CONTRAfold: RNA secondary structure prediction without physics-based models

CONTRAfold: RNA secondary structure prediction without physics-based models

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 emerged as an alternative probabilistic methodology for modeling RNA structure. Unlike physics-based methods, which rely on thousands of experimentally-measured thermodynamic paramete...

Physics-based RNA structure prediction

Despite the success of RNA secondary structure prediction for simple, short RNAs, the problem of predicting RNAs with long-range tertiary folds remains. Furthermore, RNA 3D structure prediction is hampered by the lack of the knowledge about the tertiary contacts and their thermodynamic parameters. Low-resolution structural modeling enables us to estimate the conformational entropies for a numbe...

Semi-Supervised CONTRAfold for RNA Secondary Structure Prediction: A Maximum Entropy Approach

CCG-Based RNA Secondary Structure Prediction

Various systems have been proposed to predict secondary structures of RNAs using their sequence information. Among them, Uemura et al. [2] described a system that recognizes some typical RNA secondary structures such as hairpin loops and pseudoknots with Tree Adjoining Grammar. However, their work captures only known sub-structures, and not those unknown sub-structures that might also exist. Te...

RNA Secondary Structure Prediction.

In this unit, protocols are provided for predicting RNA secondary structure with the user-friendly RNAstructure desktop computer program and the RNAstructure Web server. The minimum free energy structure and a set of suboptimal structures with similar free energies are predicted. Prediction of high-affinity oligonucleotide binding sites to a structured RNA target is also presented. © 2016 by Jo...