For that purpose we study cardinality constraints and functional dependencies as a declarative mechanism to control the occurrences and interrelationships of uncertain data.
The correspondence of classification was near chance level for the interrelationship of all three data set clusters.
However, the interrelationship of many these data sets has not been explored.
To expand upon the interrelationship of these biomarkers, data from SLE patients with two consecutive visits were segregated for analyses by increasing or decreasing IFN score by at least 50% from the first to the second visit.
Constraints, units of measurement and interrelationships for data values are specified in order to homogenise the data, eliminate ambiguities and allow for automated validation.
A hierarchical clustering analysis is a commonly used exploratory technique to handle a large set of data whose interrelationships are elusive and not fully understood.
There are only limited amount of data on the interrelationships between different inflammatory cell types (Nagtegaal et al, 2001) and inflammatory cell reaction grading methods (Roxburgh et al, 2009b; Richards et al, 2012a) in CRC, which would be essential in evaluating their relative significance.
Therefore, IDEF1X is a semantic data-modeling technique that defines the meaning of data within the context of its interrelationship with other data.
Due to the rapid accumulation of data about biological processes and molecular interrelationships, there is an increasing demand for approaches to analyse the underlying regulatory networks.
The combination of microarray data, proteomics data, protein-protein interaction data, and other -omics data, in another word, studying the interrelationship of all the components that comprise a system is a trend in identifying genes involved in the aging process.
