BACKGROUND: The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data ...
BACKGROUND: There are many challenges associated with ontology building, as the process often touches on many different subject areas; it needs knowledge of the problem domain, an understanding of the ontology formalism, software in use and, sometime...
BACKGROUND: High-throughput technologies produce huge amounts of heterogeneous biological data at all cellular levels. Structuring these data together with biological knowledge is a critical issue in biology and requires integrative tools and methods...
BACKGROUND: An experimental protocol is a sequence of tasks and operations executed to perform experimental research in biological and biomedical areas, e.g. biology, genetics, immunology, neurosciences, virology. Protocols often include references t...
BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research...
Named-Entity Recognition is commonly used to identify biological entities such as proteins, genes, and chemical compounds found in scientific articles. The Human Phenotype Ontology (HPO) is an ontology that provides a standardized vocabulary for phen...
With increased usage of cardiovascular drugs (CVDs) for treating cardiovascular diseases, it is important to analyze CVD-associated adverse events (AEs). In this study, we systematically collected package insert-reported AEs associated with CVDs used...
BACKGROUND: The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this c...
Ontologies are important components of health information management systems. As such, the quality of their content is of paramount importance. It has been proven to be practical to develop quality assurance (QA) methodologies based on automated iden...
BACKGROUND: Named entity recognition is critical for biomedical text mining, where it is not unusual to find entities labeled by a wide range of different terms. Nowadays, ontologies are one of the crucial enabling technologies in bioinformatics, pro...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.