NATURE METHODS自然-方法
NATURE METHODS(英文缩写 NAT METHODS),ISSN 1548-7091,eISSN 1548-7105,中文译名:自然-方法 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-27 至 2026-09-27，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 47.990 | Q1 |
| 2022 | 48.000 | Q1 |
| 2023 | 36.100 | Q1 |
| 2024 | 32.100 | Q1 |
| 2025 | 28.300 | Q1 |
NATURE METHODS 最新收录文献
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1. Solid-state nanopore sensing: the next workhorse of biophysical characterization.
PMID:日期:2026-09-24Nanopore sequencing has entered the mainstream, with DNA and RNA sequencing now possible on portable, user-friendly devices. In the wake of these successes, the attention of the nanopore community has turned toward the challenge of de novo protein sequencing. Biological nanopores are primed to take on this task and have thus taken center stage. Here we draw focus back toward solid-state nanopores. We argue that these size-tunable and easily functionalized pores are key to studying the macromolecular superstructures inherent to natural and synthetic biochemical systems. While sequencing is undoubtedly a worthy goal, we advocate for the use of nanopores in new applications, toward understanding the supramolecular chemistry at the heart of biology and beyond. With ongoing improvements in hardware, nanopore functionalization and experimental design, new avenues for nanopore sensing are continually arising. Looking forward, we anticipate opportunities for solid-state nanopores in drug screening, protein engineering and synthetic self-assembled systems.
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2. ResolVI: addressing noise and bias in spatial transcriptomics.
PMID:日期:2026-09-24Technologies for estimating RNA expression at high throughput, in intact tissue slices and with high spatial resolution (spatial transcriptomics) shed new light on how cells communicate and tissues function. A fundamental step in analyzing data generated by subcellular resolution spatial transcriptomics technologies is quantification, namely, segmenting the plane into regions, each approximating a cell, and then collating the molecules inside each region to estimate the cellular expression profile. Despite many advances in this area, a persistent problem is that of the incorrect assignment of molecules to cells, which limits many current applications to the level of a priori-defined cell subsets and complicates the discovery of novel cell states. Here we develop resolVI, a model that operates downstream of any segmentation algorithm to generate a probabilistic representation, correcting for the misassignment of molecules, as well as for batch effects and other nuisance factors. We demonstrate that resolVI improves our ability to distinguish between cell states, identify subtle expression changes in space and perform integrated analysis across datasets. ResolVI is available as open source software within scvi-tools.
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3. NanoTS: a deep learning tool for accurate SNP calling in nanopore long-read transcriptome data.
PMID:日期:2026-09-22Accurate variant detection using nanopore long-read transcriptome data remains challenging. Here we present NanoTS-a deep learning-based tool for single nucleotide polymorphism detection from diverse types of nanopore transcriptome sequencing data. NanoTS outperforms existing methods, achieving F scores above 0.980 and 0.966 on nanopore direct RNA and cDNA sequencing data, respectively, for single nucleotide polymorphisms with at least five supporting reads. Notably, NanoTS shows strong improvements over existing methods for allelically imbalanced variants. We also demonstrate that NanoTS enables accurate detection and genotype calling of pathogenic variants underlying Mendelian disorders, highlighting its potential clinical utility.
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4. SVPG: a pangenome-based structural variant detection approach and rapid augmentation of pangenome graphs with new samples.
PMID:日期:2026-09-21Breakthrough advances in long-read sequencing have opened unprecedented opportunities to study genetic variations through pangenome analysis, yet tools that effectively leverage such frameworks for structural variant (SV) detection remain limited. In addition, efficient construction of pangenome graphs becomes increasingly challenging with the acquisition of larger numbers of samples. Here we present SVPG, an approach that leverages haplotype-resolved pangenome reference for accurate SV detection and rapid pangenome graph augmentation from long-read sequencing data. Compared with state-of-the-art SV callers, SVPG maintained superior overall performance across different sequencing technologies and coverages. SVPG also achieved notable improvements in calling individual-specific SVs, including rare and somatic SVs. Furthermore, in a benchmark involving 20 samples, SVPG accelerated pangenome graph augmentation by nearly tenfold compared with traditional augmentation strategies. These results indicate that SVPG has the potential to improve SV detection and serve as an effective tool, offering new possibilities for advancing pangenomic research.
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7. CFM: confinement force microscopy-a dynamic, precise and stable microconfiner for traction force microscopy in spatial confinement.
PMID:日期:2026-09-14Cells migrating through tissues experience changing physical confinement, yet methods to dynamically control confinement while quantifying the resulting forces remain limited. Here we present a microconfiner platform for live-cell imaging that enables programmable confinement, allowing real-time control over the level, timing and frequency of confinement while measuring traction forces exerted on the microenvironment, a method we term confinement force microscopy (CFM). Using CFM, we find that cells respond to confinement in two phases: a rapid passive stress rise caused by compression of the cell body and nucleus against the substrate, followed by an active stress increase associated with enhanced contractility, intracellular pressure buildup and bleb formation. Bleb expansion can partially relieve pressure and reduce stress on the surroundings. ROCK and myosin II inhibition both reduce stress generation, but with distinct effects on blebbing. Overall, CFM provides a versatile approach to study dynamic mechanical adaptation in tissue-like environments.
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8. SPLENDID incorporates continuous genetic ancestry in biobank-scale data to improve polygenic risk prediction across diverse populations.
PMID:日期:2026-09-14Polygenic risk scores are widely used in disease risk stratification, but their accuracy varies across different ancestries. Recent methods leverage multi-ancestry data to improve accuracy in under-represented populations but require the labeling of individuals by ancestry. This poses practical challenges, given that clinical decisions are typically not based on ancestry, and many individuals may not fit into a pre-specified ancestry group. Here we propose SPLENDID, a penalized regression framework for large-scale individual-level data that models genetic ancestry as a continuum to produce a single prediction model without any ancestry labels. In extensive simulations and analyses in the All of Us Research Program (n = 224,364) and UK Biobank (n = 340,140), we show that SPLENDID significantly improved prediction accuracy over existing methods, particularly for non-European and admixed ancestries. SPLENDID stands as a valuable tool for robust risk prediction across diverse populations, reduced health disparities in genetic research, and fairer clinical implementation.
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9. An ultralow-background far-red light-responsive optogenetic tool based on an engineered biliverdin-binding domain.
PMID:日期:2026-09-11The robustness and broad applicability of an optogenetic tool depends heavily on the properties of the underlying photoreceptor protein and its cognate binding partner-the light-responsive 'core'. Current red light optogenetic systems for mammalian cells rely on phytochrome-based photoreceptors: large (70-kDa) proteins that act as dimers, enforcing dimerization on attached proteins. Naturally occurring or engineered binding partners can function effectively, but large size, complex interaction, background binding, weak affinity and modest dynamic range remain limiting. Here we developed a small (17-kDa) monomeric biliverdin-binding photoreceptor, FenixS, and a highly selective, high-affinity binder, Ash1 (6 kDa) using structure-based design and directed evolution. Negligible OFF-state binding and a >1,200-fold increase in binding affinity upon 700-nm illumination yield a high-performance, ultralow background core for diverse applications. A FenixS-Ash1-based optogenetic tool for red light activation of transcription in mammalian cells performs robustly without biliverdin supplementation, with head-to-head comparisons confirming its control of gene expression versus established tools.
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10. Wireless neural recordings from groups of mice inside and outside the laboratory.
PMID:日期:2026-09-10该文献暂无摘要。