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Genetic Algorithm-Based Approach for RNA Secondary Structure Prediction

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 563))

Abstract

In recent years, bioinformatics has become an essential subject for molecular biological study. The various available algorithms are used for analyzing and integrating biological data. Among many biological statistics RNA (ribonucleic acid) is one of the most important as it is used in protein synthesis. In computational molecular biology, the optimal secondary structure prediction of large RNA is a problem being faced today. RNA sequences of some virus are very large in number which requires a large amount of time for secondary structure prediction. Consequently, parallelization of algorithm is one of the solutions to diminish time consumption. This paper proposes the algorithm GAfold for predicting secondary structure of RNA on shared memory multicore architecture. The various RNA sequences as an input have been taken from Gutell database. For calculating minimum free energy, thermodynamic model is used and the outcomes are compared with existing algorithms.

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Authors and Affiliations

  1. Computer Science and Engineering Department, Priyadarshini J.L. College of Engineering, Nagpur, Maharashtra, India

    Pradnya S. Borkar

  2. Information Technology Department, Government Polytechnic, Nagpur, Maharashtra, India

    A. R. Mahajan

Authors
  1. Pradnya S. Borkar
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  2. A. R. Mahajan
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Corresponding author

Correspondence to Pradnya S. Borkar .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Białystok University of Technology, Białystok, Poland

    Khalid Saeed

  2. Department of Computer Science and Engineering, University of Calcutta, Kolkata, India

    Nabendu Chaki

  3. C.V. Raman College of Engineering, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  4. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Sambit Bakshi

  5. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Borkar, P.S., Mahajan, A.R. (2018). Genetic Algorithm-Based Approach for RNA Secondary Structure Prediction. In: Saeed, K., Chaki, N., Pati, B., Bakshi, S., Mohapatra, D. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 563. Springer, Singapore. https://doi.org/10.1007/978-981-10-6872-0_37

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  • DOI: https://doi.org/10.1007/978-981-10-6872-0_37

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6871-3

  • Online ISBN: 978-981-10-6872-0

  • eBook Packages: EngineeringEngineering (R0)

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