Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …

Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …

For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most
studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula …

Recent self-supervised methods for image representation learning are based on maximizing
the agreement between embedding vectors from different views of the same image. A trivial …

Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of
immune cell diversity. However, consistent definition of cell subtypes and cell states across …

Clustering is a fundamental machine learning task, which aim at assigning instances into
groups so that similar samples belong to the same cluster while dissimilar samples belong …

The identification of the mechanisms by which T-cell receptors (TCRs) interact with human
antigens provides a crucial opportunity to develop new vaccines, diagnostics and …

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized
transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains …

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The
establishment of large-scale genomic collaborative efforts along with the development of …

The increasing generation of population-level single-cell atlases has the potential to link
sample metadata with cellular data. Constructing such references requires integration of …