Nature Methods

Article	Citations
Robust fluorescent proteins for high-resolution microscopy and biochemical techniques	8596
Interpreting and comparing neural activity across systems by geometric deep learning	1246
Tamir Gonen	1179
More dimensions of the 3D genome	1138
Exoskeleton empowers large-scale neural recordings in freely roaming mice	882
Modeling locomotion from environment to neurons	716
Analyzing submicron spatial transcriptomics data at their original resolution	615
SNAP-tag2 improves live-cell imaging	464
How noncoding RNAs began to leave the junkyard	436
Line-scanning speeds up Brillouin microscopy	435
A complete, telomere-to-telomere human genome sequence presents new opportunities for evolutionary genomics	418
Annotating unknown metabolites	415
Optimism for abundant whole-brain connectomes and connectomic screening	413
Method of the Year 2025: electron microscopy-based connectomics	403
Antibody stabilization for thermally accelerated deep immunostaining	401
Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer	379
Fast and efficient template-mediated synthesis of genetic variants	372
Bridging the dimensional gap from planar spatial transcriptomics to 3D cell atlases	327
Chromoscope: interactive multiscale visualization for structural variation in human genomes	327
Recovery of missing single-cell RNA-sequencing data with optimized transcriptomic references	321
Maximum-likelihood model fitting for quantitative analysis of SMLM data	312
Integration of imaging-based and sequencing-based spatial omics mapping on the same tissue section via DBiTplus	311
Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput	311
DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction	310
Appeals: what, why, when, how	287

Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE	278
Tapioca: a platform for predicting de novo protein–protein interactions in dynamic contexts	265
GWAS and eQTL disparity	264
Mass spectrometry imaging: the rise of spatially resolved single-cell omics	260
MARBLE: interpretable representations of neural population dynamics using geometric deep learning	255
MRIcroGL: voxel-based visualization for neuroimaging	254
MiLoPYP: self-supervised molecular pattern mining and particle localization in situ	253
SurfDock is a surface-informed diffusion generative model for reliable and accurate protein–ligand complex prediction	231
Unlocking the power of spatial omics with AI	229
Prediction of protein subcellular localization in single cells	229
BIONIC: biological network integration using convolutions	209
Single-cell multi-omic detection of DNA methylation and histone modifications reconstructs the dynamics of epigenomic maintenance	205
Ultralong transients enhance sensitivity and resolution in Orbitrap-based single-ion mass spectrometry	203
Self-localized ultrafast pencil beam for volumetric multiphoton imaging	202
Genome-wide profiling of prime editor off-target sites in vitro and in vivo using PE-tag	201
Large Stokes shift fluorescent RNAs for dual-emission fluorescence and bioluminescence imaging in live cells	193
Quest: my postdoc home	187
BATTLES: high-throughput screening of antigen recognition under force	186
Using machine learning to predict the structure of proteins that bind to DNA and RNA	185
Setting standards for stem cells	183
Non-invasive metabolic imaging of brown adipose tissue	179
Tracking gene transfer using RNA tools	173
Sensitive protein analysis with plexDIA	173
One cell, two cell, dead cell, true cell	172
Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps	172
FISHnet: detecting chromatin domains in single-cell sequential Oligopaints imaging data	169
From GWAS to single-cell MPRA	168
Benchmarking genomic language models	166
Bat organoids at bat	160
Road trip home to start a lab	160
Mapping chromatin and DNA methylation landscapes at single-cell and single-molecule resolution	158
Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging	158
ENTERing the world of immune cells	158
Long-read sequencing in the era of epigenomics and epitranscriptomics	157
Host–microbiome maps	157
Time-resolved cryo-EM using a combination of droplet microfluidics with on-demand jetting	156
Peer review demystified: part 2	155
How developmental cell atlases inform stem cell embryo models	154
Trawling the ocean virome	153
When labs welcome under-represented groups	152
The Hodge Laplacian advances inference of single-cell trajectories	152
Tardigrades	151
Author Correction: Learning single-cell perturbation responses using neural optimal transport	148
Adaptable, turn-on maturation (ATOM) fluorescent biosensors for multiplexed detection in cells	147
Systematic scRNA-seq screens profile neural organoid response to morphogens	147
Mentoring echoes down the generations	146
Comparing classifier performance with baselines	145
Indexing and searching petabase-scale nucleotide resources	142
The crustacean Parhyale	142
Differentiating visceral sensory ganglion organoids from induced pluripotent stem cells	141

Profiling RNA at chromatin targets in situ by antibody-targeted tagmentation	140
InterPLM: discovering interpretable features in protein language models via sparse autoencoders	140
UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing	139
Genomics 2 Proteins portal: a resource and discovery tool for linking genetic screening outputs to protein sequences and structures	139
A fluorogenic chemically induced dimerization technology for controlling, imaging and sensing protein proximity	139
The tidyomics ecosystem: enhancing omic data analyses	136
Computational strategies for cross-species knowledge transfer	133
quantms: a cloud-based pipeline for quantitative proteomics enables the reanalysis of public proteomics data	130
