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

Overview of attention for article published in BMC Bioinformatics, May 2017
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Title
Numerical integration methods and layout improvements in the context of dynamic RNA visualization
Published in
BMC Bioinformatics, May 2017
DOI 10.1186/s12859-017-1682-0
Pubmed ID
Authors

Boris Shabash, Kay C. Wiese

Abstract

RNA 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. Comparing 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. The 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 .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 18%
Student > Master 2 18%
Professor 1 9%
Lecturer 1 9%
Student > Bachelor 1 9%
Other 1 9%
Unknown 3 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 27%
Environmental Science 1 9%
Mathematics 1 9%
Biochemistry, Genetics and Molecular Biology 1 9%
Computer Science 1 9%
Other 1 9%
Unknown 3 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 May 2017.
All research outputs
#20,425,762
of 22,977,819 outputs
Outputs from BMC Bioinformatics
#6,883
of 7,308 outputs
Outputs of similar age
#275,210
of 316,100 outputs
Outputs of similar age from BMC Bioinformatics
#99
of 108 outputs
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