Tools for simulating and analyzing RNA folding kinetics

Xinyu Tang, Shawna Thomas, Lydia Tapia, Nancy M. Amato

Research output: Chapter in Book/Report/Conference proceedingConference contribution


It has recently been found that some RNA functions are determined by the actual folding kinetics and not just the RNA's nucleotide sequence or its native structure. We present new computational tools for simulating and analyzing RNA folding kinetic metrics such as population kinetics, folding rates, and the folding of particular subsequences. Our method first builds an approximate representation (called a map) of the RNA's folding energy landscape, and then uses specialized analysis techniques to extract folding kinetics from the map. We provide a new sampling strategy called Probabilistic Boltzmann Sampling (PBS) that enables us to approximate the folding landscape with much smaller maps, typically by several orders of magnitude. We also describe a new analysis technique, Map-based Monte Carlo (MMC) simulation, to stochastically extract folding pathways from the map. We demonstrate that our technique can be applied to large RNA (e.g., 200+ nucleotides), where representing the full landscape is infeasible, and that our tools provide results comparable to other simulation methods that work on complete energy landscapes. We present results showing that our approach computes the same relative functional rates as seen in experiments for the relative plasmid replication rates of ColE1 RNAII and its mutants, and for the relative gene expression rates of MS2 phage RNA and its mutants.

Original languageEnglish (US)
Title of host publicationResearch in Computational Molecular Biology - 11th Annual International Conference, RECOMB 2007, Proceedings
Number of pages15
ISBN (Print)3540716807, 9783540716808
StatePublished - 2007
Externally publishedYes
Event11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007 - Oakland, CA, United States
Duration: Apr 21 2007Apr 25 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4453 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2007
Country/TerritoryUnited States
CityOakland, CA

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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