Optimal Multiple Sequence Alignment

Pankaj Bhanbri¹ , O.P. Gupta²

1. Dept. of CSE, I.K.G. Punjab Technical University, Kapurthala, India.
2. School of EE and IT, Punjab Agriculture University, Ludhiana, India.

Correspondence should be addressed to: pkbhambri@gmail.com.

Section:Review Paper, Product Type: Isroset-Journal
Vol.3 , Issue.6 , pp.54-60, Jun-2017

Online published on Jun 30, 2017

Copyright © Pankaj Bhanbri, O.P. Gupta . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
The research in bioinformatics has accumulated large amount of data. The biological data is available in different formats and is comparatively more complex. The term bioinformatics is related to study of bio-molecules information. The informatics techniques are applied to understand and organize the information associated with these molecules. Bioinformatics offers different knowledge discovery concepts for molecular biology and has many practical applications. DNA sequence alignment is one of the applications of the bioinformatics. Multiple Sequence Alignment is used to align the biological sequences along a column. As the process generates distances of multiple alignments among the pairs of different species, phylogenetic tree is being formulated. Multiple sequence alignment arranges the sequences in such a way that evolutionarily equivalent positions across all sequences are matched. Alignment of Substitutions made into two categories: Jukes Cantor Method and Kimura’s Method.

Key-Words / Index Term :
Bioinformatics, Phylogenetic tree, Juke’s Cantor model, Kimura’s 2-parameter model

References :
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