Nature Methods

Article	Citations
Robust fluorescent proteins for high-resolution microscopy and biochemical techniques	1273
Interpreting and comparing neural activity across systems by geometric deep learning	1244
More dimensions of the 3D genome	1169
Exoskeleton empowers large-scale neural recordings in freely roaming mice	935
Modeling locomotion from environment to neurons	747
Analyzing submicron spatial transcriptomics data at their original resolution	644
SNAP-tag2 improves live-cell imaging	482
A complete, telomere-to-telomere human genome sequence presents new opportunities for evolutionary genomics	445
Annotating unknown metabolites	442
Optimism for abundant whole-brain connectomes and connectomic screening	440
Antibody stabilization for thermally accelerated deep immunostaining	429
Method of the Year 2025: electron microscopy-based connectomics	429
Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer	423
Large Stokes shift fluorescent RNAs for dual-emission fluorescence and bioluminescence imaging in live cells	401
Prediction of protein subcellular localization in single cells	396
GWAS and eQTL disparity	339
Appeals: what, why, when, how	339
MiLoPYP: self-supervised molecular pattern mining and particle localization in situ	338
Chromoscope: interactive multiscale visualization for structural variation in human genomes	337
Bridging the dimensional gap from planar spatial transcriptomics to 3D cell atlases	330
Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput	323
Line-scanning speeds up Brillouin microscopy	322
Self-localized ultrafast pencil beam for volumetric multiphoton imaging	292
Ultralong transients enhance sensitivity and resolution in Orbitrap-based single-ion mass spectrometry	283
How noncoding RNAs began to leave the junkyard	276

MARBLE: interpretable representations of neural population dynamics using geometric deep learning	272
Single-cell multi-omic detection of DNA methylation and histone modifications reconstructs the dynamics of epigenomic maintenance	272
Tapioca: a platform for predicting de novo protein–protein interactions in dynamic contexts	264
Genome-wide profiling of prime editor off-target sites in vitro and in vivo using PE-tag	263
DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction	239
Fast and efficient template-mediated synthesis of genetic variants	238
Maximum-likelihood model fitting for quantitative analysis of SMLM data	217
Recovery of missing single-cell RNA-sequencing data with optimized transcriptomic references	216
Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE	213
MRIcroGL: voxel-based visualization for neuroimaging	209
Unlocking the power of spatial omics with AI	209
SurfDock is a surface-informed diffusion generative model for reliable and accurate protein–ligand complex prediction	204
Integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section via DBiTplus	198
Mass spectrometry imaging: the rise of spatially resolved single-cell omics	197
BIONIC: biological network integration using convolutions	185
Quest: my postdoc home	184
Setting standards for stem cells	182
Using machine learning to predict the structure of proteins that bind to DNA and RNA	182
BATTLES: high-throughput screening of antigen recognition under force	182
Non-invasive metabolic imaging of brown adipose tissue	180
Sensitive protein analysis with plexDIA	178
Tracking gene transfer using RNA tools	173
One cell, two cell, dead cell, true cell	169
FISHnet: detecting chromatin domains in single-cell sequential Oligopaints imaging data	167
From GWAS to single-cell MPRA	166
Benchmarking genomic language models	165
Bat organoids at bat	164
Road trip home to start a lab	164
ENTERing the world of immune cells	163
Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging	162
Mapping chromatin and DNA methylation landscapes at single-cell and single-molecule resolution	161
Host–microbiome maps	158
Peer review demystified: part 2	157
How developmental cell atlases inform stem cell embryo models	156
Indexing and searching petabase-scale nucleotide resources	155
Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures	154
quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data	153
Trawling the ocean virome	152
The Hodge Laplacian advances inference of single-cell trajectories	152
When labs welcome under-represented groups	148
Computational strategies for cross-species knowledge transfer	148
The crustacean Parhyale	147
A fluorogenic chemically induced dimerization technology for controlling, imaging and sensing protein proximity	145
De novo protein design with a denoising diffusion network independent of pretrained structure prediction models	145
Detection of m6A from direct RNA sequencing using a multiple instance learning framework	145
Differentiating visceral sensory ganglion organoids from induced pluripotent stem cells	145
Mentoring echoes down the generations	143
Comparing classifier performance with baselines	139
Author Correction: Learning single-cell perturbation responses using neural optimal transport	135
Adaptable, turn-on maturation (ATOM) fluorescent biosensors for multiplexed detection in cells	129

Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps	127
Profiling RNA at chromatin targets in situ by antibody-targeted tagmentation	127
Time-resolved cryo-EM using a combination of droplet microfluidics with on-demand jetting	124
The tidyomics ecosystem: enhancing omic data analyses	124
UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing	124
The placozoan Trichoplax	123
Long-read sequencing in the era of epigenomics and epitranscriptomics	121
Systematic scRNA-seq screens profile neural organoid response to morphogens	121
Tardigrades	120
