Nature Methods, Published online: 04 April 2026; doi:10.1038/s41592-026-03058-1

Deciphering the genomic regulatory code driving cell type-specific gene regulation has been a research quest for decades. We present CREsted, a software package that provides data-driven insights into the regulatory elements driving enhancer function in cell types from single-cell chromatin accessibility atlases in various tissues and species.

Nature Methods, Published online: 02 April 2026; doi:10.1038/s41592-026-03057-2

CREsted is an efficient and user-friendly toolbox for analysis, modeling and design of cell-type-specific enhancers across diverse species.

Nature Methods, Published online: 01 April 2026; doi:10.1038/s41592-026-03047-4

ROCKET improves experimental structure elucidation by integrating implicit structural knowledge from OpenFold, a trainable reimplementation of AlphaFold2, with X-ray crystallographic and cryo-electron microscopy experiments.

Nature Methods, Published online: 01 April 2026; doi:10.1038/s41592-026-03059-0

Plenty of scientists give their instruments nicknames, chosen with affection and for good reasons.

Nature Methods, Published online: 01 April 2026; doi:10.1038/s41592-026-03027-8

Language model-inferred embeddings are replacing structure-derived descriptions of proteins, genes and genomes. We propose a model-agnostic measure to quantify reliability of these new representations.

Nature Methods, Published online: 01 April 2026; doi:10.1038/s41592-026-03028-7

A model-agnostic empirical framework is proposed to measure the uncertainty associated with protein embeddings and to assess the biological relevance of these embeddings in order to improve model reliability and performance on downstream tasks.

Nature Methods, Published online: 01 April 2026; doi:10.1038/s41592-026-03052-7

A new sequencing-based method optimizes barcode-based synaptic mapping by capturing paired neuronal barcodes from intact synaptic fragments, achieving the efficiency needed to scale toward comprehensive brain connectivity maps.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03049-2

By allowing protein language models (PLMs) to learn from each other’s most confident predictions, we compressed the collective knowledge of existing PLMs into VESM — a single sequence-only model that outperforms state-of-the-art hybrid methods. VESM predictions extended beyond binary pathogenicity classification, accurately quantifying the severity of variant effects on clinical phenotypes.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03050-9

A co-distillation framework is used to iteratively adapt sequence-only protein language models for high-accuracy variant effect prediction, without the need for additional structural or genetic data. Individual protein language models therefore self-improve by distilling the most confident predictions from multiple models, achieving state-of-the-art performance across multiple variant effect prediction benchmarks.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03025-w

Hyperspectral fingerprint optoacoustic microscopy enables the differentiation of different lipid classes in living cells, which is of interest in the study of lipid metabolism in health and disease.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03041-w

Tunable hydrogel-based micropillar arrays are fabricated to model the biomechanical cues of size, shape and rigidity characteristic of axons. These next-gen micropillars allow the exquisite examination of the cell biology of oligodendroglia, resolving the myelinogenic potential, myelin extent and kinetics of wrapping in a cell-autonomous manner.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03024-x

Sensing and mapping lipid species in living cells has been challenging. Here, we show that hyperspectral fingerprint opto-acoustic microscopy (HyFOPM) achieves label-free visualization of specific lipid species, including sphingomyelin and cholesterol, within living cells. This technology could offer insight into lipid metabolism and disease without requiring fluorescence or other exogenous tags.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03045-6

In this study, long-read RNA sequencing achieves accurate single-nucleotide polymorphism calling, haplotype phasing and allele-specific expression analysis.

Nature Methods, Published online: 30 March 2026; doi:10.1038/s41592-026-03048-3

To study myelination in vitro, a hydrogel-based micropillar array is used to mimic the stiffness and diameter of axons, with variations in these properties allowing evaluation of their influence. The platform can also be used to assess the effects of putative remyelination drugs.

Nature Methods, Published online: 27 March 2026; doi:10.1038/s41592-026-03034-9

3d-OT enables efficient alignment of heterogenous multi-omics tissue slices and spatial domain identification.

Nature Methods, Published online: 27 March 2026; doi:10.1038/s41592-026-03063-4

A nascent group of researchers sees planetary health as an urgent reason to bridge the molecular and planetary scales. This is shaping their strategies, methods, collaborations and outlook about their fields.

Nature Methods, Published online: 26 March 2026; doi:10.1038/s41592-026-03055-4

Predictive virtual embryo systems that integrate single-cell and spatial data with artificial intelligence (AI) techniques offer a promising avenue for modeling mammalian embryogenesis across scales and could advance our fundamental understanding of development and congenital disease.

Nature Methods, Published online: 24 March 2026; doi:10.1038/s41592-026-03030-z

DIAMOND DeepClust provides an ultra-fast clustering method for organizing the protein universe of life at low sequence identity, enabling large-scale dimensionality reduction and improving downstream structure prediction with AlphaFold2.