Abstract
In this paper, four methods were explored for improving the performance of jViz.RNA’s structure drawing algorithm when dealing with large sequences; First, the approximation based Barnes-Hut algorithm was explored. Second, the effects of using multithreading were measured. additionally, dynamic C libraries, which integrate C code into the JavaTM environment, were investigated. Finally, a technique termed structure recall was examined.
The results demonstrated that the use of the Barnes-Hut algorithm produced the most drastic improvements in run-time, but distorts the structure if too crude of an approximation is used. Multithreading and integration of C code proved to be favorable approaches since these improved the speed at which calculations are done, without distorting the structures.
jViz.RNA is available to download from http://jviz.cs.sfu.ca/ .
Keywords
- Repulsion Force
- Large Sequence
- Java Virtual Machine
- Virtual Body
- Brute Force Algorithm
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
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© 2012 Springer-Verlag Berlin Heidelberg
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Shabash, B., Wiese, K., Glen, E. (2012). Improving the Portability and Performance of jViz.RNA – A Dynamic RNA Visualization Software. In: Shibuya, T., Kashima, H., Sese, J., Ahmad, S. (eds) Pattern Recognition in Bioinformatics. PRIB 2012. Lecture Notes in Computer Science(), vol 7632. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34123-6_8
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DOI: https://doi.org/10.1007/978-3-642-34123-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34122-9
Online ISBN: 978-3-642-34123-6
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