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C-loss based Higher-order Fuzzy Inference Systems for Identifying DNA N4-methylcytosine Sites.

Ding, Y., Tiwari, P., Zou, Q., Guo, F. and Pandey, H. M., 2022. C-loss based Higher-order Fuzzy Inference Systems for Identifying DNA N4-methylcytosine Sites. IEEE Transactions on Fuzzy Systems. (In Press)

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DOI: 10.1109/TFUZZ.2022.3159103

Abstract

DNA methylation is an epigenetic marker, that plays an important role in the biological processes of regulating gene expression, maintaining chromatin structure, imprinting genes, inactivating X chromosomes, and developing embryos. The traditional detection method is time-consuming. Currently, researchers have used effective computational methods to improve the efficiency of methylation detection. This study proposes a fuzzy model with correntropy induced loss (C-loss) function to identify DNA N4-methylcytosine (4mC) sites. To improve the robustness and performance of the model, we use kernel method and the C-loss function to build a higher-order fuzzy inference system (HFIS). To test performance, our model is implemented on six 4mC and eight UCI data sets. The experimental results show that our model achieves better prediction performance.

Item Type:Article
ISSN:1063-6706
Uncontrolled Keywords:Fuzzy systems; DNA; Support vector machines; Fuzzy logic; Computational modeling; Predictive models; Kernel method; Sequence classification 16
Group:Faculty of Science & Technology
ID Code:36992
Deposited By: Symplectic RT2
Deposited On:30 May 2022 09:33
Last Modified:30 May 2022 09:33

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