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 language | English (US) |
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Pages (from-to) | 226-230 |
Number of pages | 5 |
Journal | Journal of Chemical Information and Computer Sciences |
Volume | 28 |
Issue number | 4 |
DOIs | |
State | Published - Nov 1 1988 |
ASJC Scopus subject areas
- General Chemistry
- Information Systems
- Computer Science Applications
- Computational Theory and Mathematics