2011Unpublished venueRequires access

Biological Sequence Alignment for Bioinformatics Applications Using MATLAB

Sonali Vijan

Open publisher page 6 citations

Abstract

Biological Sequence alignment is widely used operation in the field of Bioinformatics and computational biology as it is used to determine the similarity between the biological sequences. The two basic alignment algorithms i.e. Smith Waterman for local alignment and Needleman Wunsch for global alignment have been used in this paper. The algorithms have been developed and simulated using MATLAB for genome analysis and sequence alignment. The local and global alignment has been presented and the results are shown in the form of Dot plots and local and global scores for the sequences. The proposed work is a useful tool that can aid in the exploration, interpretation and visualization of data in the field of molecular biology.

About this research paper

What this paper is about

Biological Sequence alignment is widely used operation in the field of Bioinformatics and computational biology as it is used to determine the similarity between the biological sequences. The two basic alignment algorithms i.e. Smith Waterman for local alignment and Needleman Wunsch for global alignment have been used in this paper. The algorithms have been developed and simulated using MATLAB for genome analysis and sequence alignment. The local and global alignment has been presented and the results are shown in the form of Dot plots and local and global scores for the sequences. The proposed work is a useful tool that can aid in the exploration, interpretation and visualization of data in the field of molecular biology.

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OpenAlex reports 6 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Biological Sequence alignment is widely used operation in the field of Bioinformatics and computational biology as it is used to determine the similarity between the biological sequences. The two basic alignment algorithms i.e. Smith Waterman for local alignment and Needleman Wunsch for global alignment have been used in this paper. The algorithms have been developed and simulated using MATLAB for genome analysis and sequence alignment. The local and global alignment has been presented and the results are shown in the form of Dot plots and local and global scores for the sequences. The proposed work is a useful tool that can aid in the exploration, interpretation and visualization of data in the field of molecular biology.

Key concepts: Alignment-free sequence analysis, Smith–Waterman algorithm, Multiple sequence alignment, Sequence alignment, Visualization, Computer science, Field (mathematics), Structural alignment

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