A heuristic approach for detecting RNA H-type pseudoknots

Chun Hsiang Huang, Chin Lung Lu, Hsien Tai Chiu

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)

Abstract

Motivation: RNA H-type pseudoknots are ubiquitous pseudoknots that are found in almost all classes of RNA and thought to play very important roles in a variety of biological processes. Detection of these RNA H-type pseudoknots can improve our understanding of RNA structures and their associated functions. However, the currently existing programs for detecting such RNA H-type pseudoknots are still time consuming and sometimes even ineffective. Therefore, efficient and effective tools for detecting the RNA H-type pseudoknots are needed. Results: In this paper, we have adopted a heuristic approach to develop a novel tool, called HPknotter, for efficiently and accurately detecting H-type pseudoknots in an RNA sequence. In addition, we have demonstrated the applicability and effectiveness of HPknotter by testing on some sequences with known H-type pseudoknots. Our approach can be easily extended and applied to other classes of more general pseudoknots.

Original languageEnglish
Pages (from-to)3501-3508
Number of pages8
JournalBioinformatics
Volume21
Issue number17
DOIs
Publication statusPublished - 2005 Sep 1

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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