publication . Article . 2006

CONTRAfold: RNA secondary structure prediction without physics-based models

Daniel A. Woods; Chuong B. Do; Serafim Batzoglou;
Open Access
  • Published: 15 Jul 2006 Journal: Bioinformatics, volume 22, pages e90-e98 (issn: 1367-4803, eissn: 1460-2059, Copyright policy)
  • Publisher: Oxford University Press (OUP)
Abstract
Motivation: For several decades, free energy minimization methods have been the dominant strategy for single sequence RNA secondary structure prediction. More recently, stochastic context-free grammars (SCFGs)have emergedas an alternative probabilisticmethodology for modeling RNA structure. Unlike physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, SCFGs use fully-automated statistical learning algorithms to derive model parameters. Despite this advantage, however, probabilistic methods have not replaced free energy minimization methods as the toolofchoiceforsecondarystructureprediction,astheaccuraciesofthe best cu...
Subjects
free text keywords: Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications, Rna secondary structure prediction, Probabilistic method, Probabilistic logic, Rule-based machine translation, Energy minimization, Synchronous context-free grammar, Discriminative model, Machine learning, computer.software_genre, computer, Artificial intelligence, business.industry, business, Empirical measure, Computer science
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