Cipher constrained encoding for constraint optimization in extended nucleic acid memory

As the time elapsed by, the present real life problems have guided the human race towards a data driven society. This in turn caused an exponential hype of data generation globally that led to a new challenge for the human to store and manage such an enormous amount of data. It was further analysed through other research works that this is going to manufacture immense tension on the availability of silicon and magnetic memories in the near future. At this point in time, good data compression algorithms became the prime focus of the computing community. However, it was able to check the pace of the growing scarcity of data storage technologies but could not solve the problem from the root. As a result, it became a necessity to develop an efficient alternative data storage technology when the Nucleic Acid Memory (NAM) was brought forward as a promising solution. On the other hand, the research on expansion of the genetic alphabets beyond the standard nucleotides have emerged recently which have drawn a significant attention in the domain of biological science simultaneously. This led to the creation of the Extended Nucleic Acid Memory (ENAM). However, the initial proposals were put forward without considering the real life sequencing constraints namely the homopolymer runlength and the GC content constraint. But, it was observed in the literature that encoding techniques which accounted for countering the sequencing constraints had to pay a penalty in terms of digital data holding capacity per nucleotide. In this context, taking the inspiration from the domain of cryptography a new encoding algorithm namely the Cipher Constrained Encoding (CCE) has been proposed in this work which has the capability of considering both the sequencing constraints without significantly penalizing the data capacity per nucleotide. Few properties of the Vigenére and Vernam Cipher have been adapted and integrated with basic statistical analytical techniques which was very efficient in checking the violation of the sequencing constraints. Furthermore, experimentation has been done and the results have been reported and compared with the previous works found in the literature which demonstrated promising outcome.