Nature computational science最新文献_第2页

CellART: a unified framework for extracting single-cell information from high-resolution spatial transcriptomics. CellART：从高分辨率空间转录组学中提取单细胞信息的统一框架。

IF 20.3

Nature computational science Pub Date : 2026-10-05 DOI: 10.1038/s43588-026-01054-1

Yuheng Chen, Yuyao Liu, Zhiwei Wang, Yeqin Zeng, Zitong Chao, Peiqi Jiang, Hao Chen, Jiguang Wang, Jiashun Xiao, Can Yang

引用次数: 0

Modulatability of complex oscillators. 复振荡器的可调性。

IF 20.3

Nature computational science Pub Date : 2026-10-01 DOI: 10.1038/s43588-026-01050-5

Yutong Cai, Zhaoyue Zhong, Zefeng Zhang, Bo-Wei Qin, Wei Lin

{"title":"Modulatability of complex oscillators.","authors":"Yutong Cai, Zhaoyue Zhong, Zefeng Zhang, Bo-Wei Qin, Wei Lin","doi":"10.1038/s43588-026-01050-5","DOIUrl":"https://doi.org/10.1038/s43588-026-01050-5","url":null,"abstract":"<p><p>Modulating complex oscillators toward simultaneous multiple spatiotemporal properties is essential for sustaining systems' functionalities. Statistical and dynamical-systems approaches have yielded much progress. However, a comprehensive understanding of modulatability problems, namely, existence and uniqueness of modulation parameters targeting desired properties, remains elusive and challenging. An integrative and efficient framework for identifying those parameters concerning as many properties as possible is also lacking. Here we establish rigorous analyses of modulatability showing that its local-uniqueness condition is generally the equal dimension of parameters and properties. It helps us develop a framework for identifying parameters as a property-based inverse problem, providing an alternative perspective to those trajectory-based methods. The efficacy of the framework is validated across various systems including electronic analogs of genetic circuits. In data-driven demonstrations, our framework achieves less runtime and higher accuracy compared with baseline methods. This work therefore provides rigorous analyses in modulating complex oscillators. Our framework is also a useful tool for future computational and experimental studies.</p>","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":" ","pages":""},"PeriodicalIF":20.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards a chemistry genome. 走向化学基因组。

IF 20.3

Nature computational science Pub Date : 2026-09-30 DOI: 10.1038/s43588-026-01059-w

Thomas Bligaard, Benjamin Thomas Hinrichsen

引用次数: 0

Learning brain folds from simpler shapes. 从简单的形状学习大脑褶皱。

IF 20.3

Nature computational science Pub Date : 2026-09-25 DOI: 10.1038/s43588-026-01056-z

Yue Zheng

引用次数: 0

Intuitive enzyme design with LLM agents. 直观的酶设计与LLM代理。

IF 20.3

Nature computational science Pub Date : 2026-09-22 DOI: 10.1038/s43588-026-01052-3

Terra Sztain

引用次数: 0

Reproducibility in the era of large language models 大语言模型时代的再现性

IF 20.3

Nature computational science Pub Date : 2026-09-22 DOI: 10.1038/s43588-026-01061-2

引用次数: 0

Computational active materials and embodied intelligence in extreme conditions 极端条件下的计算活性材料和具身智能

IF 20.3

Nature computational science Pub Date : 2026-09-22 DOI: 10.1038/s43588-026-01051-4

Yifan Yang, Fan Xu

引用次数: 0

Algorithmic systems, human agency and the future of platform research 算法系统，人类代理和平台研究的未来

IF 20.3

Nature computational science Pub Date : 2026-09-21 DOI: 10.1038/s43588-026-01038-1

Homa Hosseinmardi, Upasana Dutta, David Rothschild, Duncan J. Watts

{"title":"Algorithmic systems, human agency and the future of platform research","authors":"Homa Hosseinmardi, Upasana Dutta, David Rothschild, Duncan J. Watts","doi":"10.1038/s43588-026-01038-1","DOIUrl":"10.1038/s43588-026-01038-1","url":null,"abstract":"As the volume of online content grows exponentially, algorithmic curation has become necessary for delivering content to billions of users daily, such as via recommendation and ranking algorithms. However, there are widespread concerns that these algorithms amplify problematic content or prioritize content that reinforces users’ existing beliefs. Although legitimate, these concerns have overshadowed the role that users’ own preferences play in determining these same outcomes. Here we argue for a more balanced approach to understanding online content consumption and engagement that considers both algorithmic mechanisms and human agency. We review the existing literature on the role of algorithmic recommendation and users’ self-selection in the patterns of users’ online diets and show that evidence linking algorithmic curation to problematic outcomes is inconclusive. We highlight the gaps in the existing literature and call for the need for more large-scale data-driven empirical research and experimentation, with the goal of refining the debate on the societal impact of digital platforms and providing a path for future research. While there are widespread concerns about the potential negative societal impacts of algorithm-driven systems, a more balanced approach to understanding online content consumption and engagement that considers both algorithmic mechanisms and human agency will be crucial moving forward.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"6 9","pages":"923-938"},"PeriodicalIF":20.3,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149014819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large language models as human proxies. 作为人类代理的大型语言模型。

IF 20.3

Nature computational science Pub Date : 2026-09-18 DOI: 10.1038/s43588-026-01060-3

Nikita Karetnikov, Iyad Rahwan, Davor Svetinovic

引用次数: 0

Revisiting molecular descriptors with TDiMS for interpretable intramolecular interactions based on substructure pairs 基于子结构对的可解释分子内相互作用用TDiMS重新审视分子描述符。

IF 20.3

Nature computational science Pub Date : 2026-09-17 DOI: 10.1038/s43588-026-01036-3

Lisa Hamada, Akihiro Kishimoto, Kohei Miyaguchi, Masataka Hirose, Junta Fuchiwaki, Indra Priyadarsini, Seiji Takeda

{"title":"Revisiting molecular descriptors with TDiMS for interpretable intramolecular interactions based on substructure pairs","authors":"Lisa Hamada, Akihiro Kishimoto, Kohei Miyaguchi, Masataka Hirose, Junta Fuchiwaki, Indra Priyadarsini, Seiji Takeda","doi":"10.1038/s43588-026-01036-3","DOIUrl":"10.1038/s43588-026-01036-3","url":null,"abstract":"Molecular descriptors play a crucial role in representing the structural features of molecules for machine learning-based physical property prediction. However, current descriptors either consider only local aspects of molecular structures or fail to effectively learn nonlocal structural features involving long-distance intramolecular interactions. Here, to address this issue, we present a descriptor named TDiMS. TDiMS effectively summarizes the enumerated pairwise topological distances between molecular substructures, thus capturing nonlocal interactions. Our evaluation shows that TDiMS successfully identifies essential features of large structures and outperforms other representative descriptors in predicting properties for which distances between substructures are a primary factor. In addition, these identified features are highly interpretable for experts in materials discovery. A descriptor, TDiMS, is developed to summarize the enumerated pairwise topological distances between molecular substructures and identify interpretable molecular features for materials discovery.","PeriodicalId":74246,"journal":{"name":"Nature computational science","volume":"6 9","pages":"945-953"},"PeriodicalIF":20.3,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s43588-026-01036-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148993005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0