25 papers · ranked by Valyu relevance
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…
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…
Zhuoyan Xu, Kris Sankaran
Spatially resolved transcriptomics (ST) measures gene expression along with the spatial coordinates of the measurements. The analysis of ST data involves significant computation complexity. In this work, we propose gene expression dimensionality reduction algorithm that retains spatial structure. We combine the wavelet…
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…
Yeojin Kim, Abhishek Ojha, Alex Schrader, Juyeon Lee + 7 more
Spatial transcriptomics (ST) technologies have enabled new explorations into the spatial organization of tissues and their functional implications. However, one of the most fundamental analyses – comparative analysis of spatial gene expression across phenotypes – remains a formidable challenge. We introduce…
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…
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…
David Liska, Zachery Wolfe, Adam Norris, Guoqiang Yu
As an example of the utility of VISTA, we investigated whether we could predict interesting new spatially restricted gene expression patterns simply by visual browsing through genes on VISTA. We focused on transcription factor genes, which have been extensively studied for their cell-specific expression and function…
Matthew N. Bernstein, Zijian Ni, Aman Prasad, Jared Brown + 4 more
'Chitrasen Mohanty' 'Ron Stewart' 'Michael A. Newton' 'Christina Kendziorski'] Title: Summary Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial…
Uthsav Chitra, Shu Dan, Fenna Krienen, Benjamin J. Raphael
Gene expression varies across a tissue due to both the organization of the tissue into spatial domains, i.e. discrete regions of a tissue with distinct cell type composition, and continuous spatial gradients of gene expression within different spatial domains. Spatially resolved transcriptomics (SRT) technologies…
Kevin Meng-Lin, Choong-Yong Ung, Cheng Zhang, Taylor M. Weiskittel + 9 more
'Philip Wisniewski' 'Zhuofei Zhang' 'Shyang-Hong Tan' 'Kok-Siong Yeo' 'Shizhen Zhu' 'Cristina Correia' 'Hu Li' 'Xin Lai' 'Le Zhang'] Spatially resolved sequencing technologies help us dissect how cells are organized in space. Several available computational approaches focus on the identification of spatially variable…
Shicheng Zhang, Koichi Saeki, Hiroshi Haeno
Spatial transcriptomics captures context-dependent gene expression; however, existing workflows do not consistently account for measurement scale and often rely on a user-defined spatial neighbor graph, making results sensitive to this choice and limiting cross-study comparability. We present geneSCOPE (gene Spatial…
Shan Yu, Wei Vivian Li
Spatially resolved transcriptomics technologies have opened new avenues for understanding gene expression heterogeneity in spatial contexts. However, existing methods for identifying spatially variable genes often focus solely on statistical significance, limiting their ability to capture continuous expression patterns…
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…
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…
James Boyle, Gregory Hamm, Eleanor Williams, Robin JG Hartman + 3 more
'Magnus Soderburg' 'Ian Henry' 'Michael Casey'] 1Data Science and AI, Translational Science & Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism, Biopharmaceuticals R&D, AstraZeneca, Cambridge, UK 2 Integrated Bioanalysis, Clinical Pharmacology and Safety Sciences…
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…
Chenxin Flora Jiang, Yuxin Yin, Paul Robson, Yuanhao James Li + 2 more
Spatial transcriptomics has transformed our ability to explore gene expression within its tissue context, enabling us to dissect subtle yet biologically significant variations in situ. While numerous computational methods have been proposed for detecting Spatially Varying Genes (SVGs) expression by modeling each…
Siddhartha G. Jena, Archit Verma, Barbara E. Engelhardt
Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shape, relative locations of, movement of, and interactions between cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun…
Magdalena Schindler, Marco Osterwalder, Izabela Harabula, Lars Wittler + 6 more
'Lars Wittler' 'Athanasia C. Tzika' 'Dina K. N. Dechmann' 'Martin Vingron' 'Axel Visel' 'Stefan A. Haas' 'Francisca M. Real'] Title: ABSTRACT Changes in gene expression represent an important source of phenotypic innovation. Yet how such changes emerge and impact the evolution of traits remains elusive. Here, we…
Authors not listed
Self-organizing tissues, such as organoids, offer transformative potential beyond healthcare by enabling the sustainable production of advanced materials. Resource scarcity and global warming drive the need for innovative fabrication solutions. This prospective review explores developmental biology as a manufacturing…
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One aim of the international Human Proteome Organization (HUPO) Human Proteome Project (HPP) is to obtain high-confidence translation evidence for every human protein-coding gene established in its target list of 19433 entries based on the protein-coding genes from Ensembl-GENCODE. However, 76 are annotated in…
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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…
Spencer Kim, Dylan Gray, Michelle Shanguhyia, Rachel Steinhardt
Recreating the signaling profile a chemical synapse to analyze serotonin receptor activation is a challenge. This is due in part to the kinetics of the synapse, where neurotransmitters are rapidly released and quickly cleared by active reuptake machinery. One strategy to produce a rapid rise in a bio-orthogonally…
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Molecular mechanisms governing initiation steps of the assembly of thousands of endogenous multi-protein complexes (EMCs) remain incompletely understood. Here, multiple lines of observations are reported reflecting the biological functions-aligned initiation sequence of hybrid assembly pathways (HAPs) of EMCs. HAPs…