Sentence examples for mean character difference from inspiring English sources

The mean character difference distances were measured between the samples directly, and eigen analysis of the distance matrix resulted in direct ordination of the samples.

Among a variety of different measures of distance or similarity that can be used for PCO analysis, the mean character difference was found to be comparable to several other genetic distance measures for binary data matrices and thus selected for use.

The following parameters were used to establish the distance phylogenetic tree based on the amino acid sequence alignment: i) 298 characters, ii) bootstrap method with neighbor-joining search at 1000 replicates was used for statistical analysis, iii) ties were broken at random, iv) distance measure  =  mean character difference.

The optimality criterion was set to distance (mean character difference, minimal evolution, negative branches = 0) and 1000 bootstrap replicates were performed using the BioNeighbor-Joining (BioNJ) algorithm.

The conditions were set to distance (mean character difference, minimal evolution, negative branches = 0), and 1,000 bootstrap replicates were performed by using the BioNeighbor-Joining algorithm.

Bootstrapping analysis was carried with heuristic search based on 1000 replicates and the distance measure was set to be equal to mean character difference.

The conditions were set to distance, neighbor-joining, with mean character differences, and dendrograms were constructed by using the 50% majority rule.

The NJ tree [ 67] was constructed based on mean character differences (distance) and bootstrap support values were determined based on 10,000 neighbor joining replicates.

Sequence comparisons between the taxa revealed uncorrected mean character differences of Koerneria to all Pristionchus species of 18.0 to 18.8%, whereas within the genus Pristionchus the concatenated ribosomal protein cDNA sequences differed by merely 1.7 – 10.3%.

The percentage of amino acid identity, the percentage of gaps and the uncorrected amino acid distances, corresponding to mean character differences per 100 aa adjusted for missing data, were calculated on the optimized protein alignment using PAUP* v4.0b10 [ 56].

The Mean model (the mean of pairwise character difference), which can adjust for missing data in the matrix, was used to calculate the pairwise distance.