Sentence examples for multiple datasets as from inspiring English sources

In order to achieve this objective, we set out to develop a computational framework that has the potential to combine different inference methodologies, multiple datasets, as well as any pre-existing biological knowledge.

Missing and multiple datasets as a consequence of possible problems during data transfer or storage are identified, and appropriate metadata together with aggregated statistical data in the time domain are generated.

The evaluation of multiple datasets as employed in this study has been shown to yield more reliable and valid results, because they are based on large sample numbers and the individual bias caused by each study is weakened [30].

The combination of multiple datasets, as illustrated here, can further improve the functional inferences that typically are generated via a single type of datasets.

These issues are particularly important for studies covering several years and multiple datasets, as people can report their name or date of birth differently on different occasions [ 13].

While these committees provide access oversight for specific projects, they do not provide a simple solution for a researcher who may want to access multiple datasets, as individual applications must still be made to a number of different committees.

The same two genes also showed high expression in root tissues in multiple microarray transcriptomics datasets as well.

We will also review the methodology of specific approaches to science analysis based on joint analysis of DTM and orthoimage information, or benefitting from high accuracy of co-registration between multiple datasets, such as studies using multi-temporal or multi-angular observations, from the fields of geomorphology, structural geology, compositional mapping, and atmospheric science.

Moreover, we discuss data management, distribution, and integration tools that are capable of performing comparative metagenomic analyses of multiple datasets using well-established databases, as well as commonly used annotation standards.

In such a situation, which is more typical than the earlier illustration example, one can use exactly the same method, applied to multiple datasets with different dynamic profiles, as long as one can validly assume that the functional forms are not affected by differences among the datasets.

Multiple datasets were created, as each missing value was replaced with a set of random plausible values conditional on known covariates and known distributional information.