Bio-medical Ontologies Maintenance and Change Management

Protein Data Integration Problem 57
definitions of these concepts and relationships and also the possibility of defining
ontology rules and axioms, in order to define a mechanism to control the objects
that can be introduced in the ontology and to apply logical inference. Ontologies
in biomedicine have emerged because of the need for a common language for effective
communication across diverse sources of biological data and knowledge.
In this section, we provide a survey of ontologies used in the biomedical domain.
This section covers ontologies that focus on biological terminology.
2.1 The Gene Ontology
In 1998, efforts to develop the Gene Ontology (Lewis, 2004, Ashburner et al.,
2001) began, leading ontological development in the genetic area. The Gene
Ontology is a collaborative effort to create a controlled vocabulary of gene and
protein roles in cells, addressing the need for consistent descriptions of gene products
in different databases. The GO collaborators are developing three structured,
controlled vocabularies (ontologies) that describe gene products in terms of their
associated biological processes, cellular components and molecular functions in a
species-independent manner. The GO Consortium was initially a collaboration
among Mouse Genome Database (Blake et al., 1998), FlyBase (Ashburner, 1993),
and Saccharomyces Genome database (Schuler et al., 1996a) efforts. GO is now a
part of UMLS, and the GO Consortium is a member of the Open Biological Ontologies
consortium to be discussed later in this section. One of the important uses
of GO is the prediction of gene function based on patterns of annotation. For example,
if annotations for two attributes tend to occur together in the database, then
the gene holding one attribute is likely to hold for the other as well (King et al.,
2003). In this way, functional predictions can be made by applying prior knowledge
to infer the function of the new entity (either a gene or a protein).
GO consists of three distinct ontologies, each of which serves as an organizing
principle for describing gene products. The intention is that each gene product
should be annotated by classifying it three times, once within each ontology (Fraser
and Marcotte, 2004). The three GO ontologies are:
1. Molecular Function: This ontology describes the biochemical activity
of the gene product. For example, a gene product could be a transcription
factor or DNA helicase. This classifies the gene product’s kind of molecule.
2. Biological Process: This ontology describes the biological goal to which
a gene product contributes. For example, mitosis or purine metabolism.
An ordered assembly of molecular functions accomplishes such a process.
This describes what a molecule does or is involved in doing.
3. Cellular Component: This ontology describes the location in a cell in
which the biological activity of the gene product is performed. Examples
include the nucleus, telomere, or an origin recognition complex. This is
where the gene product is located.
GO is the result of an effort to enumerate and model concepts used to describe genes
and gene products. The central unit for description in GO is a concept. Concept