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Reseach Article

Article:Effect of Neural Network Parameters on RNA Secondary Structure Classification

by Ruchi Mann, Shailendra Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 23 - Number 6
Year of Publication: 2011
Authors: Ruchi Mann, Shailendra Singh
10.5120/2894-3786

Ruchi Mann, Shailendra Singh . Article:Effect of Neural Network Parameters on RNA Secondary Structure Classification. International Journal of Computer Applications. 23, 6 ( June 2011), 6-9. DOI=10.5120/2894-3786

@article{ 10.5120/2894-3786,
author = { Ruchi Mann, Shailendra Singh },
title = { Article:Effect of Neural Network Parameters on RNA Secondary Structure Classification },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 23 },
number = { 6 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 6-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume23/number6/2894-3786/ },
doi = { 10.5120/2894-3786 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:09:25.969203+05:30
%A Ruchi Mann
%A Shailendra Singh
%T Article:Effect of Neural Network Parameters on RNA Secondary Structure Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 23
%N 6
%P 6-9
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Helix, Hairpin, Bulge, external loop, internal loop, multi-branch loop are the elements of RNA secondary structure. We have designed a neural network to classify the RNA sequence in to three categories i.e Hairpin, helix, neither of two. This can be extended to classify into all secondary structure elements. If all the elements are predicted then we can determine the entire structure of a RNA family. The parameters of neural network affect the performance of the network. But there are no rules to define the value of these parameters of network. For a given problem the optimal value of parameters can be obtained by performing the experiments on their values. This paper shows the effect on the performance of classification by varying the number of hidden layers, number of neurons and activation functions.

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Index Terms

Computer Science
Information Sciences

Keywords

Classification RNA secondary structure neural networks activation function number of hidden layers