, which we call the detailed graph, and then utilizes a Newtonian mechanics inspired system of forces to calculate a layout for the RNA molecule. The work presented here focuses on improvements to jViz.RNA that allow the drawing of RNA secondary structures according to common drawing conventions, as well as dramatic run-time performance improvements. This is done first by presenting an alternative method for mapping the RNA molecule into a graph, which we call the compressed graph, and then employing advanced numerical integration methods for the compressed graph representation.

resultsComparing the compressed graph and detailed graph implementations, we find that the compressed graph produces results more consistent with RNA drawing conventions. However, we also find that employing the compressed graph method requires a more sophisticated initial layout to produce visualizations that would require minimal user interference. Comparing the two numerical integration methods demonstrates the higher stability of the Backward Euler method, and its resulting ability to handle much larger time steps, a high priority feature for any software which entails user interaction.

conclusionThe work in this manuscript presents the preferred use of compressed graphs to detailed ones, as well as the advantages of employing the Backward Euler method over the Forward Euler method. These improvements produce more stable as well as visually aesthetic representations of the RNA secondary structures. The results presented demonstrate that both the compressed graph representation, as well as the Backward Euler integrator, greatly enhance the run-time performance and usability. The newest iteration of jViz.RNA is available at https://jviz.cs.sfu.ca/download/download.html .

Indexed as

AlgorithmsBase SequenceNucleic Acid ConformationRNASoftwareRNAGraph layoutNumerical integrationRNAVisualization

Identifiers

PMID28558664
PMCPMC5450055

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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.