15 papers · ranked by Valyu relevance
Jiayu Su, Jean-Baptiste Reynier, Xi Fu, Guojie Zhong + 7 more
'Rydberg Supo Escalante' 'Yiping Wang' 'Luis Aparicio' 'Benjamin Izar' 'David A. Knowles' 'Raul Rabadan'] Spatial omics technologies can help identify spatially organized biological processes, but existing computational approaches often overlook structural dependencies in the data. Here, we introduce Smoother, a…
Chia-Hsien Lin, Tzai-Hung Wen, Peter A. Leggat, John Frean
Both directly and indirectly transmitted infectious diseases in humans are spatial-related. Spatial dimensions include: distances between susceptible humans and the environments shared by people, contaminated materials, and infectious animal species. Therefore, spatial concepts in managing and understanding emerging…
Linglin Ni, Xiaokun (Cara) Wang, Xiqun (Michael) Chen, Dapeng Zhang + 1 more
'Xiaoqiang ‘Jack’ Kong'] This paper proposes a random-effect spatial OD (origin-destination) dependence model to investigate varying trip distributions over time. By proposing a maximum likelihood estimation with spectral decomposition methods, the effects of spatial dependences and the unobservable zonal heterogeneity…
Emiko Dupont, Simon N. Wood, Nicole H. Augustin
In spatial regression models, collinearity between covariates and spatial effects can lead to significant bias in effect estimates. This problem, known as spatial confounding, is encountered modeling forestry data to assess the effect of temperature on tree health. Reliable inference is difficult as results depend on…
Chichun Tan, Ying Ma
The rapid advancement of spatially resolved transcriptomics (SRT) technology enables gene expression profiling across tissue locations while preserving spatial context. Gene co-expression analysis in SRT data provides critical insights into how genes function together within the tissue microenvironment. However…
Jing Zhao, Yue Pu, Mohamed R. Abonazel
Spatial Autoregressive (SAR) models are widely used to analyze interactions among regions. However, the traditional model assumes a constant spatial autocorrelation coefficient, which fails to effectively capture spatial heterogeneity. To address this issue, we propose proposes a novel Spatial Single-Index Varying…
Takahiro Yabe, Bernardo García Bulle Bueno, Morgan R. Frank, Alex Pentland + 1 more
'Alex Pentland' 'Esteban Moro'] Disruptions, such as closures of businesses during pandemics, not only affect businesses and amenities directly but also influence how people move, spreading the impact to other businesses and increasing the overall economic shock. However, it is unclear how much businesses depend on…
Zhibo Xing, Mingxia Huang, Wentao Li, Dan Peng
Accurately obtaining accurate information about the future traffic flow of all roads in the transportation network is essential for traffic management and control applications. In order to address the challenges of acquiring dynamic global spatial correlations between transportation links and modeling time dependencies…
Daniel A. Griffith, Paul B. Tchounwou, William A. Toscano
This opinion piece postulates that quantitative environmental research and public health spatial analysts unknowingly tolerate certain spatial statistical model specification errors, whose remedies constitute some of the urgent emerging trends and issues in this subfield (e.g., forecasting disease spreading). Within…
Jiaxin Han, Yudong Miao, Zhanlei Shen, Jingbao Zhang + 14 more
Background Cognitive impairment is frequent but often overlooked among elderly hypertensive individuals in rural settings. Existing studies have predominantly relied on global statistical models that assume uniform effects across space, failing to capture geographic heterogeneity in risk factor mechanisms and limiting…
Lei Zhang, Shu Liang, Lin Wan
Spatially resolved transcriptomics data are being used in a revolutionary way to decipher the spatial pattern of gene expression and the spatial architecture of cell types. Much work has been done to exploit the genomic spatial architectures of cells. Such work is based on the common assumption that gene expression…
Pau Satorra, Cristian Tebé
In this study, we modelled the incidence of COVID-19 cases and hospitalisations by basic health areas (ABS) in Catalonia. Spatial, temporal and spatio-temporal incidence trends were described using estimation methods that allow to borrow strength from neighbouring areas and time points. Specifically, we used Bayesian…
Holger Engleitner, Ashwani Jha, Marta Suarez Pinilla, Amy Nelson + 5 more
'Daniel Herron' 'Geraint Rees' 'Karl Friston' 'Martin Rossor' 'Parashkev Nachev'] Title: Summary The characteristics and determinants of health and disease are often organized in space, reflecting our spatially extended nature. Understanding the influence of such factors requires models capable of capturing spatial…
Fangyi Wang, Xinyi Xu, Elizabeth Ghias, Stephen J Mooney + 10 more
Background Neighborhood disinvestment, characterized by built environment disrepair and deterioration, has been linked to health behaviors and outcomes, including cancer survival. However, disinvestment temporal dynamics, including time-lagged exposure estimates among colorectal cancer (CRC) cases, remain…
Xin Lyu, Yanling Li, Yuming Tai
The equitable allocation of public service facilities is a key issue in regional coordinated development; however, the long-term spatiotemporal dynamics of their spatial distribution and interregional interaction mechanisms remain underexplored. Based on point-of-interest (POI) data from 13 prefecture-level cities in…