Cited by 359RNA and protein synthesis mechanismsAlgorithms and Data CompressionDNA and Biological Computing

RNA Pseudoknot Prediction in Energy-Based Models

Lyngsø, Rune B., Pedersen, Christian N. S.·2000·Journal of Computational Biology

Abstract

RNA molecules are sequences of nucleotides that serve as more than mere intermediaries between DNA and proteins, e.g., as catalytic molecules. Computational prediction of RNA secondary structure is among the few structure prediction problems that can be solved satisfactorily in polynomial time. Most work has been done to predict structures that do not contain pseudoknots. Allowing pseudoknots introduces modeling and computational problems. In this paper we consider the problem of predicting RNA secondary structures with pseudoknots based on free energy minimization. We first give a brief comparison of energy-based methods for predicting RNA secondary structures with pseudoknots. We then prove that the general problem of predicting RNA secondary structures containing pseudoknots is NP complete for a large class of reasonable models of pseudoknots.

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Crossref · 10.1089/106652700750050862

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Authors
Lyngsø, R. B., & Pedersen, C. N. S.
Affiliations
  • University of California, Santa Cruz (US)
  • Aarhus University (DK)
Venue
Journal of Computational Biology
Published
2000-08
Volume
7
Issue
3-4
Pages
409-427
ISSN
  • 1066-5277 (ISSN-L)
  • 1557-8666
OpenAlex
W2076756368
Cited by
359
References
28
Citations by year
2026: 4 · 2025: 3 · 2024: 25 · 2023: 8 · 2022: 27 · 2021: 9 · 2020: 8 · 2019: 9 · 2018: 11 · 2017: 10 · 2016: 11 · 2015: 13 · 2014: 11 · 2013: 16 · 2012: 21
FWCI
1.33
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Computational Biology (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › DNA and Biological Computing
Keywords
RNA pseudoknots, RNA secondary structure prediction, energy-based models, free energy minimization, NP-completeness, computational complexity
MeSH terms
Algorithms, Models, Molecular, Nucleic Acid Conformation, RNA, Thermodynamics, Computational Biology

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