Sequence similarity - a non-aligning technique

C.H. Elzinga

doi:10.1177/0049124103253373

Sequence similarity - a non-aligning technique

C.H. Elzinga

Research output: Contribution to Journal › Article › Academic › peer-review

137 Downloads (Pure)

Abstract

This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformulates the concept of sequence similarity in terms of a binary precedence relation. This precedence relation is then used to develop a new quantification of sequence similarity. The new measure is used to reanalyze the life history data that were previously discussed by Dijkstra and Taris (1995). The reanalysis demonstrates the new measure to be superior to the OM algorithm and the alternatives proposed by Dijkstra and Taris. A new algorithm is presented to enumerate matching k-tuples from pairs of sequences in polynomial time.

Original language	English
Pages (from-to)	3-29
Number of pages	27
Journal	Sociological Methods and Research
Volume	32
Issue number	1
DOIs	https://doi.org/10.1177/0049124103253373
Publication status	Published - 2003

Access to Document

10.1177/0049124103253373

157419Final published version, 132 KB

Cite this

@article{f820d619262249cfbe61eeeb4cf1d2ad,

title = "Sequence similarity - a non-aligning technique",

abstract = "This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformulates the concept of sequence similarity in terms of a binary precedence relation. This precedence relation is then used to develop a new quantification of sequence similarity. The new measure is used to reanalyze the life history data that were previously discussed by Dijkstra and Taris (1995). The reanalysis demonstrates the new measure to be superior to the OM algorithm and the alternatives proposed by Dijkstra and Taris. A new algorithm is presented to enumerate matching k-tuples from pairs of sequences in polynomial time.",

author = "C.H. Elzinga",

year = "2003",

doi = "10.1177/0049124103253373",

language = "English",

volume = "32",

pages = "3--29",

journal = "Sociological Methods and Research",

issn = "0049-1241",

publisher = "SAGE Publications Inc.",

number = "1",

}

TY - JOUR

T1 - Sequence similarity - a non-aligning technique

AU - Elzinga, C.H.

PY - 2003

Y1 - 2003

N2 - This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformulates the concept of sequence similarity in terms of a binary precedence relation. This precedence relation is then used to develop a new quantification of sequence similarity. The new measure is used to reanalyze the life history data that were previously discussed by Dijkstra and Taris (1995). The reanalysis demonstrates the new measure to be superior to the OM algorithm and the alternatives proposed by Dijkstra and Taris. A new algorithm is presented to enumerate matching k-tuples from pairs of sequences in polynomial time.

AB - This article reviews objections to optimal-matching (OM) algorithms in sequence analysis and reformulates the concept of sequence similarity in terms of a binary precedence relation. This precedence relation is then used to develop a new quantification of sequence similarity. The new measure is used to reanalyze the life history data that were previously discussed by Dijkstra and Taris (1995). The reanalysis demonstrates the new measure to be superior to the OM algorithm and the alternatives proposed by Dijkstra and Taris. A new algorithm is presented to enumerate matching k-tuples from pairs of sequences in polynomial time.

U2 - 10.1177/0049124103253373

DO - 10.1177/0049124103253373

M3 - Article

VL - 32

SP - 3

EP - 29

JO - Sociological Methods and Research

JF - Sociological Methods and Research

SN - 0049-1241

IS - 1

ER -

Sequence similarity - a non-aligning technique

Abstract

Access to Document

Fingerprint

Cite this