Question

what is pairwise sequence analysis?​

Answer 1

Answer:

Explanation:

Pairwise Sequence Alignment is used to identify regions of similarity that may indicate functional, structural and/or evolutionary relationships between two biological sequences (protein or nucleic acid

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Answer 2

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Let’s consider 3 methods for pairwise sequence alignment: 1) dot plot, 2) global alignment, and 3) local alignment.

Dot Plot

The simplest method is the dot plot. One sequence is written out horizontally, and the other sequence is written out vertically, along the top and side of an m x n grid, where m and n are the lengths of the two sequences. A dot is placed in a cell in the grid wherever the the two sequences match. A diagonal line in the grid visually shows where the two sequences have sequence identity. Nucleic acid sequence dot plot comparisons will show a very high level of background

Global Alignment: Needleman-Wunsch

The algorithm published by Needleman and Wunsch in 1970 for alignment of two protein sequences was the first application of dynamic programming to biological sequence analysis. The Needleman-Wunsch algorithm finds the best-scoring global alignment between two sequences. A blog post by Chetan has a very clear explanation of how this works. Global alignments are most useful when the two sequences being compared are of similar lengths, and not too divergent.

Local Alignment: Smith-WatermanReal

life is often complicated, and we observe that genes, and the proteins they encode, have undergone exon-shuffling, recombination, insertions, deletions, and even fusions. Many proteins exhibit modular architecture. In searching databases for similar sequences, it is useful to find sequences that have similar domains or functional motifs. Smith & Waterman (1981) published an application of dynamic programming to find optimal local alignments. The algorithm is similar to Needleman-Wunsch, but negative cell values are reset to zero, and the traceback procedures starts from the highest scoring cell, anywhere in the matrix, and ends when the path encounters a cell with a value of zero.

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