Add to ORKGIn this paper, we define several quantitative measures that are useful when using ontologies to describe biological data. More precisely, we define the precision of a term inside an ontology, and use this concept to quantify the similarity between terms inside an ontology, or, by extension, between biological entities annotated to terms of the ontology. This similarity measure is used to build a hierarchical tree between biological objects annotated to a particular ontology. The graphical representation of this tree allows to easily interpret the relationships between objects of a set based on this ontology, and to identify relevant annotations. We have implemented this principle in ClusterInspector, a tool that allows to browse the resulti...
Abstract Background Semantic similarity measures are ...
Molecular biologists and medical geneticists have to analyse large lists of genes and genomic varian...
The co-occurrence of terms in a text corpus may indicate the presence of a relation between the refe...
In this paper, we define several quantitative measures that are useful when using ontologies to desc...
Background: Various measures of semantic similarity of terms in bio-ontologies such as the Gene Onto...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
BackgroundBiomedical ontologies have been growing quickly and proven to be useful in many biomedical...
Recommender systems and search engines are examples of systems that have used techniques such as Pea...
A-09-52International audienceWe present a web-based service, SimCT, which allows to graphically disp...
Methods for comparing associative relationships across on-tologies often rely solely on lexical simi...
Background Gene ontology (GO) is a well-structured knowledge of biological terms that desc...
land Motivation: Representing a domain of knowledge has been tradi-tionally accomplished in biology ...
The Ontological Discovery Environment (ODE) provides an efficient structure for storage of gene and ...
leipzig.de Linked Open Data has made available a diversity of scien-tific collections where scientis...
Visualization can help domain experts make sense of their data, but determining appropriate visual r...
Abstract Background Semantic similarity measures are ...
Molecular biologists and medical geneticists have to analyse large lists of genes and genomic varian...
The co-occurrence of terms in a text corpus may indicate the presence of a relation between the refe...
In this paper, we define several quantitative measures that are useful when using ontologies to desc...
Background: Various measures of semantic similarity of terms in bio-ontologies such as the Gene Onto...
Ontologies and hierarchical clustering are both important tools in biology and medicine to study hig...
BackgroundBiomedical ontologies have been growing quickly and proven to be useful in many biomedical...
Recommender systems and search engines are examples of systems that have used techniques such as Pea...
A-09-52International audienceWe present a web-based service, SimCT, which allows to graphically disp...
Methods for comparing associative relationships across on-tologies often rely solely on lexical simi...
Background Gene ontology (GO) is a well-structured knowledge of biological terms that desc...
land Motivation: Representing a domain of knowledge has been tradi-tionally accomplished in biology ...
The Ontological Discovery Environment (ODE) provides an efficient structure for storage of gene and ...
leipzig.de Linked Open Data has made available a diversity of scien-tific collections where scientis...
Visualization can help domain experts make sense of their data, but determining appropriate visual r...
Abstract Background Semantic similarity measures are ...
Molecular biologists and medical geneticists have to analyse large lists of genes and genomic varian...
The co-occurrence of terms in a text corpus may indicate the presence of a relation between the refe...