Predicting RNA secondary structures with pseudoknots by MCMC sampling

DOI10.1007/s00285-007-0106-6zbMath1143.92011OpenAlexW2014031166WikidataQ51911866 ScholiaQ51911866MaRDI QIDQ938120

Dirk Metzler, Markus E. Nebel

Publication date: 18 August 2008

Published in: Journal of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00285-007-0106-6

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Bayesian inference (62F15) Applications of mathematical programming (90C90) Dynamic programming (90C39) Biochemistry, molecular biology (92C40) Grammars and rewriting systems (68Q42)

Related Items (7)

Topological Classification of RNA Structures via Intersection Graph ⋮ Predicting RNA secondary structures with pseudoknots by MCMC sampling ⋮ Fatgraph models of RNA structure ⋮ On the page number of RNA secondary structures with pseudoknots ⋮ Random k -noncrossing RNA structures ⋮ Gibbs/MCMC Sampling for Multiple RNA Interaction with Sub-optimal Solutions ⋮ Stacks in canonical RNA pseudoknot structures

Uses Software

• Rfam
• HotKnots
• Sfold

Cites Work

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• Optimization by Simulated Annealing
• Predicting RNA secondary structures with pseudoknots by MCMC sampling
• Tree adjoining grammars for RNA structure prediction
• Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots
• A Poisson model for gapped local alignments
• Thermodynamic Analysis of Interacting Nucleic Acid Strands
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Algorithms for Loop Matchings
• Biological Sequence Analysis
• Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations
• Monte Carlo sampling methods using Markov chains and their applications
• Monte Carlo strategies in scientific computing

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