Predicting RNA secondary structures from sequence and probing data
نویسندگان
چکیده
منابع مشابه
Predicting RNA secondary structures from sequence and probing data.
RNA secondary structures have proven essential for understanding the regulatory functions performed by RNA such as microRNAs, bacterial small RNAs, or riboswitches. This success is in part due to the availability of efficient computational methods for predicting RNA secondary structures. Recent advances focus on dealing with the inherent uncertainty of prediction by considering the ensemble of ...
متن کاملGrammatically Modeling and Predicting RNA Secondary Structures
Tree Adjunct Grammar for RNA (TAG 2 RNA ) is a new grammatical device to model RNA secondary structures including pseudoknots. An e cient parsing algorithm for this grammar is developed, and applied to some computational problems concerning RNA secondary structures. With this parser, we rst try to predict secondary structures of RNA sequences which are known to form pseudoknots structures, and ...
متن کاملPredicting RNA Secondary Structures Including Pseudoknots
RNA secondary structures play a vital role in modern genetics and a lot of time and e ort has been put into their study. It is important to be able to predict them with high accuracy, since methods involving manual analysis are expensive, time-consuming and error-prone. Predictions can also be used to guide experiments to reduce time and money requirements. Several algorithms have been develope...
متن کاملPredicting RNA secondary structures with pseudoknots by MCMC sampling.
The most probable secondary structure of an RNA molecule, given the nucleotide sequence, can be computed efficiently if a stochastic context-free grammar (SCFG) is used as the prior distribution of the secondary structure. The structures of some RNA molecules contain so-called pseudoknots. Allowing all possible configurations of pseudoknots is not compatible with context-free grammar models and...
متن کاملPredicting RNA Secondary Structures with Pseudoknots by MCMC Sampling . — preprint —
The most probable secondary structure of an RNA molecule, given the nucleotide sequence, can be computed efficiently if a stochastic context-free grammar (SCFG) is used as the prior distribution of the secondary structure. The structures of some RNA molecules contain so-called pseudoknots. Allowing all possible configurations of pseudoknots is not compatible with context-free grammar models and...
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ژورنال
عنوان ژورنال: Methods
سال: 2016
ISSN: 1046-2023
DOI: 10.1016/j.ymeth.2016.04.004