RNA Pseudoknot Prediction in Energy-Based Models

By Rune B. Lyngsø, Christian N. S. Pedersen. J. Comput. Biol., 2000

360 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/dd7f40ee815c01811749c88a6c9ad1cdb7e24157

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Erik Winfree
2. D. Mathews
3. Justin S. Bois
4. Christopher W. Leonard
5. Joseph M. Schaeffer
6. Niles A. Pierce
7. Robert M. Dirks
8. Stanislav Bellaousov

Citations in the corpus

• Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots (2013, background): “The prediction of lowest free energy structures with pseudoknots is NP-complete (9), which means that lowest free energy structure cannot be solved as a function of sequence length in polynomial time.”
• IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming (2011, background): “This is a drawback of our method.”
• Thermodynamic Analysis of Interacting Nucleic Acid Strands (2007, background): “Furthermore, if the ensemble is augmented to include all possible pseudoknots, MFE determination can be NP -hard [20, 1].”