Ontologies, Linnaeus, Genia Ontology, Gene Onotology, Galen, FMA

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The Foundational Model of Anatomy Ontology (FMA) is an evolving computer-based knowledge source for biomedical informatics; it is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Specifically, the FMA is a domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy.


The GALEN CORE Model for representation of the Common Reference Model for Procedures contains the building blocks for defining procedures - the anatomy, surgical deeds, diseases, and their modifiers used in the definitions of surgical procedures. This document describes the structure the CORE model and gives a detailed account of its high level schemata followed by a detailed example of the use of the ontology for a portion of the model of the cardiovascular system and diseases.


The Gene Ontology project is a major bioinformatics initiative with the aim of standardizing the representation of gene and gene product attributes across species and databases. The project provides a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data from GO Consortium members, as well as tools to access and process this data.

Genia Ontology

The GENIA ontology is intended to be a formal model of cell signaling reactions in human. It is to be used as a basis of thesauri and semantic dictionaries for natural language processing applications, e.g.,

Information retrieval (IR) & filtering (IF)
Information extraction (IE)
Document and term classification & categorization
Summarization, etc.

Another use of the GENIA ontology is to provide the basis for integrated view of multiple databases including CSNDB developed at National Institiute of Health Science.

Web ontology segmentation: analysis, classification and use

Seidenberg, J., and A. Rector, "Web ontology segmentation: analysis, classification and use", Proceedings of the 15th international conference on World Wide Web: ACM, pp. 13–22, 2006.

Selecting an ontology for biomedical text mining

Tan, H., and P. Lambrix, "Selecting an ontology for biomedical text mining", Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Association for Computational Linguistics} maptags={Ontology, pp. 55–62, 2009.
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