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Rate heterogeneity among sites was modelled using the gamma model.
We subsequently estimated the optimal parameters and the log-likelihood using the GAMMA model of rate heterogeneity.
Gaps were removed manually, and all alignments were analyzed using RAxML v 7.2.6 [ 86] using the Gamma model of rate heterogeneity and the WAG substitution matrix with 100 bootstrap replicates.
Calculation of log-likelihood values was performed using the GAMMA model of rate heterogeneity and empirical base frequencies with RAxML 7.3.1 (PTHREADS) on the MESCA System of the HPC Linux Cluster CHEOPS, RRZK, University of Cologne.
All the Molly-like repeats, the active copy, the alignment 'majority' consensus sequence and the new deRIP consensus sequence were compared via RAxML (using the gamma model and maximum-likelihood phylogeny) [ 39].
Distances were estimated by the Tamura-Nei method [ 15], using the gamma model to correct for multiple hits and to account for excess transitions, unequal nucleotide frequencies, and variation of the substitution rate among different sites.
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For amino acids, neighbor-joining trees were calculated using the gamma distance model that considers the dissimilarity of substitution rates among sites.
ML tree topologies were constructed using the software PUZZLE 4.0 [ 43], employing 1000 puzzling steps, the JTT substitution matrix, estimation of rate heterogeneity using the gamma distribution model with eight rate categories, and the gamma-parameter estimation from the dataset.
There are numerous cases of using the gamma distribution when modeling insurance losses (e.g., Hürlimann2001; Furman and Landsman2005; Alai et al.2013).2013
The JTT amino acid substitution model was used with the Gamma model of rate heterogeneity.
We used various groups of angiosperms, lizards, harvestmen, caddisflies and diving beetles, and tested diversification models using the gamma statistic [ 34] and likelihood models [ 35].
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