InterPLM: discovering interpretable features in protein language models via sparse autoencoders	120
StayGold variants for molecular fusion and membrane-targeting applications	119
Nicheformer: a foundation model for single-cell and spatial omics	119
The LGBTQ+ job hunt	118
Deciphering subcellular organization with multiplexed imaging and deep learning	117
What makes a Nature Methods paper	115
Neural networks built with biomolecules	115
A method for quantitative and base-resolution sequencing of pseudouridine	114
Science while parenting	113
Inside the chase after those elusive proteoforms	113
Method of the Year: EM connectomics	112
Analyzing single-cell bisulfite sequencing data with MethSCAn	112
Tackling tumor complexity with single-cell proteomics	110
HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence	110
Differentiable simulation expands frontiers for biophysical neural models	109
The future of bioimage analysis: a dialog between mind and machine	109
Building an automated three-dimensional flight agent for neural network reconstruction	109
Profiling the epigenetic landscape of the antigen receptor repertoire: the missing epi-immunogenomics data	108
Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences	107
Vector choices, vector surprises	107
Multimodal large language models for bioimage analysis	106
Publisher Correction: ELI trifocal microscope: a precise system to prepare target cryo-lamellae for in situ cryo-ET study	104
Interpretable representation learning for 3D multi-piece intracellular structures using point clouds	103
The evolution of embryo models	103
Permittivity tensor imaging: modular label-free imaging of 3D dry mass and 3D orientation at high resolution	101
A graph neural network that combines scRNA-seq and protein–protein interaction data	100
Merging conformational landscapes in a single consensus space with FlexConsensus algorithm	100
SODB facilitates comprehensive exploration of spatial omics data	99
Propensity score weighting	97
Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields	97
Enabling global image data sharing in the life sciences	97
Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq	97
Principles and challenges of modeling temporal and spatial omics data	97
DAQ-Score Database: assessment of map–model compatibility for protein structure models from cryo-EM maps	96
Image processing tools for petabyte-scale light sheet microscopy data	95
Nano3P-seq: transcriptome-wide analysis of gene expression and tail dynamics using end-capture nanopore cDNA sequencing	95
Dissecting cell membrane tension dynamics and its effect on Piezo1-mediated cellular mechanosensitivity using force-controlled nanopipettes	94
Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification	94
Combining compact human protein domains with CRISPR systems for robust gene activation	94
Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function	93
RNA-Puzzles Round V: blind predictions of 23 RNA structures	93
Comparison of transformations for single-cell RNA-seq data	92
Learning single-cell perturbation responses using neural optimal transport	92
MISO: microfluidic protein isolation enables single-particle cryo-EM structure determination from a single cell colony	92
Metrics reloaded: recommendations for image analysis validation	91
Method of the Year 2024: spatial proteomics	91
Decoding post-transcriptional regulatory networks by RNA-linked CRISPR screening in human cells	91
First-gen scientists leap hurdles and give back	90
Lighting up oxytocin dynamics in the brain with MTRIAOT	90
The bearded dragon Pogona vitticeps	89
Author Correction: CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping	88
Unravelling cellular interactions using flow cytometry	88
Estimation of skeletal kinematics in freely moving rodents	86
Author Correction: iPipet: sample handling using a tablet	86
Learning the immunological repertoire	85
ShareLoc — an open platform for sharing localization microscopy data	84
An exceptionally photostable mScarlet3 mutant	84
Machine learning for accelerating discovery from single-molecule data	84
Improved structure prediction of protein complexes is within GRASP	83
Imaging the genome in motion	83
A deconvolution algorithm to achieve super-resolution stimulated Raman scattering imaging	82
Assessment of 3D MINFLUX data for quantitative structural biology in cells	81
Regression modeling of time-to-event data with censoring	81
DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes	80
Modeling morphogenesis	79
Illuminating life processes by vibrational probes	79
Coupling CRISPR scanning with targeted chromatin accessibility profiling using a double-stranded DNA deaminase	79
A three-photon head-mounted microscope for imaging all layers of visual cortex in freely moving mice	78
Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function	78
Team updates at Nature Methods	77
DECODE: deep learning-based common deconvolution framework for various omics data	77

TIRTL-seq: deep, quantitative and affordable paired TCR repertoire sequencing	77
Scalable and unbiased sequence-informed embedding of single-cell ATAC-seq data with CellSpace	77
Mapping effective connectivity by virtually perturbing a surrogate brain	77
Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations	77
CAVE: Connectome Annotation Versioning Engine	76
Post-translational modification-centric base editor screens to assess phosphorylation site functionality in high throughput	76
Segmentation metric misinterpretations in bioimage analysis	76
Repurposing large-format microarrays for scalable spatial transcriptomics	76
Orthrus: toward evolutionary and functional RNA foundation models	76
Incorporating the image formation process into deep learning improves network performance	76
