Beyond Traditional Computing - Harnessing the Power of DNA Computing for Massive-Scale Data Processing

Still, DNA computing which is a relatively new paradigm of data processing represents an amazing potential for seeing the ability to solve computational issues on a vast level. This paper seeks to discuss how DNA molecules can be used to compute, given that the molecules can process problems in parallelism, store data, and use minimal energy. The proposed methodology represents abstract computational problems in form of DNA sequences so that biochemical operations can be performed in parallel on large scale. Results have shown that this approach to parallelism has separated tremendous computational time improvements, as much as 97%, and energy decrease of up to 99%. 99%, as compared to the conventional computing systems. The feasibility and practical applications of DNA computing have been demonstrated by this method’s capacity to solve NP-complete and combinatorial problems such as TSP, Boolean satisfiability, and protein folding and the applicability of this method in cryptography and possibly in big data applications. The higher error rates are a problem that cannot be erased entirely and are attributed to biochemical limitations. Added to this, error correction mechanisms are also incorporated into the methodology to improve accuracy but there is a required development for critical improvement for its broad application. This study shows the applicability and enormous benefits of using DNA computing to perform computations on a large scale making it more feasible to support silicon-based systems that are viable in the future computing for hard problem solving.