ArticleRNA biology2012
A domain-based model for predicting large and complex pseudoknotted structures.
Article in RNA biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 7 citations in OpenAlex.
- Predicting RNA Structure with Vfold.Methods in molecular biology (Clifton, N.J.) · 2017Article
- Structural computational modeling of RNA aptamers.Methods (San Diego, Calif.) · 2016Article
- A Method to Predict the Structure and Stability of RNA/RNA Complexes.Methods in molecular biology (Clifton, N.J.) · 2016Article
- Predicting kissing interactions in microRNA-target complex and assessment of microRNA activity.Nucleic acids research · 2012Article
- Physics-based RNA structure prediction.Biophysics reportsArticle
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Authors and funding
2 authors at 1 institution in 1 country.
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Abstract
Pseudoknotted structures play important structural and functional roles in RNA cellular functions at the level of transcription, splicing and translation. However, the problem of computational prediction for large pseudoknotted folds remains. Here we develop a domain-based method for predicting complex and large pseudoknotted structures from RNA sequences. The model is based on the observation that large RNAs can be separated into different structural domains. The basic idea is to first identify the domains and then predict the structures for each domain. Assembly of the domain structures gives the full structure. The use of the domain-based approach leads to a reduction of computational time by a factor of about ~N ( 2) for an N-nt sequence. As applications of the model, we predict structures for a variety of RNA systems, such as regions in human telomerase RNA (hTR), internal ribosome entry site (IRES) and HIV genome. The lengths of these sequences range from 200-nt to 400-nt. The results show good agreements with the experiments.
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