24 papers · ranked by Valyu relevance
Linlin Zhang, Dongsheng Chen, Dongli Song, Xiaoxia Liu + 3 more
'Xun Xu' 'Xiangdong Wang'] The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) acts as a pivotal component to bridge the pathological phenomes of human tissues with molecular alterations, defining in situ intercellular molecular communications and knowledge on spatiotemporal…
Boxiang Liu, Yanjun Li, Liang Zhang
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation…
Xiaoxia Liu, Yujia Jiang, Dongli Song, Linlin Zhang + 12 more
'Rui Hou' 'Yong Zhang' 'Jian Chen' 'Yunfeng Cheng' 'Longqi Liu' 'Xun Xu' 'Gang Chen' 'Duojiao Wu' 'Tianxiang Chen' 'Ao Chen' 'Xiangdong Wang'] Title: Abstract Spatial transcriptomics is considered as an important part of spatiotemporal molecular images to bridge molecular information with clinical images. Of those…
Boxiang Liu, Yanjun Li, Liang Zhang
Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of spatial information. Spatial transcriptomics is a recent technological innovation…
David W. McKellar, Madhav Mantri, Meleana Hinchman, John S.L. Parker + 3 more
Spatial transcriptomics reveals the spatial context of gene expression, but current methods are limited to assaying polyadenylated (A-tailed) RNA transcripts. Here we demonstrate that enzymatic in situ polyadenylation of RNA enables detection of the full spectrum of RNAs, expanding the scope of sequencing-based spatial…
Dario Righelli, Lukas M Weber, Helena L Crowell, Brenda Pardo + 6 more
Spatially-resolved transcriptomics (SRT) refers to a new set of high-throughput technologies, which measure up to transcriptome-wide gene expression along with the spatial coordinates of the measurements. Technological platforms differ in terms of the number of measured genes (from hundreds to full transcriptome) and…
Jun Du, Yu-Chen Yang, Zhi-Jie An, Ming-Hui Zhang + 4 more
'Zou-Fang Huang' 'Ye Yuan' 'Jian Hou'] Spatial transcriptomics technologies developed in recent years can provide various information including tissue heterogeneity, which is fundamental in biological and medical research, and have been making significant breakthroughs. Single-cell RNA sequencing (scRNA-seq) cannot…
Zhiwei Fan, Yangyang Luo, Huifen Lu, Tiangang Wang + 4 more
'Weiling Zhao' 'Pora Kim' 'Xiaobo Zhou'] Title: Abstract In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location…
Guoxin Cai, Yichang Chen, Xun Gu, Zhan Zhou
Spatial transcriptomics enables the depiction of in situ gene expression and could further be applied to infer the mechanism of cell functions. In this study, we present Spanve (Spatial Neighborhood Variably Expressed Genes), a statistic based approach to detect space-dependent expressed genes from spatial…
Eleftherios Zormpas, Nikolaos I. Vlachogiannis, Anastasia Resteu, Adrienne Unsworth + 9 more
Spatial transcriptomics (ST) has the potential to provide unprecedented insights into gene expression across tissue architecture, but existing analytical methods often overlook the full complexity of the spatial dimension. We present STExplorer, an R package that adapts well-established computational geography (CG)…
Chase Holdener, Shaowen Jiang, Danica M. Sutherland, Kira A. Griswold + 3 more
The morbidity and mortality associated with viral diseases in plants, animals, and humans are significant concerns. Understanding how viruses cause disease and identifying the viral and host factors that determine the outcome of infection are essential to develop new antiviral therapeutics and strategies to induce…
Yingying Lu, Qin Chen, Lingling An
The advent of spatial transcriptomics technology has allowed for the acquisition of gene expression profiles with multi-cellular resolution in a spatially resolved manner, presenting a new milestone in the field of genomics. However, the aggregate gene expression from heterogeneous cell types obtained by these…
Chao Zhang, Renchao Chen, Yi Zhang
