Sentence examples for mislead interpretation from inspiring English sources

Since the vast majority of virus particles are likely to be adsorbed without productive infection of cells, reporter gene imaging gives a skewed report of virus or vector distribution that may mislead interpretation of the pharmacology of these agents.

In this case, if an unsuitable aligner is selected with existing repetitive regions and polymorphisms, the results may then convey error messages and mislead interpretation of biological outcome.

The effects of global systemic physiology were also investigated, particularly low frequency blood pressure oscillations which give rise to broad regions of high correlation and mislead interpretation of the results.

Because increased cell number due to increased proliferation can mislead interpretation of wound-healing data; we performed these assays in the presence of mitomycin C, an inhibitor of cell division.

The funding source was mainly non-profit (n = 54, 42 %), but for 41 articles (32 %) the funding source was not reported or was unclear.> The classification of spin we developed was divided into 3 categories: misleading reporting, misleading interpretation and inadequate extrapolation of the results.

He we provide an example of how alternative prior choices can seriously influence results and mislead interpretations.

Stress values <0.2 are recommended (Clarke 1993) as values above this threshold may mislead interpretations.

Since it is known that unbalanced principal components analyses could mislead interpretations of population structures [ 30], four randomized evenly sampled analyses were run (Additional file 2: Figure S2).

But then – and this, perhaps, is the actual reason why the information is being withheld – the prime minister's claim that "40% of recent European migrants are supported by the benefit system" is based on a deliberately misleading interpretation of the data, and the government knew, or should have known, that when he said it.

The higher the PEEP, the more the probability of misleading interpretation of STE data.

Therefore, without rationale for classification, both arbitrary and distribution-based classifications are liable to cut-point bias and prone to misleading interpretation [ 26, 62].