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Computer matching of oligonucleotide patterns on electrophoretic gels: An application to the epidemiology of cytomegalovirus

  • A. E. Ades
    ,
  • A. J. Garrett
    ,
  • ,
  • K. S. Chin
    ,
  • C. S. Peckham
  • University College London
    ,
  • Medicines and Healthcare Products Regulatory Agency
    ,
  • Imperial College London
Scholary Output:
Contribution to journal
Article
Peer-review

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

A computer program was written to analyse oligonucleotide patterns displayed by gel electrophoresis following restriction endonuclease digestion of human cytomegaloviral DNA, and was applied to an epidemiological study of the transmission of infection in a hospital special care baby unit, with regard to infant-to-infant and mother-to-infant transmission. The program calculates the molecular weight of oligonucleotides from their mobilities, using a cubic spline curve based on the mobilities of oligonucleotides from the AD169 strain. A matching algorithm then calculates the number of unmatched fragments for each pair of viral isolates. This was used as a similarity measure which successfully distinguished mother and infant isolate pairs from epidemiologically unrelated pairs. The program is not intended to provide fully automatic matching, but could be recommended as a screening device to pick out pairs of strains which are sufficiently similar to suggest a common source of infection, and which may warrant closer comparison. Other applications are discussed, and the possible use of densitometers to automate data entry is considered.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 467-479 (13 pages)

Journal (Volume, Issue Number)

Epidemiology and Infection (Volume 100, Issue 3)

Publication milestones

  • Published - 06/1988

Publication status

Published - 06/1988

ISSN

0950-2688

Publication IDs

  • Scopus: 0023932733
  • PubMed: 2837406

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