Intelligent and robust computational prediction model for DNA N4-methylcytosine sites via natural language processing

Abstract DNA N4-methylcytosine (4 ​mC) is an essential epigenetic modification and performs crucial roles in restriction-modification systems. The 4 ​mC involves many essential cellular processes, namely: correcting DNA replication and controlling DNA replication errors in the prokaryotic organism. In order to understand their biological functional mechanisms, the prediction of 4 ​mC modification is indispensable. Although computationally, it was targeted but the desired outcomes were not obtained. Thus, the development of an intelligent computational prediction system that truly expresses 4 ​mC modification sites is imperative. An efficient and high throughput discriminative intelligent computational system called “iDNA-4mC-DL” is introduced using the natural language processing method “word2vec” along with a convolution neural network. The obtained outcomes authenticated that the proposed iDNA-4mC-DL system performs outstandingly on six publicly available benchmark and independent datasets compared to current tools. It is, thus, highly estimated that the proposed model might be a more supportive and applied tool for rudimentary research and academia.

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