Pairwise Sequence Alignment between HBV and HCC Using Modified Needleman Wunsch Algorithm

Abstract

Ths paper aims to find similarity of Hepatitis B virus (HBV) and Hepatocelluler Carcinoma (HCC) DNA sequences. It is very important in bioformatics task. The similarity of sequence allignments indicates that they have similarity of chemical and physical properties. Mutation of the virus DNA in X region has potential role in HCC. It is observed using pairwise sequence alignment of genotype-A in HBV. The complexity of DNA sequence using dynamic programming, Needleman-Wunsch algorithm, is very high. Therefore, it is purpose to modifiy the method of Needleman Wunsch algorithm for optimum global DNA sequence alignment. The main idea is to optimize filling matrix and backtracking proccess of DNA components.This method can also solve various length of the both sequence alignment.This research is applied to DNA sequence of 858 hepatitis B virus and 12 carcinoma patient, so that there are 10,296 pairwis of sequences. They are aligned globally using the purposed method and as a result, it is achieved high similarity of 96.547% and validity of 99.854%. Furhthermore, this method has reduced the complexity of original Needleman-Wunsch algorithm The reduction of computational time is as 34.6% and space complexity is as 42.52%.

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“…The other hand, many researchers have developed tools for diagnosis some diseases using bioinformatics approach including machine learning algorithm. The previous research has been conducted on pairwise DNA sequence alignment between hepatitis B virus (HBV) and hepatocarcinoma (HCC) using modified dynamic programming which improved performance of computation space and time [8]. Also, the related research have been conducted for classification of breast cancer using logistic regression, diabetic analylitics using data mining approach.…”