ML Anthology

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

Aleksandar Milosavljevic, Jerzy Jurka
MLJ 1993 pp. 69-87
doi:10.1007/BF00993061 /mlj/1993/milosavljevic1993mlj-discovery/

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.

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Text

Milosavljevic and Jurka. "Discovery by Minimal Length Encoding: A Case Study in Molecular Evolution." Machine Learning, 1993. doi:10.1007/BF00993061

Markdown

[Milosavljevic and Jurka. "Discovery by Minimal Length Encoding: A Case Study in Molecular Evolution." Machine Learning, 1993.](https://mlanthology.org/mlj/1993/milosavljevic1993mlj-discovery/) doi:10.1007/BF00993061

BibTeX

@article{milosavljevic1993mlj-discovery,
  title     = {{Discovery by Minimal Length Encoding: A Case Study in Molecular Evolution}},
  author    = {Milosavljevic, Aleksandar and Jurka, Jerzy},
  journal   = {Machine Learning},
  year      = {1993},
  pages     = {69-87},
  doi       = {10.1007/BF00993061},
  volume    = {12},
  url       = {https://mlanthology.org/mlj/1993/milosavljevic1993mlj-discovery/}
}