title: 13C NMR assignments of the bases in oligodeoxynucleotides: an automated procedure using Bayesian statistics.
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.
authors.affiliation: NIH Research Resource for NMR and Data Processing, Syracuse University, New York 13244-1200.
authors.forename: T J
authors.initials: TJ
authors.lastname: Hyman
authors.forename: E A
authors.initials: EA
authors.lastname: Boudreau
authors.forename: G G
authors.initials: GG
authors.lastname: Martin
authors.forename: B M
authors.initials: BM
authors.lastname: Jucker
authors.forename: P N
authors.initials: PN
authors.lastname: Borer
authors.forename: G C
authors.initials: GC
authors.lastname: Levy
mesh_terms: D001483:Base Sequence; D001499:Bayes Theorem; D002247:Carbon Isotopes; D009682:Magnetic Resonance Spectroscopy; D009838:Oligodeoxyribonucleotides; D011336:Probability; D012985:Software Design
chemical_list: D002247:Carbon Isotopes; D009838:Oligodeoxyribonucleotides