Sentence examples for dataset removing from inspiring English sources

To predict catalytic residues for the α-chymotrypsin structure 1acb, we estimated D iscern parameters using a subset of the CATRES-FAM dataset, removing all enzymes in the same SCOP superfamily as 1acb.

Our pre-processing of the data further included merging the datasets, specifically combining data for the 10 Hgs that appeared in both datasets; removing Hgs which had less than two samples in the combined dataset; removing samples which had less than 11 Y-STRs observed.

Also, we took the Lukk08 dataset, removed randomly chosen 10percentt of condition columns, and performed full AHC.

We determined the time for the taxonomic assignment of simArt49e for all methods when performing a cross-validation with families present in the test dataset removed from the reference data (Fig. 3).

A background with the same GC composition distribution (mean and variance) as the foreground dataset removes bias arising from GC composition differences and controls against TFBSs being unduly assigned high or low over-representation scores.

We started with the "Total Intron-Exon Time-Course Dataset", removed the intron-exon combinations with zero reads in all exonic or intronic samples and then selected the top half exonic expressors based on average density of exonic signal to generate the "Top expressed Intron-Exon Time-Course Dataset".

In the frizzled-CRD datasets, removing up to 50% of the fastest evolving sites of the "reduced" dataset did not significantly affect the topology or the support values, with moderate support for sFRP polyphyly (fig. 5 G, BP ML: 62%; PP: 92%) and no support for sFRP monophyly still retained (BP ML: 0%–1%).

Two additional datasets were sampled from this basic dataset, by removing apparent recombinant regions or haplotypes ('IM Reduced Dataset 1', and 'IM Reduced Dataset 2' – see methods and Table 1).

We tested the algorithm with 50 colonoscopy video frames before (Dataset 1) and after (Dataset 2) removing specular highlights.

Accuracy mk) for a target sequence is computed on the benchmark dataset after removing the target from the dataset.

w m for a target sequence was computed on the benchmark dataset after removing the target from the dataset.