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Remote sensing provides the only feasible option for mapping LAI continuously over landscapes, but existing methodologies have significant limitations.
Such methodologies have significant hurdles to overcome: first, multiple studies are likely to use different platforms, different sample dissection, handling and preparation, and, especially, different definition of the non-diseased counterpart, resulting in different physical samples being hybridized against different platforms [1], [2], [3].
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Therefore, the sample preparation methodologies, which have significant effect on these newly identified human and murine immunoreactive proteins of B.p but not on these known pertussis antigens, should be also one of the main factors resulting in the apparent differences between the two immunoproteoms of B.p.
The evolution of our proposed methodology could have significant societal impact opening the way to customized mobile phone applications, which may detect the users' condition and suggest specific actions to them in order to prevent disease spreading and minimize the risk of contagion.
The potential to obtain more accurate forecasts using data fusion methodologies could therefore have significant implications for the design and construction of automated flood forecasting and flood warning systems.
Although this methodology appears to have significant utility for animal research in chronic myocardial infarctions, it is recognized that several study limitations exist.
This article describes how the twin processes of modelling and simulation are being used to improve the efficiency of the clinical drug-development process, and consequently how these methodologies have delivered significant benefits in the drive to save time, money (and additionally assisted in ensuring an 'optimal quality' drug label) in the development of novel therapeutic agents.
MS-based methodologies have provided significant advances in accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools.
In fact, this methodology determines which factors have significant effects on a response as well as how the effect of one factor varies according to the level of the other factors (Meski et al. 2011; Balbasi 2013; Azza et al. 2015).
Aboyans and colleagues recently highlighted that a lack of standardised ABI methodology is likely to have significant clinical, public health and economic repercussions [ 10].
Current methodologies used for typing Leptospira have significant drawbacks.
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CEO of Professional Science Editing for Scientists @ prosciediting.com