Motivation: Ontologies are essential in biomedical research due to their ability to semantically integrate content from different scientific databases and resources. Their application improves capabilities for querying and mining biological knowledge. An increasing number of ontologies is being developed for this purpose, and considerable effort is invested into formally defining them in order to represent their semantics explicitly. However, current biomedical ontologies do not facilitate data integration and interoperability yet, since reasoning over these ontologies is very complex and cannot be performed efficiently or is even impossible. We propose the use of less expressive subsets of ontology representation languages to enable effici...
Abstract. There are few successful applications of automated reasoning over OWL-formalised bio-ontol...
Motivation: Ontologies have become indispensable in the Life Sciences for managing large amounts of ...
It is increasingly challenging to analyze the data produced in biomedicine, even more so when relyin...
Motivation: Ontologies are essential in biomedical research due to their ability to semantically int...
MOTIVATION: Ontologies are essential in biomedical research due to their ability to semantically int...
Motivation: Ontologies are essential in biomedical research due to their ability to semantically int...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
Abstract. Objectives: Biomedical ontologies exist to serve integration of clinical and experimental ...
Biomedical ontologies exist to serve integration of clinical and experimental data, and it is critic...
The use of ontologies in the biomedical field has been increasing exponentially for the two last dec...
With the substantial increase in stored scientific data of various types a major challenge of the po...
When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledg...
Today, it is impossible to contemplate successful biomedical research in the absence of canonical da...
Biomedical ontologies are increasingly being represented in Web Ontology Language (OWL) in order to ...
Abstract. There are few successful applications of automated reasoning over OWL-formalised bio-ontol...
Motivation: Ontologies have become indispensable in the Life Sciences for managing large amounts of ...
It is increasingly challenging to analyze the data produced in biomedicine, even more so when relyin...
Motivation: Ontologies are essential in biomedical research due to their ability to semantically int...
MOTIVATION: Ontologies are essential in biomedical research due to their ability to semantically int...
Motivation: Ontologies are essential in biomedical research due to their ability to semantically int...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
Researchers design ontologies as a means to accurately annotate and integrate experimental data acro...
Abstract. Objectives: Biomedical ontologies exist to serve integration of clinical and experimental ...
Biomedical ontologies exist to serve integration of clinical and experimental data, and it is critic...
The use of ontologies in the biomedical field has been increasing exponentially for the two last dec...
With the substantial increase in stored scientific data of various types a major challenge of the po...
When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledg...
Today, it is impossible to contemplate successful biomedical research in the absence of canonical da...
Biomedical ontologies are increasingly being represented in Web Ontology Language (OWL) in order to ...
Abstract. There are few successful applications of automated reasoning over OWL-formalised bio-ontol...
Motivation: Ontologies have become indispensable in the Life Sciences for managing large amounts of ...
It is increasingly challenging to analyze the data produced in biomedicine, even more so when relyin...