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In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. [1]
The Smith–Waterman algorithm performs local sequence alignment; that is, for determining similar regions between two strings of nucleic acid sequences or protein sequences. Instead of looking at the entire sequence, the Smith–Waterman algorithm compares segments of all possible lengths and optimizes the similarity measure .
Combines DNA and Protein alignment, by back translating the protein alignment to DNA. DNA/Protein (special) Local or global: Wernersson and Pedersen: 2003 (newest version 2005) SAGA Sequence alignment by genetic algorithm: Protein: Local or global: C. Notredame et al. 1996 (new version 1998) SAM Hidden Markov model: Protein: Local or global: A ...
Multiple sequence alignment (MSA) is the process or the result of sequence alignment of three or more biological sequences, generally protein, DNA, or RNA. These alignments are used to infer evolutionary relationships via phylogenetic analysis and can highlight homologous features between sequences.
In bioinformatics, BLAST (basic local alignment search tool) [3] is an algorithm and program for comparing primary biological sequence information, such as the amino-acid sequences of proteins or the nucleotides of DNA and/or RNA sequences.
Recent development has focused on improving the time and space cost of the algorithm while maintaining quality. For example, in 2013, a Fast Optimal Global Sequence Alignment Algorithm (FOGSAA), [9] suggested alignment of nucleotide/protein sequences faster than other optimal global alignment methods, including the Needleman–Wunsch algorithm ...
Two important algorithms for aligning pairs of sequences are the Needleman-Wunsch algorithm and the Smith-Waterman algorithm. Popular tools for sequence alignment include: Pair-wise alignment - BLAST, Dot plots; Multiple alignment - ClustalW, PROBCONS, MUSCLE, MAFFT, and T-Coffee. A common use for pairwise sequence alignment is to take a ...
By comparing generated maps of RNA, DNA, and sequences from evolutionary families, people can assess conservation of proteins and find functional gene domains by comparing differences between evolutionary sequences. Generally, heuristic algorithms and tree alignment graphs are also adopted to solve multiple sequence alignment problems.