Sentence examples for variation were identified from inspiring English sources

Two QTLs (qB11Jtbn2-1, qB12Ctbn2-1, qB12Ctbn5-1q11JBthat-1, qB12Ctbn5-1, qBJtbn5-1) thaccountedted for more than 10% of the phenotypic variation were identified.

In the first experiment, three main sources of variation were identified: (1) different levels of dissection, (2) omitted components, and (3) different values for the factors used to compute PCI.

No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance.

Subsequently, Moran's Eigenvector Maps (MEM) variables, which may account for spatial variation and un-accounted environmental factors, were applied to an allele distribution model, and 19 loci significantly associated to environmental variation were identified.

Dominant factors of variation were identified as the spatial distribution of total vegetation growth, seasonality of growth, magnitude of seasonal variability in growth, and regularity of variation in growth.

Because most of the genes functionally characterized by using natural variation were identified as genes responsible for QTLs, it was not unexpected to find that most of their genomic locations were included in QTL regions associated with those same traits (Figure 2).

However, no cause for this inter-replicate variation was identified.

A family of surface proteins, rifins, that may play a role in antigenic variation was identified.

A new missense nucleotide variation was identified in OsYSL7, the metal-nicotinamide transporter protein (Table 4).

However, an interesting feature of average signal strength variation was identified from the data analysis.

Overall, significant variation was identified at all scales examined, excluding the largest scale (area).