Cart 2

Pairwise Sequence Alignment(local alignment)

Local Sequence Alignment finds local regions with the highest level of similarity between the two sequences. A local alignment aligns a substring of the query sequence to a substring of the target sequence. Any two sequences can be locally aligned as local alignment finds stretches of sequences with high level of matches without considering the alignment of rest of the sequence regions. Suitable for aligning more divergent sequences or distantly related sequences. Used for finding out conserved patterns in DNA sequences or conserved domains or motifs in two proteins. A general local alignment method is Smith–Waterman algorithm.

1. Enter 2 FASTA sequences(Protein/DNA/RNA, no more than 100 sequences, no exceeds 1MB):

Sequence Number:0

Sequence Length:0

Pairwise alignment

Pairwise sequence alignment methods are used to find the best-matching piecewise (local or global) alignments of two query sequences. Pairwise alignments can only be used between two sequences at a time, but they are efficient to calculate and are often used for methods that do not require extreme precision (such as searching a database for sequences with high similarity to a query). The three primary methods of producing pairwise alignments are dot-matrix methods, dynamic programming, and word methods;[1] however, multiple sequence alignment techniques can also align pairs of sequences. Although each method has its individual strengths and weaknesses, all three pairwise methods have difficulty with highly repetitive sequences of low information content - especially where the number of repetitions differ in the two sequences to be aligned. One way of quantifying the utility of a given pairwise alignment is the 'maximum unique match' (MUM), or the longest subsequence that occurs in both query sequences. Longer MUM sequences typically reflect closer relatedness.