Highlights•Ontology map** enables data analytics through interoperability and
integration.•Map** between ontologies expands coverage across large domains such as …

Recent advances in genomics technologies have greatly accelerated the progress in both
fundamental plant science and applied breeding research. Concurrently, high‐throughput …

Motivation Ontologies are widely used in biology for data annotation, integration and
analysis. In addition to formally structured axioms, ontologies contain meta-data in the form …

Motivation Infectious diseases caused by novel viruses have become a major public health
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …

Motivation Over the past years, many computational methods have been developed to
incorporate information about phenotypes for disease–gene prioritization task. These …

Background Prioritization of variants in personal genomic data is a major challenge.
Recently, computational methods that rely on comparing phenotype similarity have shown to …

Background While representation learning techniques have shown great promise in
application to a number of different NLP tasks, they have had little impact on the problem of …

Motivation In the past years, several methods have been developed to incorporate
information about phenotypes into computational disease gene prioritization methods …

Background A major obstacle faced by families with rare diseases is obtaining a genetic
diagnosis. The average" diagnostic odyssey" lasts over five years and causal variants are …

Motivation From image stacks to computational models, processing digital representations of
neuronal morphologies is essential to neuroscientific research. Workflows involve various …