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Moreover, we rely on just one auxiliary matrix which is different from other greedy solutions which require two auxiliary matrices; We performed two controlled experiments in the unconstrained CIT domain (TTR 1.1 × TTR 1.2; TTR 1.2 × IPOG-F, jenny, IPO-TConfig, PICT, ACTS) with almost three times more participants, in each experiment, than in the previous one (Balera and Santiago Júnior 2016).
For any remaining matrices, we performed a X2 test to determine if there is a significant difference in the number of sites matching the matrix in the HSF-bound promoters relative to HSF-bound introns.
To understand sources of variance in these matrices, we performed PERMANOVA analyses (adonis function in vegan) with 10,000 permutations.
For both the 3-gene and 5-gene data matrices, we performed 100 maximum likelihood (ML) bootstrap replicates using GARLI v. 0.951 [ 52], which implements a genetic heuristic algorithm for the tree search.
To test the substitution matrices, we performed maximum likelihood calculations on each family of Table 2. Since the models compared have the same number of parameters, they can be compared using Maximum Likelihood (ML) values obtained using a reasonable phylogenetic tree topology [ 42, 43] (see Methods).
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Using [TiO2 Si NH3+][CHC−] as a matrix, we performed the analysis of various types of small molecules, including amino acids and dopamine.
Given that varimax rotation may impose some correlations between the columns of the principal component matrix, we performed permutations on the rows of the unrotated matrix, subsequently applying component rotation and calculating a random map on each permutation in the same way as it was done for the real principal components.
After equilibration step on simulation cell and achieve the minimum energy of composition of matrix, we performed an anneal procedure with molecular dynamics which it is included some consecutive NPT dynamics simulation cycles with temperature treatment.
To understand the information contained in this statistical coupling matrix, we performed an iterative two-dimensional clustering analysis.
To assess the collagen matrix, we performed picrosirius red staining and visualized the sections by polarization microscopy (Olympus BX51, Olympus, USA) as previously described [22].
As with the Total1080 matrix, we performed partitioned ML inference under best-fitting empirical models of protein evolution on the Best108 matrix.
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