Databases are structured to facilitate the storage, retrieval, modification, and deletion of data in conjunction with various data-processing operations.
The database is structured on the Bridgman table principle of the partial derivatives of state functions.
The database is structured around clusters of protein sequences, which allows for the evaluation of redundancy, protein prediction discrepancies, and possible splice variants.
The database is structured according to the steps in a metabolomics experiment and therefore consists of four principal components: "Experimental design" "Analytical Metadata", "Spectra data" and "Compounds".
The system's internal database is structured as a meta-graph database that contains the features attributable to a given bio-entity, such as gene, protein, pathway, operon, experiment, COG, and other.
However, the database is structured to easily integrate references to published works or HTML links to raw data files generated for each originating specimen (and patient) used from the Resource.
The database is structured in three hierarchical levels: level 1 includes all the separate questions, without grouping or aggregation, level 2 includes the questions recorded by area and by unit - each area can refer to many units - and level 3 includes the questions recorded by department and whole health care organisation.
This database was structured using the 'normalisation' method, which is a process of removing duplication in the data, therefore minimising redundancy and the chance of entering inconsistent data (Connolly and Begg, 2005; Powell 2006).
To analyze the druggability of herbs on molecular level, the database was structured to incorporate several important ADME-related properties such as human oral bioavailability (OB) [23], half-life (HL) Yao Y, Wei Z, Yonghua W: A novel Systems Pharmacology model for herbal medicine injection: a case using Reduning Injection.
Three ontologies in the GO database are structured as directed acyclic graphs.
