Spatial omics technologies enable a deeper understanding of cellular organizations and
interactions within a tissue of interest. These assays can identify specific compartments or …

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images.
Existing cell segmentation methods are often tailored to specific modalities or require …

Towards foundation models of biological image segmentation | Nature Methods Skip to main
content Thank you for visiting nature.com. You are using a browser version with limited support …

Reverse transcription has frequently been co-opted for cellular functions and in prokaryotes
is associated with protection against viral infection, but the underlying mechanisms of …

Highlights•Adoption of segmentation models driven by user-friendly tools and
documentation.•Advancements in novel architectures are driven by the need for a truly …

Innate immune pattern recognition receptors, such as the Toll-like receptors (TLRs), are key
mediators of the immune response to infection and central to our understanding of health …

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-
networks to analyse bacterial microscopy images using the recently developed …

The drivers of immune evasion are not entirely clear, limiting the success of cancer
immunotherapies. Here we applied single-cell spatial and perturbational transcriptomics to …

Patescibacteria, also known as the candidate phyla radiation (CPR), are a diverse group of
bacteria that constitute a disproportionately large fraction of microbial dark matter. Its few …

Cells are a fundamental unit of biological organization, and identifying them in imaging data–
cell segmentation–is a critical task for various cellular imaging experiments. While deep …