Topology selection in unrooted molecular phylogenetic tree by minimum model-based complexity method.

H. Tanaka*, F. Ren, T. Okayama, T. Gojobori

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In reconstruction of phylogenetic trees from molecular data, it has been pointed out that multifurcate phylogenetic trees are difficult to be correctly reconstructed by the conventional methods like maximum likelihood method(ML). In order to resolve this problem, we have been engaged in developing a new phylogenetic tree reconstruction method, based on the minimum complexity principle widely used in the inductive inference. Our method, which we call "minimum model-based complexity (MBC) method", has been proved so far to be efficient in estimating multifurcate branching when the tree is described in the form of rooted one. In this study, we make further investigations about the efficiency of MBC method in estimating the multifurcation in unrooted phylogenetic trees. To do so, we conduct computer simulation in which the estimations by MBC method are compared with those by ML, AIC and statistical test approach. The results show that MBC method also provides good estimations even in the case of multifurcate unrooted trees and suggest that it could be generally used for reconstruction of phylogenetic tree having arbitrary multifurcations.

Original languageEnglish (US)
Pages (from-to)326-337
Number of pages12
JournalPacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
StatePublished - 1999
Externally publishedYes

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics


Dive into the research topics of 'Topology selection in unrooted molecular phylogenetic tree by minimum model-based complexity method.'. Together they form a unique fingerprint.

Cite this