ArticlePloS one2014
DFA7, a new method to distinguish between intron-containing and intronless genes.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Computational Prediction and Analysis of Associations between Small Molecules and Binding-Associated S-Nitrosylation Sites.Molecules (Basel, Switzerland) · 2018Article
- Genes from the TAS1R and TAS2R Families of Taste Receptors: Looking for Signatures of Their Adaptive Role in Human Evolution.Genome biology and evolution · 2018Article
- Long Non-Coding RNA Review and Implications in Lung Diseases.JSM Bioinformatics, genomics and preteomics · 2018Article
- Single-nucleotide variant proportion in genes: a new concept to explore major depression based on DNA sequencing data.Journal of human genetics · 2017Article
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Authors and funding
6 authors.
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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.
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