Sentence examples for data integration in the from inspiring English sources

In this paper, initial elements are described for data integration in the prototype and development phases for parts and tools.

In this work we present the case of EPOS, a plan for data integration in the field of Earth Sciences.

Target information in the database was pre-processed as a previous step before data integration in the predictor.

This book constitutes the refereed proceedings of the 8th International Conference on Data Integration in the Life Sciences, DILS 2012, held in College Park, MD, USA, on June 28-29 , 2012

We analyse here different normalisation approaches for microarray data integration, in the context of reverse engineering of GRN quantitative models.

These have been compared for four criteria, relevant for data integration in the context of GRN quantitative modelling: variability between replicates, wavelet coefficient analysis, simple gene-gene correlations and GRN differential equation model translation between datasets.

However, in addition, as participants in the qualitative sample would also have responses to the quantitative data collected for the trial, this will allow for the possibility of taking a mixed-methods approach to data integration, in which the two forms of data can be used in a complementary way.

In 2007, the challenges identified for data integration in genomic medicine were the lack of clinical data sources; the privacy issues linked to clinical data; the inherent complexity of medical records; and finally, the lack of data representation standards in the clinical domain [ 6].

While we have not used these approaches to improve our framework yet, we plan to combine our framework with different methods for data integration in systems biology in the future.

To date, much of the discussion of data integration in ecology has focused on the importance and possible use of 'dark' data in the 'long tail' of science, i.e., the large number of small datasets that make up the majority of science, that are not well indexed or stored and typically are not publicly accessible [ 16].

The most effective uses for cloud data integration in healthcare will be the management of patient data for use by remote clinicians.