Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …

Single-cell atlases promise to provide a 'missing link'between genes, diseases and
therapies. By identifying the specific cell types, states, programs and contexts where disease …

Non-genetic mechanisms have recently emerged as important drivers of cancer therapy
failure, where some cancer cells can enter a reversible drug-tolerant persister state in …

Over the past few decades, RNA sequencing has significantly progressed, becoming a
paramount approach for transcriptome profiling. The revolution from bulk RNA sequencing …

Cell atlas projects and high-throughput perturbation screens require single-cell sequencing
at a scale that is challenging with current technology. To enable cost-effective single-cell …

Glioblastomas harbor diverse cell populations, including rare glioblastoma stem cells
(GSCs) that drive tumorigenesis. To characterize functional diversity within this population …

Cultured cell lines are the workhorse of cancer research, but the extent to which they
recapitulate the heterogeneity observed among malignant cells in tumors is unclear. Here …

Genome sequencing studies have identified millions of somatic variants in cancer, but it
remains challenging to predict the phenotypic impact of most. Experimental approaches to …

Deep learning architectures such as variational autoencoders have revolutionized the
analysis of transcriptomics data. However, the latent space of these variational …

Morphological and gene expression profiling can cost-effectively capture thousands of
features in thousands of samples across perturbations by disease, mutation, or drug …