Pairwise Sequence Alignment Similarity Score Prediction on Mushroom Biological data

Abstract

The role of data science is highly essential in the field of bioinformatics; this is one of the emerging trends in the new era to discover novel insights for the benefit of societal need related to disease and drug discovery. In bioinformatics, sequence alignment is the basic process to identify the similar species. This paper contributes the essence of pairwise sequence alignment algorithm to determine the similar strains of 30 Mushrooms (5.8s rRNA) sequence around Tamilnadu, India. This proposed system given solution to predict, as different categorical ranges of similarity score by comparing all the nucleotide sequences. Though many alignment tools are available in the online, retrieval of raw data with the maximum probability of alignment comparison between sequences with the better data visualization is unique than the Blast alignment tool. Also, it can be convenient to the end user on seeing maximum comparison of alignments in detail as well as it leads to future research enhancement on discovering new perceptions in the sequence alignments.