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The main application of pairwise alignment is retrieving biological sequences in databases based on similarity.

The main application of pairwise alignment is retrieving biological sequences in databases based on similarity. Correct Answer True

This process involves submission of a query sequence and performing a pairwise comparison of the query sequence with all individual sequences in a database. Thus, database similarity searching is pairwise alignment on a large scale. This type of searching is one of the most effective ways to assign putative functions to newly determined sequences.

Related Questions

If the two sequences share significant similarity, it is extremely ______ that the extensive similarity between the two sequences has been acquired randomly, meaning that the two sequences must have derived from a common evolutionary origin.
The resulting tree is then used to guide the alignment of the most closely related sequences and groups of sequences. The resulting alignment is a global alignment produced by the Needleman-Wunsch algorithm.
Progressive alignment methods use the dynamic programming method to build an MSA starting with the most related sequences and then progressively adding less related sequences or groups of sequences to the initial alignment.
The final step involves pairwise alignment by extending from the words in both directions while counting the alignment score using the same substitution matrix.
Annotation is based on finding significant alignment to sequences of known function in database similarity searches.
In EM algorithm, as an example, suppose that there are 10 DNA sequences having very little similarity with each other, each about 100 nucleotides long and thought to contain a binding site near the middle 20 residues, based on biochemical and genetic evidence. the following steps would be used by the EM algorithm to find the most probable location of the binding sites in each of the ______ sequences.
The major drawback of the progressive and iterative alignment strategies is that they are largely global alignment based and may therefore fail to recognize conserved domains and motifs among highly divergent sequences of varying lengths.
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Emotif uses which databases for alignment of sequences?