11 papers · ranked by Valyu relevance
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…
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…
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…
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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…
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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…
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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…