Since the problem proposed in late 2000s, microRNA–disease association (MDA)
predictions have been implemented based on the data fusion paradigm. Integrating diverse …

We followed a systematic approach based on the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses to identify existing clinical natural language processing (NLP) …

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

Although our knowledge of human diseases has increased dramatically, the molecular
basis, phenotypic traits, and therapeutic targets of most diseases still remain unclear. An …

The amount of data collected and managed in (bio) medicine is ever-increasing. Thus, there
is a need to rapidly and efficiently collect, analyze, and characterize all this information …

The past decade has seen an explosion in the collection of genotype data in domains as
diverse as medicine, ecology, livestock and plant breeding. Along with this comes the …

Highlights•Next-generation sequencing technology accelerates rare disease research.•
Accumulated genomics information aids orphan drug development.•Novel drug …

Linked data and bio-ontologies enabling knowledge representation, standardization, and
dissemination are an integral part of developing biological and biomedical databases. That …

Multiparameter quantitative imaging incorporates anatomical, functional, and/or behavioral
biomarkers to characterize tissue, detect disease, identify phenotypes, define longitudinal …

Accurately extracting medical entities from social media is challenging because people use
informal language with different expressions for the same concept, and they also make …