Maximum likelihood Jukes-Cantor triplets: Analytic solutions

Benny Chor, Michael D. Hendy, Sagi Snir

Research output: Contribution to journalArticlepeer-review


Maximum likelihood (ML) is a popular method for inferring a phylogenetic tree of the evolutionary relationship of a set of taxa, from observed homologous aligned genetic sequences of the taxa. Generally, the computation of the ML tree is based on numerical methods, which in a few cases, are known to converge to a local maximum on a tree, which is suboptimal. The extent of this problem is unknown, one approach is to attempt to derive algebraic equations for the likelihood equation and find the maximum points analytically. This approach has so far only been successful in the very simplest cases, of three or four taxa under the Neyman model of evolution of two-state characters. In this paper we extend this approach, for the first time, to four-state characters, the Jukes-Cantor model under a molecular clock, on a tree T on three taxa, a rooted triple. We employ spectral methods (Hadamard conjugation) to express the likelihood function parameterized by the path-length spectrum. Taking partial derivatives, we derive a set of polynomial equations whose simultaneous solution contains all critical points of the likelihood function. Using tools of algebraic geometry (the resultant of two polynomials) in the computer algebra packages (Maple), we are able to find all turning points analytically. We then employ this method on real sequence data and obtain realistic results on the primate-rodents divergence time.

Original languageEnglish
Pages (from-to)626-632
Number of pages7
JournalMolecular Biology and Evolution
Issue number3
StatePublished - Mar 2006
Externally publishedYes


  • Analytical solutions
  • Hadamard conjugation
  • Jukes-Cantor
  • Maximum likelihood
  • Phylogenetic trees
  • Symbolic algebra

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics


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