Nature Inspired Algorithms for Genome Subsequence Assembly in Hadoop

摘要

Genome subsequencing has become one of the normal requirements of the modern era due to the huge possibilities it provides for personalized medicine. Assembled genome sequencing will give valuable consciousness into numerous aspects of human life, thereby generating healthier environments and personalized treatments. The most important need of this field is for a quicker and accurate sequencing device. The methods for genome sequencing become very hard due to the massive amount of genome fragments. This paper extents an optimized genome assembly technique with nature inspired algorithm using MapReduce. DNA subsequence is initially matched with the genome to identify the possible matching locations. These identified points are then analyzed for complete matches. The consensus sequence assembly is performed by employing hamming distance identical systems. The experimental outcomes analyzed display that our method is improved and shows high coverage by providing exact sequence alignments.