[HTML][HTML] Identifying multicellular spatiotemporal organization of cells with SpaceFlow
One major challenge in analyzing spatial transcriptomic datasets is to simultaneously
incorporate the cell transcriptome similarity and their spatial locations. Here, we introduce …
incorporate the cell transcriptome similarity and their spatial locations. Here, we introduce …
[HTML][HTML] SPACEL: deep learning-based characterization of spatial transcriptome architectures
H Xu, S Wang, M Fang, S Luo, C Chen, S Wan… - Nature …, 2023 - nature.com
Spatial transcriptomics (ST) technologies detect mRNA expression in single cells/spots
while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to …
while preserving their two-dimensional (2D) spatial coordinates, allowing researchers to …
DeepST: identifying spatial domains in spatial transcriptomics by deep learning
C Xu, X Jin, S Wei, P Wang, M Luo, Z Xu… - Nucleic Acids …, 2022 - academic.oup.com
Recent advances in spatial transcriptomics (ST) have brought unprecedented opportunities
to understand tissue organization and function in spatial context. However, it is still …
to understand tissue organization and function in spatial context. However, it is still …
Cell clustering for spatial transcriptomics data with graph neural networks
Spatial transcriptomics data can provide high-throughput gene expression profiling and the
spatial structure of tissues simultaneously. Most studies have relied on only the gene …
spatial structure of tissues simultaneously. Most studies have relied on only the gene …
[HTML][HTML] Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder
Recent advances in spatially resolved transcriptomics have enabled comprehensive
measurements of gene expression patterns while retaining the spatial context of the tissue …
measurements of gene expression patterns while retaining the spatial context of the tissue …
[HTML][HTML] Museum of spatial transcriptomics
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 …
tumors, depends on the spatial organization of their cells. In the past decade, high …
stLearn: integrating spatial location, tissue morphology and gene expression to find cell types, cell-cell interactions and spatial trajectories within undissociated tissues
Spatial Transcriptomics is an emerging technology that adds spatial dimensionality and
tissue morphology to the genome-wide transcriptional profile of cells in an undissociated …
tissue morphology to the genome-wide transcriptional profile of cells in an undissociated …
Identifying spatial domains of spatially resolved transcriptomics via multi-view graph convolutional networks
Motivation: Recent advances in spatially resolved transcriptomics (ST) technologies enable
the measurement of gene expression profiles while preserving cellular spatial context …
the measurement of gene expression profiles while preserving cellular spatial context …
[HTML][HTML] Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues
Spatial transcriptomics (ST) technologies generate multiple data types from biological
samples, namely gene expression, physical distance between data points, and/or tissue …
samples, namely gene expression, physical distance between data points, and/or tissue …
STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing
The recent advances in spatial transcriptomics have brought unprecedented opportunities to
understand the cellular heterogeneity in the spatial context. However, the current limitations …
understand the cellular heterogeneity in the spatial context. However, the current limitations …