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Open Access
Genome Biology 2005 6 :R46

© Smith et al. ; licensee BioMed Central Ltd.2005

Received: 28October2004

Accepted: 31March2005

Published: 28April2005


To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

Gene Ontology Spatial Region Unify Medical Language System Process Instance Relation Ontology

The background to this paper is the now widespread recognition that many existing biological and medical ontologies (or 'controlled vocabularies') can be improved by adopting tools and methods that bring a greater degree of logical and ontological rigor. We describe one endeavor along these lines, which is part of the current reform efforts of the Open Biomedical Ontologies (OBO) consortium [ 2018 Discount Cheapest Online Sleepy Jones Woman Gingham Seersucker Cotton Pajama Top Black Size L Sleepy Jones Free Shipping Newest Fast Delivery Sale Online q6S2JKH3P
, 2 ] and which has implications for ontology construction in the life sciences generally.

The OBO ontology library [ Free Shipping Choice Skinny Washed Knee Rip Jeans Heave stonewash DStruct Popular Cheap Price HI5SUqi
] is a repository of controlled vocabularies developed for shared use across different biological and medical domains. Thus the Gene Ontology (GO) [ 3 , 4 ] consists of three controlled vocabularies (for cellular components, molecular functions, and biological processes) designed to be used in annotations of genes or gene products. Some ontologies in the library - for example the Cell and Sequence Ontologies, as well as the GO itself - contain terms which can be used in annotations applying to all organisms. Others, especially OBO's range of anatomy ontologies, contain terms applying to specific taxonomic groups such as fly, fungus, yeast, or zebrafish.

Controlled vocabularies can be conceived as graph-theoretical structures consisting on the one hand of (which form the nodes of each corresponding graph) linked together by means of edges called . The ontologies in the OBO library are organized in this way by means of different types of relations. OBO's Mouse Anatomy ontology, for example, uses just one type of edge, labeled . The GO currently uses two, labeled and . The Anatomy ontology includes also a link. Other OBO ontologies include further links, for example (in the Sequence Ontology) and . The National Cancer Institute (NCI) Thesaurus adds many additional links, including for anatomical structures and different relations for structures and for processes.

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Page Contents

Overview of model relations

Individual models are easy to understand and work with. But in reality, models are often connected or related. When you build a real-world application with multiple models, you’ll typically need to define relations between models. For example:

With connected models, LoopBack exposes as a set of APIs to interact with each of the model instances and query and filter the information based on the client’s needs.

You can define the following relations between models:

You can define models relations in JSON in the Classic Cheap Online Womens The Icon Ankle Jeans Joes Free Shipping Shopping Online Low Price LHKumM
file or in JavaScript code. The end result is the same.

When you define a relation for a model, LoopBack adds a set of methods to the model, as detailed in the article on each type of relation.

It’s important to understand that all models inherit from the Mikael Aghal Woman Cutout Brocade Midi Dress Fuchsia Size 2 Mikael Aghal Cheap Price Fake Cheap Sale New Arrival PluMQq
and they can have relations between them regardless of the specific type of model or the backing data source. Models backed by different data sources can have relations between them.

The easiest way to create a new relation between existing models is to use the slc loopback:relation , or the apic loopback:relation ,relation generator.

The tool will prompt you to enter the type of relation (belongsTo, hasMany, and so on) and the affected models.

The name of the relation must be different than a property it references.

There are three options for most relation types:

REVIEW COMMENT from Rand "Most"? Which ones DON'T they apply to?

The scope property can be an object or function, and applies to all filtering/conditions on the related scope.

The object or returned object (in case of the function call) can have all the usual filter options: where , order , include , limit , offset , …

These options are merged into the default filter, which means that the where part will be AND -ed. The other options usually override the defaults (standard mergeQuery behavior).

When scope is a function, it will receive the current instance, as well as the default filter object.

For example:

You can specify the properties option in two ways:

For example, the following relationtransfers the type to the product, and de-normalizes the category name into categoryName on creation:

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