Nature Methods

Article	Citations
Combined sequencing of genomes and epigenomes	6055
A celebration of structural biology	2474
Jie Xiao	1035
Genome-wide analysis of structural variation	752
Expanding views of the transcriptome	683
iSCAT gets a signal boost	674
Mapping human hematopoiesis	667
Methods lead the way	658
New happenings at Nature Methods	637
A multimodal whole-body atlas	577
Seeking more nucleases	573
When peace arrives	510
Inferring biological age from the transcriptome with RAPToR	487
Robust fluorescent proteins for high-resolution microscopy and biochemical techniques	412
How’s your health, forests?	406
Deep learning method for the prediction of glycan structures from mass spectrometry data	395
High-speed low-light in vivo two-photon voltage imaging of large neuronal populations	319
RepoRT: a comprehensive repository for small molecule retention times	296
Visual interpretability of bioimaging deep learning models	291
ReX: an integrative tool for quantifying and optimizing measurement reliability for the study of individual differences	290
Chroma is a generative model for protein design	285
Artificial intelligence gives neuron reconstruction a performance boost	280
Doubling the resolution of light-sheet fluorescence microscopy	271
Vascular subtypes on a dish	264
Diving deeper in the 3D genome	262

LocMoFit quantifies cellular structures in super-resolution data	253
Targeted illumination confocal microscopy enables in vivo voltage imaging in thick tissue	250
Integrating one’s LGBTQ+ identity into one’s science	238
GWAS and eQTL disparity	236
In vivo traction force microscopy	236
Long-term monosynaptic tracing	228
Dissecting subcellular architecture of whole cells	228
Light-Seq: from microscopy to transcriptomics and back	223
Deep-learning language models help to improve protein sequence alignment	217
Ultra-long-working-distance multiphoton objective unlocks new possibilities for imaging	216
Breaking barriers for intravital imaging	215
Computation and biology: a partnership	211
Annotating unknown metabolites	208
Modeling locomotion from environment to neurons	197
Spatially resolved multiomics	197
Better detection for localization microscopy	196
Synthetic tissue environments	191
Navigating two-body challenges	189
SynNotch tuned for tension	186
Soil researchers dig deeper into dirt’s complexity	181
Deep learning identifies A-to-I RNA edits using nanopore sequencing data	181
Tamir Gonen	180
Modeling condensate formation in silico	180
A method to map single-cell lineages in the mouse brain by CRISPR-based barcoding	178
Nanopores distinguish RNA modifications	177
Ex utero synthetic embryos	170
How regulatory sequences learn cell representations	168
The chemistry of microbiome–host togetherness	164
Reporting T cell proliferation	164
Synthetic condensates probe chromatin viscoelasticity	155
Ringside seats to a pandemic	153
Adventures in AI	152
Analyzing submicron spatial transcriptomics data at their original resolution	152
Disentangling parallel processes with BEYOND	151
Accurate determination of molecular formulae using tandem mass spectrometry	151
Scientists set out to connect the dots on long COVID	151
Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape	151
A decade of neuroscience	151
Art appreciation	151
Recovery of missing single-cell RNA-sequencing data with optimized transcriptomic references	150
Deep brain imaging on the move	148
Sharpen SV detection	147
Conservation genomics in practice	147
Spatially resolved epigenomics	146
Orthology inference at scale with FastOMA	144
Capture of membrane proteins in their native membrane milieu	143
Efficiently accelerated bioimage analysis with NanoPyx, a Liquid Engine-powered Python framework	143
Generative modeling of genomes	142
Author Correction: Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision	142
3D holograms of embryos	139

Light-gated potassium channels from nature	138
Enhancing functional gene set analysis with large language models	138
Early-career navigation tips	137
A machine learning tool for spatial multi-omics	134
CellBender removes technical artifacts from single-cell RNA sequencing data	134
Profiling single molecules in solution	134
LLMs predict protein phases	134
Single-cell profiling of microbes	133
Extending the sensitivity, consistency and depth of single-cell proteomics	128
Author Correction: Single-cell chromatin state analysis with Signac	125
Maximum-likelihood model fitting for quantitative analysis of SMLM data	122
Towards foundation models of biological image segmentation	120
GelMap: intrinsic calibration and deformation mapping for expansion microscopy	120
Large models for genomics	117
Let’s talk about diversity in human neuroscience	117
Imaging without the labels	117
Advancing sequencing-based spatial transcriptomics with a comprehensive benchmarking study	117
Exoskeleton empowers large-scale neural recordings in freely roaming mice	116
Phasor S-FLIM: a new paradigm for fast and robust spectral fluorescence lifetime imaging	115
Miniaturized head-mounted microscope for whole-cortex mesoscale imaging in freely behaving mice	115
Toward learning a foundational representation of cells and genes	114
Cryo-electron tomography: observing the cell at the atomic level	110
Uncovering cell cycle speed modulations with statistical inference	110
Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single-cell resolution	109
Thermal-plex: fluidic-free, rapid sequential multiplexed imaging with DNA-encoded thermal channels	108
Detect-seq reveals out-of-protospacer editing and target-strand editing by cytosine base editors	107
Weighing single protein complexes on the go	107
