This Perspective establishes a comprehensive and practical framework to guide intrinsically disordered protein (IDP) ensemble determination, benchmarking and interpretation, as well as proposes a roadmap for IDP ensemble determination, uncertainty quantification and actionable benchmarking strategies.

A pangenome can reveal the spectrum of genome variation within a species. The toolbox for working with pangenomes is filling up.

SeeDB-Live is a tissue-clearing approach for live samples such as tissue slices or the in vivo brain. It improves image quality while having minimal effects on electrophysiological properties of neurons.

DECODE is a universal deconvolution framework for both cell types and cell states that can be applied to transcriptomic, proteomic and metabolomic data.

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

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.

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.

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.

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

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.

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.

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.

A non-comprehensive look back on the happenings in the spatial proteomics field since our Method of the Year 2024.