Squidiff is a diffusion-based model to predict transcriptomic changes in response to perturbations.

Since the chance discovery of nanobodies in the late 1980s, their uses and applications have kept growing. Researchers are now exploring new ways to harness nanobody versatility.

mScarlet3-S2 is a red fluorescent protein that is highly photostable and sufficiently bright. It is especially useful for applications such as stimulated emission depletion or structured illumination microscopy imaging with prolonged imaging times.

We highlight some of the Nature Methods team’s favorite papers published in 2025, reflecting on some trends and new technology developments.

DBiTplus represents an integrated experimental and computational workflow that unifies sequencing-based and imaging-based spatial omics, demonstrated by combining transcriptomic profiling and multiplexed protein imaging on the same tissue section.

MaAsLin 3 is a comprehensive and flexible framework for microbiome association studies with expanded toolsets of statistical models, tests and types of inference.

SpatialZ generates virtual single-cell spatial transcriptomics slices between experimentally measured sections, enabling accurate and efficient building of 3D cell atlases of different tissues.

Pertpy serves as a one-stop and performant framework for single-cell perturbation data analysis.

cellSTAAR advances noncoding rare variant association analysis by integrating single-cell genomics data.

SmartEM is a ‘smart’ pipeline for electron microscopy-based data acquisition for connectomics. In order to efficiently image large datasets, the approach involves imaging at short pixel dwell times and identifying problematic regions that are then imaged with longer dwell times and therefore higher quality.

We highlight some of the Nature Methods team’s favorite papers published in 2025, reflecting on some trends and new technology developments.

Not all conferences offer childcare, but when they do, these scientists, who are also mothers, rejoice. The toys are pretty good, too.