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Prediction of RNA Secondary Structure Based on Optimization in the Space of Its Descriptors by the Simulated Annealing Algorithm

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Perspectives of System Informatics (PSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11964))

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Abstract

The proportion of genome coding proteins is only a small part of a whole genome (for example, about 5% in human’s genome). Among other things the remaining part contains regulatory RNAs whose function depends on their three-dimensional structure. Secondary structure is the first level of RNA structure description (three-dimensional structure is approximated by secondary structure).

Therefore the problem of determining the common secondary structure of isofunctional RNA sequences (i.e., a set having similar functionality) is an important and longstanding problem of bioinformatics. In this paper we present the program which builds the secondary structure model for a such set of non-homologous RNA sequences.

Secondary structure is described by directed acyclic graph i.e. multitree. The problem of determining the model of secondary structure is reduced to the discrete optimization task in the space of structure multitrees. The optimizable function depends on the energy of the referenced sequences being folded into this structure.

The optimization task is solved by simulated annealing algorithm. We developed the program for building a common secondary structure model of RNA and compared it with the existing solutions on the set of mobile group II introns.

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References

  1. Skiena, S.: The Algorithm Design Manual, 2nd edn. Springer, Heidelberg (2010). https://doi.org/10.1007/978-1-84800-070-4

    Book  MATH  Google Scholar 

  2. Reuter, J., Mathews, D.H.: RNAstructure: software for RNA secondary structure prediction and analysis. J. Biomol. Struct. Dyn. 26, 831–832 (2009)

    Google Scholar 

  3. Harmanci, A.O., Sharma, G., Mathews, D.H.: TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences. BMC Bioinform. 12, 108 (2011). https://doi.org/10.1186/1471-2105-12-108

    Article  Google Scholar 

  4. Sukosd, Z., Knudsen, B., Kjems, J., Pedersen, C.N.S.: PPfold 3.0: fast RNA secondary structure prediction using phylogeny and auxiliary data. Bioinformatics 28(16), 2012. https://doi.org/10.1093/bioinformatics/bts488

    Article  Google Scholar 

  5. http://www.softberry.com/freedownloadhelp/rna/rscan/rscan.all.html

  6. Rfam family of tRNA. http://rfam.xfam.org/family/RF00005

  7. Jaeger, J.A., Turner, D.H., Zuker, M.: Improved predictions of secondary structures for RNA. Proc. Natl. Acad. Sci. U.S.A. 86, 7706–7710 (1989)

    Article  Google Scholar 

  8. Candales, M.A., et al.: Database for bacterial group II introns. Nucleic Acids Res. 187–190 (2012). https://doi.org/10.1093/nar/gkr1043

    Article  Google Scholar 

  9. Fontaine, J.M., Goux, D., Kloareg, B., Loiseaux-de Goer, S.: The reverse-transcriptase-like proteins encoded by group II introns in the mitochondrial genome of the brown alga pylaiella littoralis belong to two different lineages which apparently coevolved with the group II ribosyme lineages. J. Mol. Evol. 44, 33–42 (1997). https://doi.org/10.1007/PL00006119

    Article  Google Scholar 

  10. Rfam family of selenocysteine transfer RNA http://rfam.xfam.org/family/RF01852

  11. https://github.com/rerf2010rerf/RNAStructBuilder

  12. Powers, D.M.W.: Evaluation: from precision, recall and F-Measure to ROC, informedness, markedness & correlation (PDF). J. Mach. Learn. Technol. 2(1), 37–63 (2011)

    MathSciNet  Google Scholar 

  13. Zimmerly, S., Semper, C.: Evolution of group II introns. Mob. DNA 6, 7 (2015). https://doi.org/10.1186/s13100-015-0037-5

    Article  Google Scholar 

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Acknowledgements

The work of I.T. was supported by the Federal Agency of Scientific Organizations (project #0324-2019-0040).

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Correspondence to Nikolay Kobalo .

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Kobalo, N., Kulikov, A., Titov, I. (2019). Prediction of RNA Secondary Structure Based on Optimization in the Space of Its Descriptors by the Simulated Annealing Algorithm. In: Bjørner, N., Virbitskaite, I., Voronkov, A. (eds) Perspectives of System Informatics. PSI 2019. Lecture Notes in Computer Science(), vol 11964. Springer, Cham. https://doi.org/10.1007/978-3-030-37487-7_10

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  • DOI: https://doi.org/10.1007/978-3-030-37487-7_10

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  • Online ISBN: 978-3-030-37487-7

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