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Improved Algorithms for Parsing ESLTAGs: A Grammatical Model Suitable for RNA Pseudoknots

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Bioinformatics Research and Applications (ISBRA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5542))

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Abstract

Formal grammars have been employed in biology to solve various important problems. In particular, grammars have been used to model and predict RNA structures. Two such grammars are Simple Linear Tree Adjoining Grammars (SLTAGs) and Extended SLTAGs (ESLTAGs). Performance of techniques that employ grammatical formalisms critically depend on the efficiency of the underlying parsing algorithms. In this paper we present efficient algorithms for parsing SLTAGs and ESLTAGs. Our algorithm for SLTAGs parsing takes O( min {m,n 4}) time and O( min {m,n 4}) space where m is the number of entries that will ever be made in the matrix M (that is normally used by TAG parsing algorithms). Our algorithm for ESLTAGs parsing takes O(n min {m,n 4}) time and O( min {m,n 4}) space. We show that these algorithms perform better in practice than the algorithms of Uemura, et al. [19].

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Authors and Affiliations

  1. Department of Computer Science, University of Connecticut, Storrs, CT 06269-2155, USA

    Sanguthevar Rajasekaran, Sahar Al Seesi & Reda Ammar

Authors
  1. Sanguthevar Rajasekaran
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  2. Sahar Al Seesi
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  3. Reda Ammar
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Editors and Affiliations

  1. Computer Science & Engineering Department, University of Connecticut, 371 Fairfield Way, Unit 2155, CT 06269, Storrs, USA

    Ion Măndoiu

  2. Bioinformatics Research Group (BioRG), School of Computing and Information Sciences, Florida International University, 11200 SW 8th Street, Room ECS254, University Park, FL 33199, Miami, USA

    Giri Narasimhan

  3. Department of Computer Science, Georgia State University, P.O. Box 3994, GA 30302-3994, Atlanta, USA

    Yanqing Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Rajasekaran, S., Al Seesi, S., Ammar, R. (2009). Improved Algorithms for Parsing ESLTAGs: A Grammatical Model Suitable for RNA Pseudoknots. In: Măndoiu, I., Narasimhan, G., Zhang, Y. (eds) Bioinformatics Research and Applications. ISBRA 2009. Lecture Notes in Computer Science(), vol 5542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01551-9_14

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  • DOI: https://doi.org/10.1007/978-3-642-01551-9_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01550-2

  • Online ISBN: 978-3-642-01551-9

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