MiLoPYP: self-supervised molecular pattern mining and particle localization in situ	107
Strainy: phasing and assembly of strain haplotypes from long-read metagenome sequencing	106
Accessible computing platforms democratize neuroimaging data analysis	106
The long and winding road of development: a coordinated song of transcription factors	105
A complete, telomere-to-telomere human genome sequence presents new opportunities for evolutionary genomics	102
Author Correction: A 4D single-cell protein atlas of transcription factors delineates spatiotemporal patterning during embryogenesis	102
Unlocking the power of spatial omics with AI	100
Identification of phosphosites that alter protein thermal stability	100
Editing naive CD4+ T cells	100
Systematic molecular evolution enables robust biomolecule discovery	99
SurfDock is a surface-informed diffusion generative model for reliable and accurate protein–ligand complex prediction	97
The Simularium Viewer: an interactive online tool for sharing spatiotemporal biological models	94
Expansion microscopy opens the door to exploring more challenges	94
CherryML: scalable maximum likelihood estimation of phylogenetic models	93
Line-scanning speeds up Brillouin microscopy	93
CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning	93
Time-resolved assessment of single-cell protein secretion by sequencing	93
Chromoscope: interactive multiscale visualization for structural variation in human genomes	92
Neural optimal transport predicts perturbation responses at the single-cell level	92
Fast and efficient template-mediated synthesis of genetic variants	91
Mapping morphogenesis and mechanics in embryo models	91
Flash entropy search to query all mass spectral libraries in real time	91
A systematic search for RNA structural switches across the human transcriptome	91
Unlocking human immune system complexity through AI	90
Dissecting gene regulation with multimodal sequencing	90
Spatial landmark detection and tissue registration with deep learning	89
RNA structure profiling at single-cell resolution reveals new determinants of cell identity	89
Author Correction: ‘Ceci n’est pas un embryon?’ The ethics of human embryo model research	89
Real-time multi-angle projection imaging of biological dynamics	88
Analysis of behavioral flow resolves latent phenotypes	87
DART.2: bidirectional synaptic pharmacology with thousandfold cellular specificity	87
Best practices for reporting throughput in biomedical research	87
CR-I-TASSER: assemble protein structures from cryo-EM density maps using deep convolutional neural networks	86
PyImageJ: A library for integrating ImageJ and Python	86
Fluorophores’ talk turns them dark	85
A general method for chemogenetic control of peptide function	83
Subcellular omics: a new frontier pushing the limits of resolution, complexity and throughput	83
Author Correction: Unsupervised discovery of tissue architecture in multiplexed imaging	83
Publisher Correction: Nascent Ribo-Seq measures ribosomal loading time and reveals kinetic impact on ribosome density	83
An analytical framework for interpretable and generalizable single-cell data analysis	82
SEAM is a spatial single nuclear metabolomics method for dissecting tissue microenvironment	82
Building a molecular reference map of the human embryo	81
Constructing and personalizing population pangenome graphs	81
Neural networks learn the motions of molecular machines	81
Considerations for building and using integrated single-cell atlases	81
iFlpMosaics enable the multispectral barcoding and high-throughput comparative analysis of mutant and wild-type cells	81
Moculus: an immersive virtual reality system for mice incorporating stereo vision	80
Large language modeling and deep learning shed light on RNA structure prediction	80
Anterograde transneuronal tracing and genetic control with engineered yellow fever vaccine YFV-17D	79
Fast and flexible analysis of linked microbiome data with mako	78
Elucidating subcellular architecture and dynamics at isotropic 100-nm resolution with 4Pi-SIM	78
How noncoding RNAs began to leave the junkyard	78
Reprogrammed anti-tumor NK cells	77

Author Correction: Points of view: Color blindness	76
HYBRiD: a simple method for clearing and visualizing mammalian bodies	76
More dimensions of the 3D genome	76
Publisher Correction: Towards resolving proteomes in single cells	76
Mario Nicodemi	76
LiMCA: Hi-C gets an RNA twist	75
Protein language models guide directed antibody evolution	75
A look back at embryo models	74
Interpreting and comparing neural activity across systems by geometric deep learning	74
ERnet: a tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology	74
Optimal transport for single-cell genomics	73
Author Correction: Arkitekt: streaming analysis and real-time workflows for microscopy	73
CRISPR inspirations from nature	72
Temporal analysis of relative distances (TARDIS) is a robust, parameter-free alternative to single-particle tracking	72
Simultaneous single-cell three-dimensional genome and gene expression profiling uncovers dynamic enhancer connectivity underlying olfactory receptor choice	71
DNA-PAINT MINFLUX nanoscopy	70
A fluorescent sensor for real-time measurement of extracellular oxytocin dynamics in the brain	70
Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain	69
SVision: a deep learning approach to resolve complex structural variants	69
Modeling fragment counts improves single-cell ATAC-seq analysis	68
Homotrimer barcodes enable accurate counting of RNA molecules during high-throughput RNA sequencing	68
Comprehensive spatiotemporal mapping of single-cell lineages in developing mouse brain by CRISPR-based barcoding	68
