The diversification of methods for studying cell–cell interactions and communication
No cell lives in a vacuum, and the molecular interactions between cells define most
phenotypes. Transcriptomics provides rich information to infer cell–cell interactions and …
phenotypes. Transcriptomics provides rich information to infer cell–cell interactions and …
Spatial transcriptomics drives a new era in plant research
R Yin, K Xia, X Xu - The Plant Journal, 2023 - Wiley Online Library
Spatial transcriptomics drives a new era in plant research - Yin - 2023 - The Plant Journal - Wiley
Online Library Skip to Article Content Skip to Article Information Wiley Online Library Wiley …
Online Library Skip to Article Content Skip to Article Information Wiley Online Library Wiley …
SODB facilitates comprehensive exploration of spatial omics data
Spatial omics technologies generate wealthy but highly complex datasets. Here we present
Spatial Omics DataBase (SODB), a web-based platform providing both rich data resources …
Spatial Omics DataBase (SODB), a web-based platform providing both rich data resources …
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 …
SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics
Recent advancements in spatial transcriptomic technologies have enabled the
measurement of whole transcriptome profiles with preserved spatial context. However …
measurement of whole transcriptome profiles with preserved spatial context. However …
MENDER: fast and scalable tissue structure identification in spatial omics data
Z Yuan - Nature Communications, 2024 - nature.com
Tissue structure identification is a crucial task in spatial omics data analysis, for which
increasingly complex models, such as Graph Neural Networks and Bayesian networks, are …
increasingly complex models, such as Graph Neural Networks and Bayesian networks, are …
SpatialDM for rapid identification of spatially co-expressed ligand–receptor and revealing cell–cell communication patterns
Cell-cell communication is a key aspect of dissecting the complex cellular
microenvironment. Existing single-cell and spatial transcriptomics-based methods primarily …
microenvironment. Existing single-cell and spatial transcriptomics-based methods primarily …
NeST: nested hierarchical structure identification in spatial transcriptomic data
Spatial gene expression in tissue is characterized by regions in which particular genes are
enriched or depleted. Frequently, these regions contain nested inside them subregions with …
enriched or depleted. Frequently, these regions contain nested inside them subregions with …
Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases
P Kiessling, C Kuppe - Genome Medicine, 2024 - Springer
Spatial multi-omic studies have emerged as a promising approach to comprehensively
analyze cells in tissues, enabling the joint analysis of multiple data modalities like …
analyze cells in tissues, enabling the joint analysis of multiple data modalities like …
Pathogenesis, therapeutic strategies and biomarker development based on “omics” analysis related to microglia in Alzheimer's disease
C Gao, X Shen, Y Tan, S Chen - Journal of Neuroinflammation, 2022 - Springer
Alzheimer's disease (AD) is the most common neurodegenerative disease and the most
common cause of dementia. Among various pathophysiological aspects, microglia are …
common cause of dementia. Among various pathophysiological aspects, microglia are …