25 papers · ranked by Valyu relevance
Cameron G. Williams, Hyun Jae Lee, Takahiro Asatsuma, Roser Vento-Tormo + 1 more
'Roser Vento-Tormo' 'Ashraful Haque'] Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over the past decade, particularly in developmental biology, cancer, immunology, and neuroscience. Most commercially available scRNA-seq protocols require cells to be recovered intact and viable…
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…
Benjamin L. Walker, Zixuan Cang, Honglei Ren, Eric Bourgain-Chang + 1 more
'Qing Nie'] The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and…
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…
Yang Jin, Yuanli Zuo, Gang Li, Wenrong Liu + 5 more
'Xin Fu' 'Xiaojun Yao' 'Yong Peng'] Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent…
Dongshan Ya, Yingmei Zhang, Qi Cui, Yanlin Jiang + 6 more
'Ning Tian' 'Wenjing Xiang' 'Xiaohui Lin' 'Qinghua Li' 'Rujia Liao'] Spatial transcriptome technology acquires gene expression profiles while retaining spatial location information, it displays the gene expression properties of cells in situ. Through the investigation of cell heterogeneity, microenvironment, function…
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…
Jade Xiaoqing Wang, Xiang Zhou
Spatial transcriptomic technologies are becoming increasingly high-resolution, enabling precise measurement of gene expression at the subcellular level. Here, we introduce a computational method called subcellular expression localization analysis (ELLA), for modeling the subcellular localization of mRNAs and detecting…
Oscar E. Ospina, Christopher M. Wilson, Alex C. Soupir, Anders Berglund + 3 more
Spatially-resolved transcriptomic technologies promise to increase our understanding of the tumor microenvironment, which will lead to better cancer prognosis and therapies. Several spatial transcriptomics technologies have been developed, as well as a few methods for data analysis. Nonetheless, analytical pipelines…
Lambda Moses, Lior Pachter
The function of many biological systems, such as embryos, liver lobules, intestinal villi, and tumors depends on the spatial organization of their cells. In the past decade high-throughput technologies have been developed to quantify gene expression in space, and computational methods have been developed that leverage…
Felicita Pia Masone, Francesco Napolitano
Spatial Transcriptomics assays allow to study gene expression as a function of the spatial position of cells across a tissue sample. Although several methods have been proposed to identify spatially variable genes, they do not take into account the position of the injection site in the case of treated samples. In this…
Ruishan Liu, Marco Mignardi, Robert Jones, Martin Enge + 3 more
Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed…
Andrea Sottosanti, Davide Risso, Francesco Denti
Spatial transcriptomics measures the expression of thousands of genes in a tissue sample while preserving its spatial structure. This class of technologies has enabled the investigation of the spatial variation of gene expressions and their impact on specific biological processes. Identifying genes with similar…
Pritam Dey, Rajarshi Guhaniyogi, Yang Ni, Bani K. Mallick
Spatially resolved transcriptomics is a fast-developing set of technologies that enables the measurement of localized gene expression across spatial locations in a sample. Detecting spatially varying genes is critical for analyzing such data, yet existing methods often fail to account for inter-gene correlations…
Braulio Valdebenito-Maturana, Cristina Guatimosim, Mónica Alejandra Carrasco, Juan Carlos Tapia + 2 more
'Mónica Alejandra Carrasco' 'Juan Carlos Tapia' 'Benoît Chénais' 'Frank M. You'] Spatial transcriptomics (ST) is transforming the way we can study gene expression and its regulation through position-specific resolution within tissues. However, as in bulk RNA-Seq, transposable elements (TEs) are not being studied due to…
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…
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…
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…
Qi Liu, Chih-Yuan Hsu, Yu Shyr
The expeditious growth in spatial omics technologies enable profiling genome-wide molecular events at molecular and single-cell resolution, highlighting a need for fast and reliable methods to characterize spatial patterns. We developed SpaGene, a model-free method to discover any spatial patterns rapidly in large…
Martin Emons, Samuel Gunz, Helena L. Crowell, Izaskun Mallona + 2 more
'Reinhard Furrer' 'Mark D. Robinson'] Spatial omics assays allow for the molecular characterisation of cells in their spatial context. Notably, the two main technological streams, imaging-based and high-throughput sequencingbased, can give rise to very different data modalities. The characteristics of the two data…
Natalie Charitakis, Mirana Ramialison, Hieu T. Nim
The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new insight to different tissue development is critical, but the appropriate tools to…
Authors not listed
Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) is a powerful technique for molecular analysis of surfaces; however, its application of single cell studies has not been previously published. In the current work, a commercial DESI setup (DESI XS) coupled to a mass spectrometer was used to analyze…
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
The WRN helicase has recently emerged as a promising therapeutic target for microsatellite instability (MSI)-high cancers. Here, we report LXW-P1, a potent WRN degrader derived from marine bromotyrosine alkaloids. Its molecular target was identified using an AI-guided, pathway-informed perturbation transcriptomics…
Juerg Straubhaar, Alexandria D’Souza, Zachary Niziolek, Bogdan Budnik
Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling…