ALFA is an architecture developed for qualitative representation of biological information. The goals of ALFA are to capture and represent, in a structured manner, information from free-form text, experimental data, and diagrammatic models by defining a common hierarchical hyper-graph data structure to represent the underlying information.
While the emphasis of ALFA is to provide a means for representing information present in various sources of biological data in an abstract yet structured manner, the hierarchical hyper-graph data structure also provides a visual and computational framework to query, modify, and visualize the represented information. Moreover, this model lends itself to extensions for developing quantitative models of biological processes.
The ALFA architecture consists of an object model and an API layer to access the underlying objects. The architecture provides mechanisms to annotate objects, add a list of properties to the objects, and attach proprietary and external ontologies as classifiable properties of the objects.
The architecture further incorporates a set of native (scientific text, experimental data, and diagrammatic biological models) data viewers, which aid in extraction of information from each of these native data sources into the ALFA object model and conversely to incorporate information stored as ALFA objects into the respective viewers.
Aditya Vailaya , Peter Bluvas , Robert Kincaid , Allan Kuchinsky , Michael Creech , and Annette Adler, "An architecture for biological information extraction and representation," Bioinformatics, 2005, 21(4):430-438.
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