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Soft Computing based Model for Identification of Pseudoknots in RNA Sequence using Learning Grammar

by Ankita Jiwan, Shailendra Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 9
Year of Publication: 2012
Authors: Ankita Jiwan, Shailendra Singh
10.5120/8591-2344

Ankita Jiwan, Shailendra Singh . Soft Computing based Model for Identification of Pseudoknots in RNA Sequence using Learning Grammar. International Journal of Computer Applications. 54, 9 ( September 2012), 1-7. DOI=10.5120/8591-2344

@article{ 10.5120/8591-2344,
author = { Ankita Jiwan, Shailendra Singh },
title = { Soft Computing based Model for Identification of Pseudoknots in RNA Sequence using Learning Grammar },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 9 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number9/8591-2344/ },
doi = { 10.5120/8591-2344 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:13.239538+05:30
%A Ankita Jiwan
%A Shailendra Singh
%T Soft Computing based Model for Identification of Pseudoknots in RNA Sequence using Learning Grammar
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 9
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

RNA structure prediction is one of the major topics in bioinformatics. Among the various RNA structures, pseudoknots are the most complex and unique structure. Various methods have been used for modeling RNA pseudoknotted secondary structure. In this paper a new model for prediction of RNA pseudoknot structure has been proposed. In this model, features of two existing techniques, i. e. neural network and grammar are combined. The advantage of grammar, identification based on rules is combined with the strength of a neural network to learn. An Elman neural network is used to learn the context free grammar that represents a pseudoknot. This Learning grammar network further identifies if the RNA sequence contains pseudoknot or not. Learning grammar helps in reducing the drawbacks of both neural network and grammar thus increasing the overall power of identifying sequences with pseudoknots.

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Index Terms

Computer Science
Information Sciences

Keywords

Minimum Free Energy Pseudoknots Soft Computing Elman Neural Network Grammar Context Free Grammar

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