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RNA Pseudoknot Folding through Inference and Identification Using TAGRNA

  • Sahar Al Seesi
  • Sanguthevar Rajasekaran
  • Reda Ammar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5462)

Abstract

Studying the structure of RNA sequences is an important problem that helps in understanding the functional properties of RNA. After being ignored for a long time due to the high computational complexity it requires, pseudoknot is one type of RNA structures that has been given a lot of attention lately. Pseudoknot structures have functional importance since they appear, for example, in viral genome RNAs and ribozyme active sites. In this paper, we present a folding framework, TAGRNAInf, for RNA structures that support pseudoknots. Our approach is based on learning TAGRNA grammars from training data with structural information. The inferred grammars are used to indentify sequences with structures analogous to those in the training set and generate a folding for these sequences. We present experimental results and comparisons with other known pseudoknot folding approaches.

Keywords

Structure Prediction Threshold Function Tobacco Rattle Virus Viral Genome RNAs Pseudoknot Structure 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Sahar Al Seesi
    • 1
  • Sanguthevar Rajasekaran
    • 1
  • Reda Ammar
    • 1
  1. 1.Computer Science and Engineering DepartmentUniversity of ConnecticutUSA

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