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A distance-based tree was constructed under minimum evolution criteria [ 34].
Neighbor-joining was used to make phylogenetic trees based on these matrices, employing the minimum evolution criteria in PAUP [ 54].
The close-neighbour-interchange heuristic search algorithms for finding the optimal tree under the minimum evolution criteria were used, where a temporary neighbour-joining tree [ 88] was generated for comparison [ 89], using dynamic criteria [ 90].
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The minimum evolution criterion was used and branch lengths were allowed to be negative except when calculating tree scores.
Phylogenetic trees from the post-vaccination data set and the two data sets combined were built using MEGA 2.1 [ 25] and the minimum evolution criterion.
The modified NJst method, called the MEst method, was implemented in R [ 73] with an external call to fastME [ 76] for the calculation of the minimum evolution criterion.
The minimum evolution criterion was used by applying maximum likelihood distances estimated with the model chosen by Modeltest in the neighbor-joining analysis.
Pairwise TREx distances were used to generate lengths for the branches connecting the swine paralogs using the minimum evolution criterion in PAUP.
From this point of view, NJ is "optimal" when the algorithm outputs the tree which minimizes the balanced minimum evolution criterion.
The CFTR tree topology searches were conducted using the minimum evolution criterion with 10,000 replicates of random sequence addition in PAUP [ 29].
We believe that a deeper understanding of the "mistakes" NJ makes when it does not optimize the balanced minimum evolution criterion may be important in interpreting the results, especially for large trees.
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CEO of Professional Science Editing for Scientists @ prosciediting.com