AreTomoLive: automated reconstruction of comprehensively corrected and denoised cryo-electron tomograms in real time and at high throughput	76
A multimodal adaptive optical microscope for in vivo imaging from molecules to organisms	76
Deep 3D histology powered by tissue clearing, omics and AI	75
Scientists who decide to pick up and move	74
Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics	74
Rate variation and recurrent sequence errors in pandemic-scale phylogenetics	73
Surfice: visualizing neuroimaging meshes, tractography streamlines and connectomes	72
Jasmine and Iris: population-scale structural variant comparison and analysis	72
RoboEM: automated 3D flight tracing for synaptic-resolution connectomics	72
Highly multiplexed 3D profiling of cell states and immune niches in human tumors	72
Characterizing protein sequence determinants of nuclear condensates by high-throughput pooled imaging with CondenSeq	70
Smart parallel automated cryo-electron tomography	70
BEAST X for Bayesian phylogenetic, phylogeographic and phylodynamic inference	70
Spike sorting with Kilosort4	70
The SplitsTree App: interactive analysis and visualization using phylogenetic trees and networks	69
METLIN-CCS: an ion mobility spectrometry collision cross section database	69
DSI Studio: an integrated tractography platform and fiber data hub for accelerating brain research	68
Systematic assessment of long-read RNA-seq methods for transcript identification and quantification	68
A-SOiD, an active-learning platform for expert-guided, data-efficient discovery of behavior	68
Towards a full picture of the total transcriptome	67
A diamond microscope	67
Augmented translation via multitailed mRNA	67
A new member of the spatial omics family	66
Mapping deformations and increasing quantitative accuracy in expansion microscopy	66
A peek into early human embryogenesis	65
ScanNet uncovers binding motifs in protein structures with deep learning	65
Summer school in wartime	65
A structural learning method to uncover how information between single cells flows	65
Cell typing by electrophysiology	64
Machine learning-trained protein domain insertion for the design of switchable proteins	64
Chemical space exploration with quantum computing	64
Barcoded CRISPR screens reveal RNA regulatory networks	64
Small data methods in omics: the power of one	64
Image restoration of degraded time-lapse microscopy data mediated by near-infrared imaging	64
Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s	63
Combating hallucination in digital pathology	63
Hydrogel-based molecular tension fluorescence microscopy for investigating receptor-mediated rigidity sensing	63
The big picture in science	63
Guinea pigs as embryo models	63
Structure prediction for orphan proteins	63
Entering the era of deep single-cell proteomics	63
Spatial Omics DataBase (SODB): increasing accessibility to spatial omics data	62
Towards predictive virtual embryos with genomics and AI	62
Data sharing is the future	62
Predicting cellular responses with conditional diffusion models	62
Open microscopy in the life sciences: quo vadis?	61
Author Correction: Segment Anything for Microscopy	61
Gapr for large-scale collaborative single-neuron reconstruction	61
Molecular pixelation: spatial proteomics of single cells by sequencing	60
Using AI in bioimage analysis to elevate the rate of scientific discovery as a community	60
CaBLAM: a high-contrast bioluminescent Ca2+ indicator derived from an engineered Oplophorus gracilirostris luciferase	60
Neural engineering with photons as synaptic transmitters	60
Recommendations and considerations for hydroxyl radical protein footprinting–mass spectrometry	60
Intrinsic protein disorder at scale	59
Self-supervised learning of molecular representations	59
Inferring how animals deform improves cell tracking	58
Selective-plane-activation structured illumination microscopy	58
JIPipe: visual batch processing for ImageJ	58
Microbial-enrichment method enables high-throughput metagenomic characterization from host-rich samples	58
Predicted protein structures expand the CATH database	58
GeneAgent: self-verification language agent for gene-set analysis using domain databases	58
Seeing data as t-SNE and UMAP do	58
Automated classification of cellular expression in multiplexed imaging data with Nimbus	58
In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain–striatum–cortex assembloids	57
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA	57
Peptide sequencing based on host–guest interaction-assisted nanopore sensing	57
POLCAM: instant molecular orientation microscopy for the life sciences	56
Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines	56
ESPRESSO: spatiotemporal omics based on organelle phenotyping	56
Microscopes are coming for your job	55
SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms	55
A closer look at FluoroCubes	55
A genome-scale approach for determining the function of phosphorylation sites	54
In situ electro-sequencing	54
Next-generation expansion microscopy	54
Development of the human head	54
Fluorescent actinometers for fast and simple quantitative measurement of light intensity	54
A flexible system for tissue-specific gene expression in mice using adeno-associated virus	54
Spotting T and B cell receptors	54
Completing human genomes	53
Inferring cancer type-specific patterns of metastatic spread using Metient	53
Multiplexed profiling of intracellular protein abundance, activity, interactions and druggability with LABEL-seq	53
Tracking cell ancestry and spatial gene expression with high resolution	53
Hydrogel fibers that enable optogenetic pain inhibition during locomotion	53
SPARKing aptamer discovery	53