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speaking, EDAM is not a single, large ontology, but consists of five separate
(sub-) ontologies:
•
Topic:
fields of bioinformatics study, such as
Phylogenetics
,
Polymerase
chain reaction
,or
Metabolic pathways
.
•
Operation:
particular functions of tools or services (e.g., web service op-
erations), such as
Phylogenetic tree construction
,
PCR primer design
,or
Sequence analysis
.
•
Data:
semantic descriptions of data entities that are commonly used in
bioinformatics, such as
Phylogenetic tree
,
Sequence record
or
Sequence
alignment
.
•
Identifier:
labels for the (unique) identification of entities, such as
Phylo-
genetic tree ID
,
Sequence accession
,or
Pathway or network name
.
•
Format:
references to (syntactic) data format specifications, such as
Phylip tree format
,
FASTA sequence format
,or
KEGG PATHWAY en-
try format
.
Fig. 3.9
Conceptual model of the EDAM ontology (following [6])
While the terms within the five (sub-) ontologies are simply organized
in subclass hierarchies, additional relations have been defined that express
further connections between these concepts, as Figure 3.9 shows. The
For-
mat
and
Identifier
terms are linked to
Data
terms via
is format of
and
is identifier of
relations, respectively. The
has input
and
has output
relations
canbeusedtodenotethe
Data
types that are consumed or produced by
Op-
eration
s. Finally, the
Operation
and
Data
terms can be associated to
Topic
s
using the
in topic
relation.
At present, EDAM contains more than 3000 terms and definitions. It is
the most comprehensive ontology of bioinformatics terms that is presently
available, and is becoming used by an increasing number of applications. As
detailed in [249], the major applications of EDAM envisaged by its developers
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