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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. A BLAST search enables a researcher to compare a subject protein or nucleotide sequence (called a query ...
CS-BLAST: Sequence-context specific BLAST, more sensitive than BLAST, FASTA, and SSEARCH. Position-specific iterative version CSI-BLAST more sensitive than PSI-BLAST: Protein: Angermueller C, Biegert A, Soeding J [3] 2013 CUDASW++ GPU accelerated Smith Waterman algorithm for multiple shared-host GPUs: Protein: Liu Y, Maskell DL and Schmidt B ...
This page is a subsection of the list of sequence alignment software. Multiple alignment visualization tools typically serve four purposes: Aid general understanding of large-scale DNA or protein alignments; Visualize alignments for figures and publication; Manually edit and curate automatically generated alignments; Analysis in depth
Alignment of 27 avian influenza hemagglutinin protein sequences colored by residue conservation (top) and residue properties (bottom) Multiple sequence alignment is an extension of pairwise alignment to incorporate more than two sequences at a time. Multiple alignment methods try to align all of the sequences in a given query set.
One would use a higher numbered BLOSUM matrix for aligning two closely related sequences and a lower number for more divergent sequences. It turns out that the BLOSUM62 matrix does an excellent job detecting similarities in distant sequences, and this is the matrix used by default in most recent alignment applications such as BLAST .
A BLAST variant called MegaBLAST indexes 4 databases to speed up alignments. [9] BLAT can extend on multiple perfect and near-perfect matches (default is 2 perfect matches of length 11 for nucleotide searches and 3 perfect matches of length 4 for protein searches), while BLAST extends only when one or two matches occur close together. [1] [9]
Another method is to identify homologous sequences based on other known gene sequences (Tools see Table 4.3). [39] The two methods described here are focused on the sequence. However, the shape feature of these molecules such as DNA and protein have also been studied and proposed to have an equivalent, if not higher, influence on the behaviors ...
One way to visualize the similarity between two protein or nucleic acid sequences is to use a similarity matrix, known as a dot plot. These were introduced by Gibbs and McIntyre in 1970 [1] and are two-dimensional matrices that have the sequences of the proteins being compared along the vertical and horizontal axes.