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Abstract

Compression of DNA sequence is rapidly evolving as a field of research. The researchers are persistently analysing the DNA sequences for several purposes. Hence, the DNA sequences have to be stored and transmitted for analysing the DNA sequences. However, the huge size of the DNA sequences leads to a high cost for transmission. Thus, compressing the DNA sequence data is essential to reduce the size, minimise transmission costand help in achieving efficient analysis. This study aimed to set the encoder and decoder for DNA sequence compression. This study proposed a deep LSTM Neural Network to compress the DNA sequence that leads to various merits effectively. Initially, the DNA sequence dataset is taken as input. The data is loaded, and the vectorizer technique is performed using the encoder, channel and decoder. Then, the encoder and decoder are set for compression. The compression process is performed through the proposed Deep LSTM Neural Network. The Deep LSTM Neural Network consists of the LSTM layer, dense layer and hidden layer. The trained model is taken into account to find the compression results. Thus the results are finally analysed to validate its efficiency.