Sentence examples for higher level gains from inspiring English sources

The percentage of the genome encompassed in higher level gains was not significant (p = 0.88), suggesting that it is not the proportion of DNA amplified but the number of amplification events that is most important.

These measures included: the number of copy number changes i.e. gains, losses, higher level gains (>0.6 log2 amplitude) and total number of segments; the percentage of the genome targeted by copy number change (gain, loss and high level gain); and a "Hicks index" as described [31] for gains, losses and both.

The relative populations respond to the temperature: as the temperature increases, the higher level gains more population, while that of the lower level decreases.

The optimization process modifies the amplitude of the original filters over the frequency band of interest without adding high level gains.

CDKN2A/B deletion was also observed in Res259 astrocytoma cells, which also contained the well-described 4q12 amplicon, resulting in high level gains of the oncogenes PDGFRA and KIT, and low-level gain of a region including KDR/VEGFR2.

Log2 copy number threshold for gains were set at +0.15 (~2.2 copies) while high level gains were set at +0.5 (~2.8 copies).

When looking more into detail, the AUC remains high for chromosome 17 for both techniques (AUC is 0.941), demonstrating that high level gains are easily detected.

Single, focal high level gains were located at 6q27 and 13q33q34 in one child's tumour, and at 17q21qter and 19q13 in the remaining two tumours.

Most of the chromosomes in this profile showed multiple segmental alterations, including single copy as well as high level gains and losses.

However, while G4 (nbBP-High/GGI-median) and G5 (nbBP-Low/GGI-High) respectively belonged to the high and low risk class, their average numbers of gains, high level gains and losses were similar (Additional file 9B,C).

An R script using Circular Binary Segmentation (CBS) algorithm implemented in DNAcopy (Bioconductor for R) and normalized/replicates filtered data as input, were used to determine genomic metrics such as gains, losses, high level gains, homozygous copy losses.