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Christophe Dessimoz and Nives kunca (eds.) The Gene Ontology Handbook Methods in Molecular Biology 1446 10.1007/978-1-4939-3743-1_1
1. Primer on Ontologies
Janna Hastings 1
(1)
Cheminformatics and Metabolism, European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
Janna Hastings
Email:
Abstract
As molecular biology has increasingly become a data-intensive discipline, ontologies have emerged as an essential computational tool to assist in the organisation, description and analysis of data. Ontologies describe and classify the entities of interest in a scientific domain in a computationally accessible fashion such that algorithms and tools can be developed around them. The technology that underlies ontologies has its roots in logic-based artificial intelligence, allowing for sophisticated automated inference and error detection. This chapter presents a general introduction to modern computational ontologies as they are used in biology.
Examining aspects of the world to determine the nature of the entities that exist and their causal networks is at the heart of many scientific endeavours, including the modern biological sciences. Advances in technology have made it possible to perform large-scale high-throughput experiments, yielding results for thousands of genes or gene products in single experiments. The data from these experiments are growing in public repositories [], which is the subject of this volume.
Ontologies are computational structures that describe the entities and relationships of a domain of interest in a structured computable format, which allows for their use in multiple applications [].
Elements of Ontologies
Ontologies consist of several distinct elements, including classes, metadata, relationships, formats and axioms.
2.1 Classes
The class is the basic unit within an ontology, representing a type of thing in a domain of interest, for example carboxylic acid , heart , melanoma and apoptosis . Typically, classes are associated with a unique identifier within the ontologys namespace, for example (respectively) CHEBI:33575, FMA:7088, DOID:1909 and GO:0006915. Such identifiers are semantics free (they do not contain a reference to the class name or definition) in order to promote stability even as scientific knowledge and the accompanying ontology representation evolve. Ontology providers commit to maintaining identifiers for the long term, so that if they are used in annotations or other application contexts the user can rely on their resolution. In some cases as the ontology evolves, multiple entries may become merged into one, but in these cases alternate identifiers are still maintained as secondary identifiers. When a class is deemed to no longer be needed within the ontology it may be marked as obsolete, which then indicates that the ID should not be used in further annotations, although it is preserved for historical reasons. Obsolete classes may contain metadata pointing to one or more alternative classes that should be used instead.
2.2 Metadata
Classes are usually associated with annotated textual informationmetadata. The metadata associated with classes may include any associated secondary (alternate) identifiers and flags to indicate whether the class has been marked as obsolete. It may also include one or more synonyms; for example the synonyms of apoptotic process (a class in the GO) include cell suicide , programmed cell death and apoptosis . It further may include cross references to that class in alternative databases and web resources. For example, many Chemical Entities of Biological Interest (ChEBI) [], which represents those chemicals in the context of the biological pathways they participate in. Textual comments and examples of intended usage may be annotated. It is very important that each class include a clear definition, which provides enough information to pinpoint the meaning of the class and suggest its appropriate usesufficiently distinguishing different classes in an ontology so that a user can determine which is the best to use for annotation. The definition of apoptosis offered by the Gene Ontology is as follows:
A programmed cell death process which begins when a cell receives an internal (e.g. DNA damage) or external signal (e.g. an extracellular death ligand), and proceeds through a series of biochemical events (signaling pathway phase) which trigger an execution phase. The execution phase is the last step of an apoptotic process, and is typically characterized by rounding-up of the cell, retraction of pseudopodes, reduction of cellular volume (pyknosis), chromatin condensation, nuclear fragmentation (karyorrhexis), plasma membrane blebbing and fragmentation of the cell into apoptotic bodies. When the execution phase is completed, the cell has died.
2.3 Relations
Classes are arranged in a hierarchy from the general (high in the hierarchy) to the specific (low in the hierarchy). For example, in ChEBI carboxylic acid is classified as a carbon oxoacid , which in turn is classified as an oxoacid , which in turn is classified as a hydroxide , and so on up to the root chemical entity , which is the most general term in the structure-based classification branch of the ontology.
Despite the hierarchical organisation, most ontologies are not simple trees. Rather, they are structured as directed acyclic graphs . This is because it is possible for classes to have multiple parents in the classification hierarchy, and furthermore ontologies include additional types of relationships between entities other than hierarchical classification (which itself is represented by is_a relations). All relations are directed and care must be taken by the ontology editors to ensure that the overall structure of the ontology does not contain cycles, as illustrated in Fig..
Fig. 1
( a ) A simple hierarchical tree, ( b ) a directed, acyclic graph, ( c ) a graph that contains a cycle, indicated in red
A common relationship type used in multiple ontologies is part_of or has_part , representing composition or constitution. For example, in the Foundational Model of Anatomy (FMA) [.
Table 1
A selection of relationship types commonly used in bio-ontologies
Relationship type
Informal meaning
Examples
part_of
The standard relation of parthood.
A brain is part_of a body.
derives_from
Derivation holds between distinct entities when one succeeds the other across a temporal divide in such a way that a biologically significant portion of the matter of the earlier entity is inherited by the latter.
A zygote derives_from a sperm and an ovum.
has_participant
A relation that links processes to the entities that participate in them.
An apoptotic process has_participant a cell.
has_function
A relation that links material entities to their functions, e.g. the biological functions of macromolecules.
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