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Statistical Analysis of DNA Sequence Data : a brief review

Shaw A. C.

Archives of Control Sciences

1999

Vol. 9, no. 1/2

171-181

Molecular biology and the Human Genome Project generate large amounts of nucleic acid sequence data. The volume of these data makes it imperative to develop statistical techniques to detect the inner organization of DNA sequences. We review several methodologies,including M-entropies and Hidden Markov Models. A number of recent references are discussed. The existing approaches proved to be of somewhat limited usefulness, except in the domain of sequence comparison, mainly because of simplistic assumptions of the models and complicated structure of the data. Further efforts are needed to improve this situation.