Dynamic Programming Alignment of Sequences Representing Cyclic Patterns

Jens Gregor, Michael G. Thomason

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on actual alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. Applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.

Original languageEnglish (US)
Pages (from-to)129-135
Number of pages7
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume15
Issue number2
DOIs
StatePublished - Jan 1 1993

Fingerprint

Dynamic programming
Dynamic Programming
Alignment
Strings
Algorithmic Complexity
DNA sequences
Costs
Protein Sequence
DNA Sequence
Search Algorithm
Satellites
Proteins

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

Cite this

Dynamic Programming Alignment of Sequences Representing Cyclic Patterns. / Gregor, Jens; Thomason, Michael G.

In: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 2, 01.01.1993, p. 129-135.

Research output: Contribution to journalArticle

@article{b5d71524814b461cb169bd61c89b3fbe,
title = "Dynamic Programming Alignment of Sequences Representing Cyclic Patterns",
abstract = "String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on actual alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. Applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.",
author = "Jens Gregor and Thomason, {Michael G.}",
year = "1993",
month = "1",
day = "1",
doi = "10.1109/34.192484",
language = "English (US)",
volume = "15",
pages = "129--135",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
issn = "0162-8828",
publisher = "IEEE Computer Society",
number = "2",

}

TY - JOUR

T1 - Dynamic Programming Alignment of Sequences Representing Cyclic Patterns

AU - Gregor, Jens

AU - Thomason, Michael G.

PY - 1993/1/1

Y1 - 1993/1/1

N2 - String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on actual alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. Applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.

AB - String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal alignment cost for strings representing cyclic patterns. A guided search algorithm uses bounds on actual alignment costs to find all optimal cyclic shifts. The bounds are derived from submatrices of an initial dynamic programming matrix. Algorithmic complexity is analyzed for major stages in the search. Applicability of the method is illustrated with satellite DNA sequences and circularly permuted protein sequences.

UR - http://www.scopus.com/inward/record.url?scp=0027539635&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027539635&partnerID=8YFLogxK

U2 - 10.1109/34.192484

DO - 10.1109/34.192484

M3 - Article

VL - 15

SP - 129

EP - 135

JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

SN - 0162-8828

IS - 2

ER -