Discovery by Minimal Length Encoding: A Case Study in Molecular Evolution

Authors:
Aleksandar Milosavljević;Jerzy Jurka
Affiliations:
Linus Pauling Institute of Science and Medicine, 440 Page Mill Rd., Palo Alto, CA 94306. Current address: Genome Structure Group, Biological and Medical Research Division, Argonne National ...;Linus Pauling Institute of Science and Medicine, 440 Page Mill Rd., Palo Alto, CA 94306. JURKA@JMULLINS@STANFORD.EDU
Venue:
Machine Learning
Year:
1993

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Abstract

We apply the Minimal Length Encoding Principle to formalize inference about the evolution of macromolecular sequences. The Principle is shown to imply a combination of Weighted Parsimony and Compatibility methods that have long been used by biologists because of their good practical performance. The background assumptions are expressed as an encoding scheme for the observed data and as heuristic rules for selection of diagnostic positions in the sequences. The Principle was applied to discover new subfamilies of Alu sequences, the most numerous family of repetitive DNA sequences in the human genome.