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Abstract
Developments in the statistical analysis of DNA sequence data since 1984 are reviewed. Mathematical methods employing dynamic programming or incorporating Markov chain theory have been developed to search sequences for regions of similarity and to align sequences. When the biological forces of mutation and genetic drift are included in models, distances between aligned sequences allow the construction of evolutionary trees. Theory based on models may lead to estimates of variation of parameter estimates and so give a means of assessing the statistical significance of observed patterns and relationships. The complexity of DNA sequences, however, suggests that most statistical inferences will rest on random permutations of sequences.
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