Spatially resolved transcriptomic analyses can reveal molecular insights underlying tissue structure and context-dependent cell-cell or cell-environment interaction. Due to the current technical limitation, obtaining genome-wide spatial transcriptome at single-cell resolution is challenging. Here we developed a new…
Uthsav Chitra, Brian J. Arnold, Hirak Sarkar, Cong Ma + 3 more
Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of this data complicates the analysis of spatial gene expression patterns such as gene expression gradients. We address these issues by deriving a topographic map of a tissue…
Linbu Liao, Esha Madan, António M. Palma, Hyobin Kim + 10 more
'Praveen Bhoopathi' 'Robert Winn' 'Jose Trevino' 'Paul Fisher' 'Cord Herbert Brakebusch' 'Gahyun Kim' 'Junil Kim' 'Rajan Gogna' 'Kyoung Jae Won'] Background Understanding cellular heterogeneity within tissues hinges on knowledge of their spatial context. However, it is still challenging to accurately map cells to their…
Zhiwei Fan, Tiangang Wang, Kexin Huang, Binwu Ying + 1 more
Recent advances in spatial omics technologies have revolutionized our ability to study biological systems with unprecedented resolution. By preserving the spatial context of molecular measurements, these methods enable comprehensive mapping of cellular heterogeneity, tissue architecture, and dynamic biological…
Mengwei Hu, Yi Cui, Qianhui Huang, Khoi Chu + 18 more
Current spatial CRISPR screening technologies are limited by targeted readouts and high costs, restricting the scope of biological discovery. Here we present SPAtial Cell Exploration (SPACE), a spatial CRISPR screening platform that integrates whole-transcriptome profiling (∼18,000 genes), multiplexed protein detection…
Xiaoyu Li, Fangfang Zhu, Wenwen Min
using scRNA-seq Authors: ['Xiaoyu Li' 'Fangfang Zhu' 'Wenwen Min'] The rapid development of spatial transcriptomics (ST) technologies is revolutionizing our understanding of the spatial organization of biological tissues. Current ST methods, categorized into next-generation sequencing-based (seq-based) and fluorescence…
Guanao Yan, Shuo Harper Hua, Jingyi Jessica Li
In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 31 state-of-the-art methods, categorizing SVGs into three types: overall…
Bencong Zhu, Guanyu Hu, Yang Xie, Lin Xu + 2 more
Department of Statistics, The Chinese University of Hong Kong Guanyu Hu Department of Biostatistics and Data Science and Center for Spatial Temporal Modeling for Applications in Population Sciences, The University of Texas Health Science Center at Houston Yang Xie Peter O'Donnell Jr. School of Public Health, The…
Katharina Limbeck, Bastian Rieck
Persistence Diagrams Authors: ['Katharina Limbeck' 'Bastian Rieck'] Evaluating spatial patterns in data is an integral task across various domains, including geostatistics, astronomy, and spatial tissue biology. The analysis of transcriptomics data in particular relies on methods for detecting spatially-dependent…
Esra Busra Isik, Yusuf Hakan Usta, Haozhe Liu, Maryam Riazi + 4 more
Recent developments in spatial omics technologies have enabled the generation of high dimensional molecular data, such as transcriptomes, proteomes, and epigenomes, within their spatial tissue context, either through cocprofiling on the same slice or through serial tissue sections. These datasets, which are often…
Authors not listed
Understanding how plants respond to dynamic and spatially variable stimuli is a key goal in plant sciences. Traditional imaging methods often involve a trade-off between environmental control and spatial resolution, limiting their ability to capture real-time responses in high resolution. Microfluidic technology…
Authors not listed
Genetically encoded covalent warheads at the protein-protein interface, enable the locking of interaction from the transient complex into a stable covalent adduct, which could improve the binding affinity, selectivity, and kinetics between a protein binder and its target. Given the diverse chemical microenvironments…