The application of model-based complexity inference method to molecular evolution analysis

Fengrong Ren*, Tanaka Hiroshi, Toshitsugu Okayama, Takashi Gojobori

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this study, a new method based on the concept of complexity in inductive inference is proposed for reconstructing molecular phylogenetic tree. This method describes the complexity of molecular phylogenetic tree by three terms, which are related to tree topology, the branch lengths and fitness between the model and data measured by likelihood function. The computer simulation is used to investigate the efficiency of this method. The results suggest that this method is superior to the traditional methods because it avoids excess-complexity in the tree model estimation available from DNA sequence.

Original languageEnglish (US)
Title of host publicationMedInfo 1998 - 9th World Congress on Medical Informatics
PublisherIOS Press
Pages367-371
Number of pages5
ISBN (Print)9051994079, 9789051994070
DOIs
StatePublished - Jan 1 1998
Event9th World Congress on Medical Informatics, MedInfo 1998 - Seoul, Korea, Republic of
Duration: Aug 18 1998Aug 22 1998

Publication series

NameStudies in Health Technology and Informatics
Volume52
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other9th World Congress on Medical Informatics, MedInfo 1998
CountryKorea, Republic of
CitySeoul
Period08/18/9808/22/98

Keywords

  • Maximum likelihood method
  • Minimum model-based complexity Method
  • Molecular Phylogenetic Tree

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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