Sentence examples for using a heuristic tree from inspiring English sources

One thousand bootstrap replicates were made using a heuristic tree search of 10 wagner trees (with random addition sequences) followed by TBR.

We also performed maximum parsimony (MP) analysis on the dataset using a heuristic tree search with 1000 random addition sequence replicates and TBR branch swapping.

ML model parameters chosen by MODELTEST were used in a heuristic tree search using PAUP*4.0b [66] with the PaupUp graphical interface [67].

PAUP* was then used to search for the maximum likelihood (ML) tree, based on the best fit model and parameter estimates given by ModelTest (Table 1) and using a heuristic search with tree bisection reconnection (TBR).

Subsequent maximum likelihood (ML) analyses were performed in PAUP* 4.0 b using a heuristic search with tree bisection reconnection (TBR) branch swapping.

The aligned sequences were exported for parsimony analysis by using a heuristic search with tree bisection reconnection branch swapping (MEGA6) and distant analysis by neighbor-joining (MEGA6).

Maximum-parsimony (MP) methods were implemented in PAUP 4.0b8 [ 48], using a heuristic search and tree bisection-reconnection (TBR) branch swapping option.

In TNT v1.1 [ 35] node support was assessed using jackknife resampling with 36% of characters removed and 1000 replicates, using a heuristic search with tree bisection-reconnection (TBR) branch swapping and 1000 random addition sequence replicates.

Maximum Parsimony (MP) analysis was carried out in PAUP (version 4.0b10, [ 64]) using a heuristic search and the tree bisection and reconnection (TBR) branch swapping method.

A Maximum-Likelihood (ML) tree was built using a heuristic search starting from a neighbour-joining tree and a tree bisection reconnection (TBR) algorithm for branch swapping, with random addition of sequences in PAUP* 4.0 [ 74].

Optimal trees were found using a heuristic search with the following options: tree-bisection-reconnection (TBR) branch-swapping, MulTrees option in effect, starting tree obtained via stepwise addition, trees held at each step = 5, and MaxTrees = 100.