Cancer is the quintessential complex disease. As technologies evolve faster each day, we
are able to quantify the different layers of biological elements that contribute to the …

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing …

Computational and mathematical models are key to obtain a system-level understanding of
biological processes, but their limitations have to be clearly defined to allow their proper …

The exposome recognizes that individuals are exposed simultaneously to a multitude of
different environmental factors and takes a holistic approach to the discovery of etiological …

Abstract Analysis of selected cancer genes has become an important tool in precision
oncology but cannot fully capture the molecular features and, most importantly …

Background Machine learning (ML) methodology development for the classification of
immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of …

The accurate identification and quantitation of RNA isoforms present in the cancer
transcriptome is key for analyses ranging from the inference of the impacts of somatic …

Pancreatic cancer continues to be one of the deadliest malignancies and is the third leading
cause of cancer-related mortality in the United States. Based on several models, it is …

Developing or independently evaluating algorithms in biomedical research is difficult
because of restrictions on access to clinical data. Access is restricted because of privacy …

DNA sequencing is becoming more affordable and faster through advances in high-
throughput technologies. This rise in data availability has contributed to the development of …