13C NMR assignments of the bases in oligodeoxynucleotides: An automated procedure using bayesian statistics

Timothy J. Hyman, Eilis Boudreau, Gilles G. Martin, Béat M. Jucker, Philip N. Borer, George C. Levy

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A statistical method, Bayes Maximum Likelihood, has been applied to the classification of base 13C NMR resonances in DNA oligomers. An accuracy of 100% for carbon class discrimination was achieved for a preliminary training set of four oligomers using the following four parameters: (1) the chemical shift; (2) the temperature at which the spectrum was obtained; (3) the difference in chemical shift from the C5 resonances; and (4) a sequence factor representing the neighboring nucleotides. Classification of a fifth oligomer, previously assigned and not contained in the original training set, gave reasonable carbon class assignments.

Original languageEnglish (US)
Pages (from-to)226-230
Number of pages5
JournalJournal of Chemical Information and Computer Science
Volume28
Issue number4
StatePublished - 1988
Externally publishedYes

Fingerprint

Bayesian statistics
Oligodeoxyribonucleotides
Oligomers
Nuclear magnetic resonance
Statistics
Chemical shift
Carbon
statistical method
discrimination
Nucleotides
Maximum likelihood
Statistical methods
DNA
Temperature

ASJC Scopus subject areas

  • Chemistry(all)
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

13C NMR assignments of the bases in oligodeoxynucleotides : An automated procedure using bayesian statistics. / Hyman, Timothy J.; Boudreau, Eilis; Martin, Gilles G.; Jucker, Béat M.; Borer, Philip N.; Levy, George C.

In: Journal of Chemical Information and Computer Science, Vol. 28, No. 4, 1988, p. 226-230.

Research output: Contribution to journalArticle

Hyman, Timothy J. ; Boudreau, Eilis ; Martin, Gilles G. ; Jucker, Béat M. ; Borer, Philip N. ; Levy, George C. / 13C NMR assignments of the bases in oligodeoxynucleotides : An automated procedure using bayesian statistics. In: Journal of Chemical Information and Computer Science. 1988 ; Vol. 28, No. 4. pp. 226-230.
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