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논문 기본 정보

자료유형
학술대회자료
저자정보
Jhabindra Khanal (Chonbuk National University) Seung Bin Cho (Chonbuk National University) Kil To Chong (Chonbuk National University)
저널정보
대한전자공학회 대한전자공학회 학술대회 2020년도 대한전자공학회 하계종합학술대회 논문집
발행연도
2020.8
수록면
1,996 - 1,999 (4page)

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초록· 키워드

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DNA N4- methylcytosine (4mC) plays a crucial role in transcriptional regulation by repressing activity. DNA methylation takes part in many biological process such as Restriction –Modification(R-M) system, genomic imprinting, heredity performance, chromatin structure and suppression or repetitive sequences. In recent decades, computationally prediction of 4mC sites is much needed work in biomedical related fields. Experimental methods are costly and time-consuming so that we proposed a deep learning model to identify 4mc sits in the given DNA sequences. The previous method was developed by machine learning based method for identifying 4mC sites based on the handcrafted features while the proposed novel method extracts the features of the 4mC sites automatically using convolutional neural network (CNN). In this work, we applied the nucleotide chemical properties to encode the DNA sequences and fed those encoded sequences into the CNN model for the best feature selection and for the final classification whether the DNA sequence contains 4mC sites or not. The performance of the CNN model has been evaluated on the benchmark datasets and achieved generally good performance in predicting 4mC sites as compared to the previous method.

목차

Abstract
1. Introduction
2. Methods and materials
3. Result and discussion
4. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2020-569-001134194