Alignment of 27 avian influenza hemagglutinin protein sequences colored by residue conservation (top) and residue properties (bottom)
Index plot of 10 family life sequences
Edit distance matrix for two words using cost of substitution as 1 and cost of deletion or insertion as 0.5
Dynamic time warping
A profile HMM modelling a multiple sequence alignment
Two repetitions of a walking sequence recorded using a motion-capture system. While there are differences in walking speed between repetitions, the spatial paths of limbs remain highly similar.

The method was tailored to social sciences from a technique originally introduced to study molecular biology (protein or genetic) sequences (see sequence alignment).

- Optimal matching

It is closely related to pairwise string alignments.

- Levenshtein distance

The optimal match is denoted by the match that satisfies all the restrictions and the rules and that has the minimal cost, where the cost is computed as the sum of absolute differences, for each matched pair of indices, between their values.

- Dynamic time warping

This sequence alignment method is often used in time series classification.

- Dynamic time warping

This has a wide range of applications, for instance, spell checkers, correction systems for optical character recognition, and software to assist natural-language translation based on translation memory.

- Levenshtein distance

The Levenshtein Distance algorithm has also been used in OCR post-processing to further optimize results from an OCR API.

- Optical character recognition

The methods used for biological sequence alignment have also found applications in other fields, most notably in natural language processing and in social sciences, where the Needleman-Wunsch algorithm is usually referred to as Optimal matching.

- Sequence alignment
Alignment of 27 avian influenza hemagglutinin protein sequences colored by residue conservation (top) and residue properties (bottom)

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