Finite-state models in the alignment of macromolecules L. Allison C. S. Wallace C. N. Yee Article Received: 05 June 1991 Revised: 02 December 1991 Accepted: 23 December 1991 DOI :
10.1007/BF00160262

Cite this article as: Allison, L., Wallace, C.S. & Yee, C.N. J Mol Evol (1992) 35: 77. doi:10.1007/BF00160262
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Summary Minimum message length encoding is a technique of inductive inference with theoretical and practical advantages. It allows the posterior odds-ratio of two theories or hypotheses to be calculated. Here it is applied to problems of aligning or relating two strings, in particular two biological macromolecules. We compare the r-theory, that the strings are related, with the null-theory, that they are not related. If they are related, the probabilities of the various alignments can be calculated. This is done for one-, three-, and five-state models of relation or mutation. These correspond to linear and piecewise linear cost functions on runs of insertions and deletions. We describe how to estimate parameters of a model. The validity of a model is itself an hypothesis and can be objectively tested. This is done on real DNA strings and on artificial data. The tests on artificial data indicate limits on what can be inferred in various situations. The tests on real DNA support either the three- or five-state models over the one-state model. Finally, a fast, approximate minimum message length string comparison algorithm is described.

Key words Alignment Edit distance Homology Inductive inference Minimum message length Similarity String Offprint requests to: L. Allison

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Authors and Affiliations L. Allison C. S. Wallace C. N. Yee 1. Department of Computer Science Monash University Australia