FlyWire: online community for whole-brain connectomics	68
Evaluation of large language models for discovery of gene set function	67
DeepMainmast: integrated protocol of protein structure modeling for cryo-EM with deep learning and structure prediction	67
Biophysical modeling with variational autoencoders for bimodal, single-cell RNA sequencing data	66
Unlocking gene regulation with sequence-to-function models	66
Pushing the limits of MRI brain imaging	66
Neural space–time model for dynamic multi-shot imaging	66
Best practices and tools for reporting reproducible fluorescence microscopy methods	65
High-throughput volumetric mapping of synaptic transmission	65
Spatially resolved isotope tracing reveals tissue metabolic activity	64
Local shape descriptors for neuron segmentation	63
Fast optical recording of neuronal activity by three-dimensional custom-access serial holography	63
Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation	63
High-resolution line-scan Brillouin microscopy for live imaging of mechanical properties during embryo development	62
Machine learning in rare disease	62
Improving the sensitivity of in vivo CRISPR off-target detection with DISCOVER-Seq+	62
Advances in measuring cancer cell metabolism with subcellular resolution	62
Genome-wide profiling of prime editor off-target sites in vitro and in vivo using PE-tag	62
Mass spectrometry imaging: the rise of spatially resolved single-cell omics	62
SpatialData: an open and universal data framework for spatial omics	61
Challenging the Astral mass analyzer to quantify up to 5,300 proteins per single cell at unseen accuracy to uncover cellular heterogeneity	61
Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments	60
Integration of mass cytometry and mass spectrometry imaging for spatially resolved single-cell metabolic profiling	60
Phasor plots and the future of spectral and lifetime imaging	60
The end game: respecting major sources of population diversity	59
Unlocking capacities of genomics for the COVID-19 response and future pandemics	59
Convolutional networks for supervised mining of molecular patterns within cellular context	58
Detecting and correcting false transients in calcium imaging	58
Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges	56
Advances and opportunities in RNA structure experimental determination and computational modeling	56
SCITO-seq: single-cell combinatorial indexed cytometry sequencing	56
CellRank 2: unified fate mapping in multiview single-cell data	55
Precision size and refractive index analysis of weakly scattering nanoparticles in polydispersions	55
Context-aware transcript quantification from long-read RNA-seq data with Bambu	55
LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals	55
SCUBA-D: a freshly trained diffusion model generates high-quality protein structures	54
Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering	54
Fast and robust metagenomic sequence comparison through sparse chaining with skani	54
TomoTwin: generalized 3D localization of macromolecules in cryo-electron tomograms with structural data mining	54
Denoising Search doubles the number of metabolite and exposome annotations in human plasma using an Orbitrap Astral mass spectrometer	54
Automated segmentation and tracking of mitochondria in live-cell time-lapse images	54
Bright and stable monomeric green fluorescent protein derived from StayGold	53
The triumphs and limitations of computational methods for scRNA-seq	53
Deep learning-enhanced light-field imaging with continuous validation	53
Large Stokes shift fluorescent RNAs for dual-emission fluorescence and bioluminescence imaging in live cells	53
Spatiotemporal, optogenetic control of gene expression in organoids	53
Efficient targeted insertion of large DNA fragments without DNA donors	52
Fatigue-resistant hydrogel optical fibers enable peripheral nerve optogenetics during locomotion	52
Screening cell–cell communication in spatial transcriptomics via collective optimal transport	52
Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library	52
Cell type-specific inference of differential expression in spatial transcriptomics	52
Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics	51
OpenMS 3 enables reproducible analysis of large-scale mass spectrometry data	51
SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks	51
MSNovelist: de novo structure generation from mass spectra	51
Sharing data from the Human Tumor Atlas Network through standards, infrastructure and community engagement	51
Challenges in benchmarking metagenomic profilers	50
Streamlined and sensitive mono- and di-ribosome profiling in yeast and human cells	49
Personalized pangenome references	49
BIONIC: biological network integration using convolutions	49
Survival analysis—time-to-event data and censoring	49
MARBLE: interpretable representations of neural population dynamics using geometric deep learning	49
Antibody stabilization for thermally accelerated deep immunostaining	49
Ultralong transients enhance sensitivity and resolution in Orbitrap-based single-ion mass spectrometry	48
Unsupervised discovery of tissue architecture in multiplexed imaging	48
Understanding the invisible hands of sample preparation for cryo-EM	48
Robust single-cell matching and multimodal analysis using shared and distinct features	48
Serial lift-out for in situ structural biology of multicellular specimens	48
Method of the year: long-read sequencing	48
Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments	48
Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes	48
Museum of spatial transcriptomics	48
Spatial omics and multiplexed imaging to explore cancer biology	47