In biology and biomedicine, relating phenotypic outcomes with genetic variation and
environmental factors remains a challenge: patient phenotypes may not match known diseases, …

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing
response to the COVID-19 pandemic by the biomedical research community. While rich …

Human Phenotype Ontology (HPO)-based analysis has become standard for genomic
diagnostics of rare diseases. Current algorithms use a variety of semantic and statistical …

Electronic Health Record (EHR) systems typically define laboratory test results using the
Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast …

Graph representation learning methods opened new avenues for addressing complex, real-world
problems represented by graphs. However, many graphs used in these applications …

Autologous anti-CD19 chimeric antigen receptor T cell (CAR T) therapy is highly effective in
relapsed/refractory large B cell lymphoma (rrLBCL) but is associated with toxicities that …

Motivation Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous
data and making inferences in biology and many other domains, but a coherent solution for …

Graph Representation Learning methods opened new possibilities for addressing complex,
real-world problems represented by graphs. However, many graphs used in these …

We introduce a class of finite systems models of gene regulatory networks exhibiting behavior
of the cell cycle. The network is an extension of a Boolean network model. The system …

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer
therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved …