Introduction
Sequence alignment methods aim to both identify related protein sequences and determine the best alignment between them. This approach provides a rough measure of evolutionary distance and may indicate possible relationships between the protein structure and function of similar sequences. Multiple scoring matrices have been developed based on the techniques of the percent of accepted mutations (PAM) [3] and protein blocks (BLOSUM) [5] to quantify this evolutionary distance between aligned residues.
The pairwise sequence alignment problem is most commonly addressed through either (i) global alignment or (ii) local alignment techniques. The goal of global alignment algorithms is to determine the highest scoring overall alignment spanning the length of both sequences. One widely used approach for this problem is a dynamic programming approach proposed by Needleman and Wunsch [10].
Proteins may share sequence similarity in some regions, but not in others. Local...
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McAllister, S.R., Rajgaria, R., Floudas, C.A. (2008). Global Pairwise Protein Sequence Alignment via Mixed-Integer Linear Optimization . In: Floudas, C., Pardalos, P. (eds) Encyclopedia of Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-74759-0_250
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