Nature Methods最新文献_第6页

Their personal paths in science. 他们在科学上的个人道路。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02716-0

Vivien Marx

引用次数: 0

Guinea pigs as embryo models. 豚鼠作为胚胎模型。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02733-z

Madhura Mukhopadhyay

引用次数: 0

Intracellular protein editing. 细胞内蛋白编辑。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02734-y

Arunima Singh

引用次数: 0

Knowing when to fold 'em. 知道什么时候该收手。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02722-2

Michael Eisenstein

引用次数: 0

FISHnet: detecting chromatin domains in single-cell sequential Oligopaints imaging data. 渔网：检测单细胞序列寡聚颜料成像数据中的染色质结构域。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-12 DOI: 10.1038/s41592-025-02688-1

Rohan Patel, Kenneth Pham, Harshini Chandrashekar, Jennifer E Phillips-Cremins

{"title":"FISHnet: detecting chromatin domains in single-cell sequential Oligopaints imaging data.","authors":"Rohan Patel, Kenneth Pham, Harshini Chandrashekar, Jennifer E Phillips-Cremins","doi":"10.1038/s41592-025-02688-1","DOIUrl":"10.1038/s41592-025-02688-1","url":null,"abstract":"Sequential Oligopaints DNA FISH is an imaging technique that measures higher-order genome folding at single-allele resolution via multiplexed, probe-based tracing. Currently there is a paucity of algorithms to identify 3D genome features in sequential Oligopaints data. Here, we present FISHnet, a graph theory method based on optimization of network modularity to detect chromatin domains in pairwise distance matrices. FISHnet sensitively and specifically identifies domains and boundaries in both simulated and real single-allele imaging data and provides statistical tests for the identification of cell-type-specific domains-like folding patterns. Application of FISHnet across multiple published Oligopaints datasets confirms that nested domains consistent with TADs and subTADs are not an emergent property of ensemble Hi-C data but also observable on single alleles. We make FISHnet code freely available to the scientific community, thus enabling future studies aiming to elucidate the role of single-allele folding variation on genome function.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1255-1264"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144019789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computer vision for primate behavior analysis in the wild. 野外灵长类动物行为分析的计算机视觉。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-04-10 DOI: 10.1038/s41592-025-02653-y

Richard Vogg, Timo Lüddecke, Jonathan Henrich, Sharmita Dey, Matthias Nuske, Valentin Hassler, Derek Murphy, Julia Fischer, Julia Ostner, Oliver Schülke, Peter M Kappeler, Claudia Fichtel, Alexander Gail, Stefan Treue, Hansjörg Scherberger, Florentin Wörgötter, Alexander S Ecker

{"title":"Computer vision for primate behavior analysis in the wild.","authors":"Richard Vogg, Timo Lüddecke, Jonathan Henrich, Sharmita Dey, Matthias Nuske, Valentin Hassler, Derek Murphy, Julia Fischer, Julia Ostner, Oliver Schülke, Peter M Kappeler, Claudia Fichtel, Alexander Gail, Stefan Treue, Hansjörg Scherberger, Florentin Wörgötter, Alexander S Ecker","doi":"10.1038/s41592-025-02653-y","DOIUrl":"10.1038/s41592-025-02653-y","url":null,"abstract":"Advances in computer vision and increasingly widespread video-based behavioral monitoring are currently transforming how we study animal behavior. However, there is still a gap between the prospects and practical application, especially in videos from the wild. In this Perspective, we aim to present the capabilities of current methods for behavioral analysis, while at the same time highlighting unsolved computer vision problems that are relevant to the study of animal behavior. We survey state-of-the-art methods for computer vision problems relevant to the video-based study of individualized animal behavior, including object detection, multi-animal tracking, individual identification and (inter)action understanding. We then review methods for effort-efficient learning, one of the challenges from a practical perspective. In our outlook on the emerging field of computer vision for animal behavior, we argue that the field should develop approaches to unify detection, tracking, identification and (inter)action understanding in a single, video-based framework.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1154-1166"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144030569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A palette of bridged bicycle-strengthened fluorophores. 一组桥接的自行车强化荧光团。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-19 DOI: 10.1038/s41592-025-02693-4

Junwei Zhang, Kecheng Zhang, Kui Wang, Bo Wang, Siyan Zhu, Hongping Qian, Yumiao Ma, Mengling Zhang, Tianyan Liu, Peng Chen, Yuan Shen, Yunzhe Fu, Shilin Fang, Xinxin Zhang, Peng Zou, Wulan Deng, Yu Mu, Zhixing Chen

{"title":"A palette of bridged bicycle-strengthened fluorophores.","authors":"Junwei Zhang, Kecheng Zhang, Kui Wang, Bo Wang, Siyan Zhu, Hongping Qian, Yumiao Ma, Mengling Zhang, Tianyan Liu, Peng Chen, Yuan Shen, Yunzhe Fu, Shilin Fang, Xinxin Zhang, Peng Zou, Wulan Deng, Yu Mu, Zhixing Chen","doi":"10.1038/s41592-025-02693-4","DOIUrl":"10.1038/s41592-025-02693-4","url":null,"abstract":"Organic fluorophores are the keystone of advanced biological imaging. The vast chemical space of fluorophores has been extensively explored in search of molecules with ideal properties. However, within the current molecular constraints, there appears to be a trade-off between high brightness, robust photostability, and tunable biochemical properties. Herein we report a general strategy to systematically boost the performance of donor-acceptor-type fluorophores, such as rhodamines, by leveraging SO2 and O-substituted azabicyclo[3.2.1] octane auxochromes. These bicyclic heterocycles give rise to a collection of 'bridged' dyes (BD) spanning the ultraviolet and visible range with top-notch quantum efficiencies, enhanced water solubility, and tunable cell-permeability. Notably, these azabicyclic fluorophores showed remarkable photostability compared to their tetramethyl or azetidine analogs while being completely resistant to oxidative photoblueing. Functionalized BD dyes are tailored for applications in single-molecule imaging, super-resolution imaging (STED and SIM) in fixed or live mammalian and plant cells, and live zebrafish imaging and chemogenetic voltage imaging.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1276-1287"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144102262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single-cell foundation models evaluated. 评估单细胞地基模型。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02735-x

Lin Tang

引用次数: 0

NeuroXiv: AI-powered open databasing and dynamic mining of brain-wide neuron morphometry. NeuroXiv：人工智能驱动的全脑神经元形态开放数据库和动态挖掘。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-04-29 DOI: 10.1038/s41592-025-02687-2

Shengdian Jiang, Lijun Wang, Zhixi Yun, Hanbo Chen, Lijuan Liu, Jianhua Yao, Hanchuan Peng

引用次数: 0

Ultrafast and accurate sequence alignment and clustering of viral genomes. 病毒基因组的超快速精确序列比对和聚类。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-15 DOI: 10.1038/s41592-025-02701-7

Andrzej Zielezinski, Adam Gudyś, Jakub Barylski, Krzysztof Siminski, Piotr Rozwalak, Bas E Dutilh, Sebastian Deorowicz

引用次数: 0