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. 2009 Jul;10(4):345-53.
doi: 10.1093/bib/bbp029.

Approaches to neuroscience data integration

Affiliations

Approaches to neuroscience data integration

Kei-Hoi Cheung et al. Brief Bioinform. 2009 Jul.

Abstract

As the number of neuroscience databases increases, the need for neuroscience data integration grows. This paper reviews and compares several approaches, including the Neuroscience Database Gateway (NDG), Neuroscience Information Framework (NIF) and Entrez Neuron, which enable neuroscience database annotation and integration. These approaches cover a range of activities spanning from registry, discovery and integration of a wide variety of neuroscience data sources. They also provide different user interfaces for browsing, querying and displaying query results. In Entrez Neuron, for example, four different facets or tree views (neuron, neuronal property, gene and drug) are used to hierarchically organize concepts that can be used for querying a collection of ontologies. The facets are also used to define the structure of the query results.

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Figures

Figure 1:
Figure 1:
Screen shots illustrating the steps involved in performing a keyword search through NDG: (A) NDG home page, (B) form-based search interface that includes selection of controlled keywords, (C) list of databases whose annotation contains the selected keywords and (D) annotation of one of the matching databases.
Figure 2:
Figure 2:
Components of the NIF Web Query Interface.
Figure 3:
Figure 3:
The CBQI Web interface: (A) search page, (B) NIF Database Mediator form with the option of selection query output fields from each database, (C) query results from one of the database tables.
Figure 4:
Figure 4:
Relationships between different entity types.
Figure 5:
Figure 5:
Combined ontological components of NeuronDB, ModelDB and PDSP.
Figure 6:
Figure 6:
Entrez Neuron query interface.

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