SVPG performs accurate pangenome-facilitated structural variant detection and accelerates pangenome graph augmentation using long-read sequencing data.

CFM enables tunable cell confinement for measuring traction forces exerted by single cells and cell aggregates in tissue-mimicking microenvironments.

Rather than relying on pre-specified ancestry labels, which often fail to capture the full genetic heterogeneity of diverse populations, SPLENDID treats ancestry as a continuum and improves polygenic ...

A compact protein pair that heterodimerizes upon red light activation, FenixS and Ash1, is developed for optogenetic applications.

Studying the brain mechanisms of natural behaviors is experimentally challenging. We developed a miniaturized, wireless platform to record and manipulate neural and physiological activity in small ani...

WILD is a wireless device that can record neuronal activity, perform optogenetic stimulations, record animal movements, record the environment or eye movements via an integrated camera, analyze the da...

MemBrain v2 enables streamlined analysis of membranes in cryo-electron tomography by providing user-friendly tools for membrane segmentation, membrane protein localization and spatial analysis, suppor...

IRIS learns conserved signaling representations from in vitro perturbation data to reconstruct signaling states and histories across diverse in vivo cellular contexts.

DeepWonder3D is a pipeline for neuronal extraction from volumetric calcium imaging data acquired with a variety of one-photon or two-photon microscopy modalities.

Spl-ISO-Seq2, Spl-IsoQuant-2 and Spl-IsoFind enable isoform sequencing, barcode calling of >450 million barcodes, and spatially variable isoform detection with high spatial resolution as demonstrat...

Tau: distinguishing the good, the bad and the ugly.

Iterative Mapping of proteoforms enables large-scale measurement of intact proteoforms with single-molecule resolution. The approach is demonstrated here by quantifying tau proteoform groups across co...

This Review provides a comprehensive discussion of how methods in machine learning and computer vision have been used to improve super-resolution microscopy to gain insights into subcellular biology.

This Perspective provides recommendations for open and sustainable AI and associated resources facilitating exploration and implementation.

Foundation models are becoming increasingly popular across various biological domains, yet rigorous methods to comprehensively evaluate their full potential remain underdeveloped. This Perspective dis...

This Perspective examines the role of AI-based image analysis when applied to stem cell-derived models.

This Perspective highlights key research areas within mass spectrometry-based proteomics where AI is poised to drive significant advances.

Specialized research software has historically been costly and time-consuming to create, but large language models (LLMs) have become capable enough at code generation to fundamentally change this. We...

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 a...

Artificial intelligence is rapidly changing the landscape of how biological data are acquired and analyzed. Almost no corner of biological research has been left untouched.

This month, several review and opinion pieces discuss how AI is having an impact across nearly all areas of biological research.See Editorial

Cell biologists have long known that mechanical forces, such as tension and compression, influence tissue differentiation. Now, advanced methods are letting them observe and manipulate these forces in...

Spatial-ATAC-Hi-C enables the profiling of both chromatin accessibility and organization in a spatially resolved manner, as demonstrated on mouse brain and human glioblastoma and astrocytoma samples.

Advances in electron microscopy instrumentation and methods continue to drive progress in the physical and life sciences. The 4th edition of this conference will bring together researchers from physic...

This Perspective examines the role of AI-based image analysis when applied to stem cell-derived models.

This Perspective highlights key research areas within mass spectrometry-based proteomics where AI is poised to drive significant advances.

Specialized research software has historically been costly and time-consuming to create, but large language models (LLMs) have become capable enough at code generation to fundamentally change this. We describe how LLM-assisted programming disrupts the landscape by allowing researchers to build tools without support from software engineers, illustrate this with an example built rapidly by a single LLM-assisted developer, and discuss opportunities and risks.

A multichannel microscopy method that exploits the polarization of fluorescent molecules reconstructs super-resolved images from a single camera frame. The approach not only captures fast cellular dyn...

Using a polarimetric approach, SPIFFI enables real-time super-resolution imaging of live-cell samples.

REDCAT is a multimodal, all-optical platform that maps metabolic activity alongside cell identity in intact tissues at single-cell and subcellular resolution. By integrating Raman imaging, autofluores...

Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT) integrates stimulated Raman scattering microscopy and high-plex immunofluorescence to profile single-cell proteins, lipids, nuclear metab...

Two scientists blend their love of music and science in different ways.

Benchmarking computational tools for cutting-edge technologies such as spatially resolved transcriptomics is challenging owing to the lack of reproducibility, of data and of evaluation strategies that...

Benchmarking spatially aware clustering is challenging. SACCELERATOR is an open-source, extensible framework that formalizes expert-guided spatial clustering analysis.

MS2 bacteriophage-derived protein shells called ‘nanocrates’ help address the air–water interface-induced artifacts in cryo-EM structure determination by encapsulating target proteins and enabling the...

Integrating different modalities and flexibly amplifying signals presents a major challenge for imaging-based spatial biology. We present protein and nucleic acid serial tyramide amplification (PASTA)...

PASTA is a platform-agnostic signal amplification approach for multiplexed imaging across modalities.

Voltage imaging across much of the zebrafish brain is achieved at 200.8 Hz, by optimizing a remote-scanning light-sheet microscope.

A Kaggle challenge for particle picking in experimental cryo-electron tomography data delivered new machine learning algorithms that outperformed state-of-the-art software and provides a critical refe...

Direct preference optimization (DPO) aligns a pretrained protein language model with experimental stability data, yielding ProteinDPO, a model that scores and generates thermostable protein sequences....

This Article demonstrates that direct preference optimization (DPO) can be used to effectively align an unsupervised structure-conditioned language model with biophysical information. The aligned mode...

kpiCells are a biomimetic artificial cell system to investigate mechanoregulation in cell–cell interactions.

Advances in electron microscopy instrumentation and methods continue to drive progress in the physical and life sciences. The 4th edition of this conference will bring together researchers from physic...

Nature Methods - Getting over ANOVA: estimation graphics for multi-group comparisons

Nature Methods - Bridging complexity and accessibility in metabolomics with MetaboApps

A little more than one year ago, Nature Methods rolled out a program to formally recognize early-career researcher contributions to our peer review process. Here we provide an update on the program’s ...

GHT-SELEX—high-throughput SELEX with fragmented genomic DNA—shows that transcription factors can be rather particular about which genomic loci they bind, and that C2H2 zinc finger proteins often engag...