Ontologies are critical to data/metadata and knowledge standardization, sharing, and
analysis. With hundreds of biological and biomedical ontologies developed, it has become …

Knowledge-based biomedical data science involves the design and implementation of
computer systems that act as if they knew about biomedicine. Such systems depend on …

The correlation of phenotypic outcomes with genetic variation and environmental factors is a
core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient …

Ontologies of research areas are important tools for characterising, exploring, and analysing
the research landscape. Some fields of research are comprehensively described by large …

Motivation Biological data and knowledge bases increasingly rely on Semantic Web
technologies and the use of knowledge graphs for data integration, retrieval and federated …

Translational research requires data at multiple scales of biological organization.
Advancements in sequencing and multi-omics technologies have increased the availability …

The “RNA world” represents a novel frontier for the study of fundamental biological
processes and human diseases and is paving the way for the development of new drugs …

Ontologies of research areas are important tools for characterizing, exploring, and analyzing
the research landscape. Some fields of research are comprehensively described by large …

Background Cancer is the second leading cause of death in the United States, exceeded
only by heart disease. Extant cancer survival analyses have primarily focused on individual …

Background Biomedical translational science is increasingly using computational reasoning
on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome …