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NEXT Generation sequencing technology is largely improved the development of molecular biology and genomic research. A huge volume of gene data or protein data can be generated with lesser cost, which leads to the exponential growth of existing gene banks or databases. Thus, it becomes a exciting task for conventional algorithms or tools to extract information with genetic significance among these ever increasing databases. There is an urgent need for advanced methods, algorithms, or tools to accomplish these complicated data analysis tasks on a more computationally powerful platform. After decades of development, the FPGA has proved itself in the field of high performance reconfigurable computation. For each generation, one can expect an immediate performance boost with the help of newer manufacturing technologies and a huge amount of volume resources on a single chip, both of which make it a competitive candidate for application acceleration.

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Surendar A. (2017). FPGA based parallel computation techniques for bioinformatics applications. International Journal of Research in Pharmaceutical Sciences, 8(2), 124-128. Retrieved from