Sentence examples for dataset length from inspiring English sources

In a Bayesian framework, the partition with the worst model estimates (3rd codon positions) produced relatively accurate branch length estimates compared to other partitions with better-estimated models, although this may also reflect increased dataset length.

For this experiment 1000 motifs were generated with the following parameters: T P ∈ [ 15, 50]; T N ∈ (50 - T P ) (50 sequences for the positive dataset); F P ∈ [0, 35]; F N ∈ (100 - F P ) (100 sequences in the negative dataset); Length ∈ [ 5, 7] amino acid symbols and numGaps ∈ [0, 5]. Figure 3 shows the correlation matrix for the 14 measures.

Despite the differences in the dataset lengths and the differences in the range and variability of θm, σθ, Tz, Hs, and Hmax, we found that the range and variability of Hmax/Hs are very similar for the four storm datasets.

The mean variance is shown in Figure 6 separately for all four dataset lengths.

However, for complex datasets, length estimates are quite accurate in ML (even for short datasets), whereas few branches are estimated accurately in a Bayesian framework.

These analyses eliminated any potential problems associated with model misestimation, isolating the remaining effects of dataset, branch length and depth, and branch length heterogeneity across the tree on branch length estimation.

A 6-taxa dataset of length 1000 bp and a 15-taxa dataset of length 3000 bp were both generated using the program SeqGen of Rambaut and Grassly (1997).

Below we present analysis of the insert size distributions for the following data: Brachybacterium faecium isolate dataset (read length 150 bp) and S taphylococcus aureus single-cell dataset (read length 101 bp).

This clearly suggested that, in the PASS2.3 dataset having length-rigid and length-deviant superfamilies, superfamilies have become more rigid in nature and i.e. similar-sized members in terms of domain length have increased.

Having extracted all fibers from the dataset, their length computation is straightforward.

Single channel microarray exploratory protocol analysis revealed up- and downregulation of C/D snoRNA dataset, including length outliers and without outliers (Supplementary data; S3E).