Nicheformer: a foundation model for single-cell and spatial omics	127
The placozoan Trichoplax	126
De novo protein design with a denoising diffusion network independent of pretrained structure prediction models	125
Detection of m6A from direct RNA sequencing using a multiple instance learning framework	123
StayGold variants for molecular fusion and membrane-targeting applications	122
Neural networks built with biomolecules	121
Science while parenting	121
The LGBTQ+ job hunt	121
Deciphering subcellular organization with multiplexed imaging and deep learning	121
Combining compact human protein domains with CRISPR systems for robust gene activation	121
What makes a Nature Methods paper	119
MISO: microfluidic protein isolation enables single-particle cryo-EM structure determination from a single cell colony	115
Building an automated three-dimensional flight agent for neural network reconstruction	115
DAQ-Score Database: assessment of map–model compatibility for protein structure models from cryo-EM maps	115
Publisher Correction: ELI trifocal microscope: a precise system to prepare target cryo-lamellae for in situ cryo-ET study	114
The future of bioimage analysis: a dialog between mind and machine	114
Profiling the epigenetic landscape of the antigen receptor repertoire: the missing epi-immunogenomics data	113
Differentiable simulation expands frontiers for biophysical neural models	112
Vector choices, vector surprises	112
Open and sustainable AI: challenges, opportunities and the road ahead in the life sciences	111
CAD we share? Publishing reproducible microscope hardware	110
Propensity score weighting	109
HyU: Hybrid Unmixing for longitudinal in vivo imaging of low signal-to-noise fluorescence	109
The evolution of embryo models	109
Enabling global image data sharing in the life sciences	109
Interpretable representation learning for 3D multi-piece intracellular structures using point clouds	108
Inside the chase after those elusive proteoforms	107
Comparison of transformations for single-cell RNA-seq data	106
Merging conformational landscapes in a single consensus space with FlexConsensus algorithm	106
Permittivity tensor imaging: modular label-free imaging of 3D dry mass and 3D orientation at high resolution	106
A method for quantitative and base-resolution sequencing of pseudouridine	106
Method of the Year 2024: spatial proteomics	105
Principles and challenges of modeling temporal and spatial omics data	105
Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function	104
Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields	102
Tackling tumor complexity with single-cell proteomics	102
Automated high-speed 3D imaging of organoid cultures with multi-scale phenotypic quantification	100
Decoding post-transcriptional regulatory networks by RNA-linked CRISPR screening in human cells	100
Dissecting cell membrane tension dynamics and its effect on Piezo1-mediated cellular mechanosensitivity using force-controlled nanopipettes	96
A graph neural network that combines scRNA-seq and protein–protein interaction data	96
Nano3P-seq: transcriptome-wide analysis of gene expression and tail dynamics using end-capture nanopore cDNA sequencing	95
Analyzing single-cell bisulfite sequencing data with MethSCAn	94
SODB facilitates comprehensive exploration of spatial omics data	93
Image processing tools for petabyte-scale light sheet microscopy data	93
RNA-Puzzles Round V: blind predictions of 23 RNA structures	93
Multimodal large language models for bioimage analysis	93
Method of the Year: EM connectomics	93
Metrics reloaded: recommendations for image analysis validation	92
Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq	91
Learning single-cell perturbation responses using neural optimal transport	91
The bearded dragon Pogona vitticeps	90
First-gen scientists leap hurdles and give back	90
Unravelling cellular interactions using flow cytometry	90
Lighting up oxytocin dynamics in the brain with MTRIAOT	90
Author Correction: CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping	89
Learning the immunological repertoire	88
Author Correction: iPipet: sample handling using a tablet	88
Estimation of skeletal kinematics in freely moving rodents	88
An exceptionally photostable mScarlet3 mutant	87
ShareLoc — an open platform for sharing localization microscopy data	86
Machine learning for accelerating discovery from single-molecule data	85
Imaging the genome in motion	84
Improved structure prediction of protein complexes is within GRASP	84
Assessment of 3D MINFLUX data for quantitative structural biology in cells	83
A deconvolution algorithm to achieve super-resolution stimulated Raman scattering imaging	83
Rate variation and recurrent sequence errors in pandemic-scale phylogenetics	83
Regression modeling of time-to-event data with censoring	83
Mapping effective connectivity by virtually perturbing a surrogate brain	82
Segmentation metric misinterpretations in bioimage analysis	82
Dictys: dynamic gene regulatory network dissects developmental continuum with single-cell multiomics	82
Modeling morphogenesis	81
Illuminating life processes by vibrational probes	81

RoboEM: automated 3D flight tracing for synaptic-resolution connectomics	81
DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes	81
Highly multiplexed 3D profiling of cell states and immune niches in human tumors	80
DSI Studio: an integrated tractography platform and fiber data hub for accelerating brain research	78
Systematic assessment of long-read RNA-seq methods for transcript identification and quantification	78
Post-translational modification-centric base editor screens to assess phosphorylation site functionality in high throughput	78
DECODE: deep learning-based common deconvolution framework for various omics data	78
