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The BLOSUM-62 matrix is one of the best substitution matrices for detecting weak protein similarities. A single matrix may be reasonably efficient over a relatively broad range of evolutionary change. In general, different substitution matrices are tailored to detecting similarities among sequences that are diverged by differing degrees. A Substitution matrix assigns a score for aligning any possible pair of residues. Substitution matrices such as BLOSUM are used for sequence alignment of proteins. Gaps are usually penalized using a linear gap function that assigns an initial penalty for a gap opening, and an additional penalty for gap extensions, increasing the gap length. The score should be positive for similar residues and negative for dissimilar residues pair. When comparing proteins, one uses a similarity matrix which assigns a score to each possible residue. The algorithm is a Dynamic programming algorithm. The local algorithm finds an alignment with the highest score by considering only alignments that score positives and picking the best one from those. A good alignment then has a positive score and a poor alignment has a negative score. Matches increase the overall score of an alignment whereas mismatches decrease the score. The Smith-Waterman algorithm is motivated by giving scores for matches and mismatches. The gap penalty for a certain document quantifies how much of a given document is probably original or plagiarized.īioinformatics applications Global alignment Ī local sequence alignment matches a contiguous sub-section of one sequence with a contiguous sub-section of another.
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Therefore, using a good gap penalty model will avoid low scores in alignments and improve the chances of finding a true alignment. Representing these differing sub-sequences as gaps will allow us to treat these cases as “good matches” even though there are long consecutive runs with indel operations in the sequence. For instance, two protein sequences may be relatively similar but differ at certain intervals as one protein may have a different subunit compared to the other. Considering multiple gaps in a sequence as a larger single gap will reduce the assignment of a high cost to the mutations. Therefore, when scoring, the gaps need to be scored as a whole when aligning two sequences of DNA. Furthermore, single mutational events can create gaps of different sizes. The notion of a gap in an alignment is important in many biological applications, since the insertions or deletions comprise an entire sub-sequence and often occur from a single mutational event. Insertions or deletions can occur due to single mutations, unbalanced crossover in meiosis, slipped strand mispairing, and chromosomal translocation.