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

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.

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Publisher Copyright: IEEE

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Computational modeling, DNA, Fuzzy logic, Fuzzy systems, Kernel, Kernel method, Sequence classification 16, Predictive models, Support vector machines

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10.1109/TFUZZ.2022.3159103

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Ding, Y, Tiwari, P, Zou, Q, Guo, F & Pandey, H M 2022, 'C-loss based Higher-order Fuzzy Inference Systems for Identifying DNA N4-methylcytosine Sites', IEEE Transactions on Fuzzy Systems, vol. 30, no. 11, pp. 4754-4765. https://doi.org/10.1109/TFUZZ.2022.3159103

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https://urn.fi/URN:NBN:fi:aalto-202204062764

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[article-cris] Perustieteiden korkeakoulu / SCI

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

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