Smith-Waterman algorithm

A better alternative in order to find the best possible results would be to use the Smith-Waterman algorithm.

The Smith-Waterman algorithm is a general local alignment method also based on dynamic programming.

The Smith-Waterman algorithm is motivated by giving scores for matches and mismatches.

Use a banded Smith-Waterman algorithm to calculate an optimal score for alignment.

This work is based upon earlier publication showing a significant acceleration of the Smith-Waterman algorithm for aligning two sequences.

This program mathematically finds best local alignment between sequence pairs, a freely available implementation of the Smith-Waterman algorithm.

In particular, the Smith-Waterman algorithm (developed with Temple Smith) is the basis for many sequence comparison programs.

Instead of looking at the total sequence, the Smith-Waterman algorithm compares segments of all possible lengths and optimizes the similarity measure.

Different variants exist, see Smith-Waterman algorithm and Needleman-Wunsch algorithm.

The Smith-Waterman algorithm performs local sequence alignment; that is, for determining similar regions between two strings or nucleotide or protein sequences.

Two important algorithms for aligning pairs of sequences are the Needleman-Wunsch algorithm and the Smith-Waterman algorithm.

The PairWise algorithm is a variant of the Smith-Waterman algorithm best local alignment algorithm.

The Smith-Waterman algorithm serves as the basis for multi sequence comparisons, identifying the segment with the maximum local sequence similarity, see sequence alignment.

This step uses a banded Smith-Waterman algorithm to create an optimised score (opt) for each alignment of query sequence to a database(library) sequence.

Temple F. Smith is a university professor in biomedical engineering who helped to develop the Smith-Waterman algorithm developed with Michael Waterman in 1981.

This is further generalized by DNA sequence alignment algorithms such as the Smith-Waterman algorithm, which make an operation's cost depend on where it is applied.

DeCypher Smith-Waterman is an accelerated Smith-Waterman algorithm implementation, which also includes FrameSearch.

Smith-Waterman algorithm is used to construct a local alignment matrix H in the Dynamic Programming Local Alignment.

Therefore, the BLAST algorithm uses a heuristic approach that is less accurate than the Smith-Waterman algorithm but over 50 times faster.

The Smith-Waterman algorithm is fairly demanding of time: To align two sequences of lengths m and n, O(mn) time is required.

The technique of dynamic programming can be applied to produce global alignments via the Needleman-Wunsch algorithm, and local alignments via the Smith-Waterman algorithm.

JAligner is an open source Java implementation of the Smith-Waterman algorithm with Gotoh's improvement for biological local pairwise sequence alignment using the affine gap penalty model.

BLAST searches for high scoring sequence alignments between the query sequence and sequences in the database using a heuristic approach that approximates the Smith-Waterman algorithm.

Cray demonstrated acceleration of the Smith-Waterman algorithm using a reconfigurable computing platform based on FPGA chips, with results showing up to 28x speed-up over standard microprocessor-based solutions.

Accelerated version of the Smith-Waterman algorithm, on Intel and AMD based Linux servers, is supported by the GenCore 6 package, offered by Biocceleration.