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.
| Original language | English |
|---|---|
| Article number | 104391 |
| Journal | Chemometrics and Intelligent Laboratory Systems |
| Volume | 217 |
| DOIs | |
| State | Published - 2021.10.15 |
Keywords
- Convolution neural network
- DNA
- Methylcytosine
- Natural language processing
- word2vec
Quacquarelli Symonds(QS) Subject Topics
- Computer Science & Information Systems
- Engineering - Petroleum
- Data Science
- Engineering - Chemical
- Chemistry
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