Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation
phase in many fields, including medicine. The combination of improved availability of large …

Within clinical, biomedical, and translational science, an increasing number of projects are
adopting graphs for knowledge representation. Graph‐based data models elucidate the …

One of the most pressing challenges in genomic medicine is to understand the role played
by genetic variation in health and disease. Thanks to the exploration of genomic variants at …

The information about the genetic basis of human diseases lies at the heart of precision
medicine and drug discovery. However, to realize its full potential to support these goals …

Abstract PubChem (https://pubchem. ncbi. nlm. nih. gov) is a popular chemical information
resource that serves a wide range of use cases. In the past two years, a number of changes …

DisGeNET is a comprehensive discovery platform designed to address a variety of
questions concerning the genetic underpinning of human diseases. DisGeNET contains …

Abstract PubChem (https://pubchem. ncbi. nlm. nih. gov) is a public chemical database at the
US National Institutes of Health. Visited by millions of users every month, it plays a role as a …

Explainability has been a goal for Artificial Intelligence (AI) systems since their conception,
with the need for explainability growing as more complex AI models are increasingly used in …

Over the past eight years, we have been involved in the development of a set of
complementary and orthogonal ontologies that can be used for the description of the main …

Research in artificial intelligence (AI) is addressing a growing number of tasks through a
rapidly growing number of models and methodologies. This makes it difficult to keep track of …