Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/116328
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Type: Journal article
Title: DFA7, a new method to distinguish between intron-containing and intronless genes
Author: Yu, C.
Deng, M.
Zheng, L.
He, R.
Yang, J.
Yau, S.-.T.
Citation: PLoS ONE, 2014; 9(7):e101363-1-e101363-10
Publisher: Public Library of Science (PLoS)
Issue Date: 2014
ISSN: 1932-6203
1932-6203
Statement of
Responsibility: 
Chenglong Yu, Mo Deng, Lu Zheng, Rong Lucy He, Jie Yang, Stephen S.-T. Yau
Abstract: Intron-containing and intronless genes have different biological properties and statistical characteristics. Here we propose a new computational method to distinguish between intron-containing and intronless gene sequences. Seven feature parameters α, β, γ, λ, θ, φ and σ based on detrended fluctuation analysis (DFA) are fully used, and thus we can compute a 7-dimensional feature vector for any given gene sequence to be discriminated. Furthermore, support vector machine (SVM) classifier with Gaussian radial basis kernel function is performed on this feature space to classify the genes into intron-containing and intronless. We investigate the performance of the proposed method in comparison with other state-of-the-art algorithms on biological datasets. The experimental results show that our new method significantly improves the accuracy over those existing techniques.
Keywords: Intron-containing genes
Rights: © 2014 Yu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RMID: 0030073940
DOI: 10.1371/journal.pone.0101363
Appears in Collections:Medicine publications

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