Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA

  • Weijia Xu
  • Stuart Ozer
  • Robin R. Gutell
Conference paper

DOI: 10.1007/978-3-642-02279-1_15

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5566)
Cite this paper as:
Xu W., Ozer S., Gutell R.R. (2009) Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA. In: Winslett M. (eds) Scientific and Statistical Database Management. SSDBM 2009. Lecture Notes in Computer Science, vol 5566. Springer, Berlin, Heidelberg

Abstract

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

Keywords

Biological database Bioinformatics Sequence Analysis RNA 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Weijia Xu
    • 1
  • Stuart Ozer
    • 2
  • Robin R. Gutell
    • 3
  1. 1.Texas Advanced Computing CenterThe University of Texas at AustinAustinUSA
  2. 2.One Microsoft Way RedmondWashingtonUSA
  3. 3.Center of Computational Biology and BioinformaticsThe University of Texas at AustinAustinUSA

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