Sentence examples for importance of method from inspiring English sources

This chapter will therefore provide a reflection on the importance of method for retrieving cartographic data; on the vital role of participation in the construction of maps; and on the potential WebGIS offer to promote such participation.

In their analyses of the importance of method of detection, Wishart et al (2008) correctly adjust for stage of disease and for the Nottingham Prognostic Index (NPI) more generally.

Her article doesn't note that the court broadly affirmed the eligibility of patent protection for synthetic DNA and underscored the importance of methods patents for the development of genetic tests.

When considering the future of ecological immunology analyses, the potential importance of methods that can unite several multivariate datasets also comes to light.

The last finding emphasizes the importance of methods with specificity for single CpG sites to clearly define the extent of hypomethylation in SRS patients.

This supports the biological relevance of DTCs and the importance of methods to accurately assess the DTC-status when selecting patients for adjuvant treatment.

Further steps towards recognizing the importance of methods aimed at unraveling causality in observational data would contribute to conducting higher-quality fertility research.

In particular, the data highlight the importance of methods that provide an ongoing measure of the activity of key components of the signalling pathway and methods that manipulate the duration of activity of these components.

The mediating effect of cognitive processing speed on the ability of a primary school child to achieve his/her full potential of intellectual functioning emphasizes the importance of methods to detect "slow" children.

This finding illustrates the importance of methods such as NGS in epidemiology, which can detect novel gene acquisitions, which can have a high impact on the virulence of pathogens.

These results are encouraging and point to the importance of methods, such as Bayesian analysis, which fully take into account both the quality of data and prior experimental knowledge when comparing growth rates between microbial response curves.