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Mobeen Ur Rehman(레흐만 모빈우르),Kil To Chong(정길도) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.10
DNA methylation is a modification mechanism that takes part in the number of biological functions including the normal development and proper functionality of the brain. The methylated DNA holds crucial epigenetic information. In recent years numerous research drills are carried out to propose efficient computational models for 6㎃ modification identification. Still, a great gap of improvement is available in the performance of these models. This paper proposes an efficient model for DNA N6-methyladenine modification identification in Rice genome. In proposed model one-hot encoding is applied to the input-sequence. The two convolution layers with a max-pooling layer and a dropout layer extract convolutional features and Long Short Term Memory (LSTM) gives the optimal interpretation to these features. The extracted optimal feature vector from Neural Network is embedded to the Naïve Bayes (NB) for the classification of DNA 6mA. The proposed model is evaluated on two publically available datasets of Rice genome. The proposed model has illustrated high performance when compared with other existing techniques. The high performance of the proposed model depicts its effectiveness.