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New algorithms to predict secondary structures of RNA macromolecules

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Methodology and Tools in Knowledge-Based Systems (IEA/AIE 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1415))

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Abstract

In this paper, we present, under the Hypothesis of Linearity of Energy (HLE), new algorithms to solve the problem of the prediction by energy computation of RNA stable secondary structures. We present our dynamic programming algorithm to compute the free energies of the stable secondary structures, and our traceback algorithm to predict these structures. Our algorithm for computing the free energies is of complexities O(n 3) in computing time and O(n 2) in memory space, where n is the length of the string. Our prediction algorithm is of complexity O(n*log2(n)) in computing time. Compared to other algorithms, under the HLE, our algorithms present the advantage of taking into account the energetic contribution of all the unpaired bases, in addition to the energetic contribution of the paired ones.

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Authors and Affiliations

  1. Computer Science Department, Faculty of Sciences of Tunis, and Faculty of Economic Sciences and Management of Tunis, El Manar, 2092, Tunis, Tunisia

    Mourad Ellourni

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  1. Mourad Ellourni
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José Mira Angel Pasqual del Pobil Moonis Ali

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© 1998 Springer-Verlag

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Ellourni, M. (1998). New algorithms to predict secondary structures of RNA macromolecules. In: Mira, J., del Pobil, A.P., Ali, M. (eds) Methodology and Tools in Knowledge-Based Systems. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64582-9_820

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  • DOI: https://doi.org/10.1007/3-540-64582-9_820

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64582-5

  • Online ISBN: 978-3-540-69348-2

  • eBook Packages: Springer Book Archive

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