Scientists who decide to pick up and move	77
Statistical inference with a manifold-constrained RNA velocity model uncovers cell cycle speed modulations	77
Surfice: visualizing neuroimaging meshes, tractography streamlines and connectomes	77
Team updates at Nature Methods	77
Incorporating the image formation process into deep learning improves network performance	77
METLIN-CCS: an ion mobility spectrometry collision cross section database	76
Scalable and unbiased sequence-informed embedding of single-cell ATAC-seq data with CellSpace	76
Orthrus: toward evolutionary and functional RNA foundation models	76
A-SOiD, an active-learning platform for expert-guided, data-efficient discovery of behavior	75
TIRTL-seq: deep, quantitative and affordable paired TCR repertoire sequencing	75
Smart parallel automated cryo-electron tomography	75
A three-photon head-mounted microscope for imaging all layers of visual cortex in freely moving mice	75
CAVE: Connectome Annotation Versioning Engine	74
ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction	73
Deep 3D histology powered by tissue clearing, omics and AI	73
BEAST X for Bayesian phylogenetic, phylogeographic and phylodynamic inference	73
The SplitsTree App: interactive analysis and visualization using phylogenetic trees and networks	72
Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function	72
Repurposing large-format microarrays for scalable spatial transcriptomics	71
Coupling CRISPR scanning with targeted chromatin accessibility profiling using a double-stranded DNA deaminase	71
Jasmine and Iris: population-scale structural variant comparison and analysis	71
Towards a full picture of the total transcriptome	70
Spike sorting with Kilosort4	70
Characterizing protein sequence determinants of nuclear condensates by high-throughput pooled imaging with CondenSeq	70
A new member of the spatial omics family	69
A diamond microscope	69
Augmented translation via multitailed mRNA	69
A peek into early human embryogenesis	68
Mapping deformations and increasing quantitative accuracy in expansion microscopy	68
Predicted protein structures expand the CATH database	68
Summer school in wartime	67
A structural learning method to uncover how information between single cells flows	67
ScanNet uncovers binding motifs in protein structures with deep learning	67
Image restoration of degraded time-lapse microscopy data mediated by near-infrared imaging	66
Machine learning-trained protein domain insertion for the design of switchable proteins	66
Barcoded CRISPR screens reveal RNA regulatory networks	66
Inferring how animals deform improves cell tracking	65
Cell typing by electrophysiology	64
Small data methods in omics: the power of one	64
In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain–striatum–cortex assembloids	63
Guinea pigs as embryo models	63
Microscopes are coming for your job	63
Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s	63
Hydrogel-based molecular tension fluorescence microscopy for investigating receptor-mediated rigidity sensing	63
Chemical space exploration with quantum computing	63
Spatial Omics DataBase (SODB): increasing accessibility to spatial omics data	62
Combating hallucination in digital pathology	62
POLCAM: instant molecular orientation microscopy for the life sciences	62
Data sharing is the future	62
Entering the era of deep single-cell proteomics	62
Seeing data as t-SNE and UMAP do	62
Structure prediction for orphan proteins	62
The big picture in science	62
Peptide sequencing based on host–guest interaction-assisted nanopore sensing	62
Predicting cellular responses with conditional diffusion models	61
ESPRESSO: spatiotemporal omics based on organelle phenotyping	61
Towards predictive virtual embryos with genomics and AI	61
Automated classification of cellular expression in multiplexed imaging data with Nimbus	61
Open microscopy in the life sciences: quo vadis?	61
Intrinsic protein disorder at scale	60
Self-supervised learning of molecular representations	60
Microbial-enrichment method enables high-throughput metagenomic characterization from host-rich samples	60
Molecular pixelation: spatial proteomics of single cells by sequencing	59
Selective-plane-activation structured illumination microscopy	59
JIPipe: visual batch processing for ImageJ	59
Using AI in bioimage analysis to elevate the rate of scientific discovery as a community	58
GeneAgent: self-verification language agent for gene-set analysis using domain databases	58
SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms	58
Neural engineering with photons as synaptic transmitters	57
Gapr for large-scale collaborative single-neuron reconstruction	57
Author Correction: Segment Anything for Microscopy	57
CaBLAM: a high-contrast bioluminescent Ca2+ indicator derived from an engineered Oplophorus gracilirostris luciferase	57
Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines	57
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA	57
Spotting T and B cell receptors	56
In situ electro-sequencing	56
A closer look at FluoroCubes	56
Development of the human head	56
A genome-scale approach for determining the function of phosphorylation sites	55
Fluorescent actinometers for fast and simple quantitative measurement of light intensity	55
A flexible system for tissue-specific gene expression in mice using adeno-associated virus	55
Immune intestine interfaces in vitro	55
Next-generation expansion microscopy	55
Base editing in mitochondrial DNA	55
Tracking cell ancestry and spatial gene expression with high resolution	54
Not if but when nanopore protein sequencing meets single-cell proteomics	54
Hydrogel fibers that enable optogenetic pain inhibition during locomotion	54
TREX reveals proteins that bind to specific RNA regions in living cells	54