The volume of publicly available genomic scale data is increasing. Genomic datasets in
public repositories are annotated with free-text fields describing the pathological state of the …

Finding concepts in large clinical ontologies can be challenging when queries use different
vocabularies. A search algorithm that overcomes this problem is useful in applications such …

Natural language understanding is a key task in a wide range of applications targeting data
interoperability or analytics. For the analysis of domain-specific data, specialised knowledge …

Background Ontology term labels can be ambiguous and have multiple senses. While this is
no problem for human annotators, it is a challenge to automated methods, which identify …

Background Standard ontologies are critical for interoperability and multisite analyses of
health data. Nevertheless, mapping concepts to ontologies is often done with generic tools …

Background Ontologies and controlled terminologies have become increasingly important in
biomedical research. Researchers use ontologies to annotate their data with ontology terms …

A scientific ontology is a formal representation of knowledge within a domain, typically
including central concepts, their properties, and relations. With the rise of computers and …

Abstract The National Center for Biomedical Ontology (NCBO) is developing a system for
automated, ontology-based access to online biomedical resources. The system's indexing …

Motivation: Ontologies are an everyday tool in biomedicine to capture and represent
knowledge. However, many ontologies lack a high degree of coverage in their domain and …

With the vast amount of biomedical data we face the necessity to improve information
retrieval processes in biomedical domain. The use of biomedical ontologies facilitated the …