SpatialScope: A unified approach for integrating spatial and single-cell transcriptomics data using deep generative models
The rapid emergence of spatial transcriptomics (ST) technologies are revolutionizing our
under-standing of tissue spatial architecture and their biology. Current ST technologies …
under-standing of tissue spatial architecture and their biology. Current ST technologies …
Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope
The rapid emergence of spatial transcriptomics (ST) technologies is revolutionizing our
understanding of tissue spatial architecture and biology. Although current ST methods …
understanding of tissue spatial architecture and biology. Although current ST methods …
Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing
AA Heydari, SS Sindi - BioRxiv, 2022 - biorxiv.org
Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …
Tissue module discovery in single-cell-resolution spatial transcriptomics data via cell-cell interaction-aware cell embedding
Computational methods are desired for single-cell-resolution spatial transcriptomics (ST)
data analysis to uncover spatial organization principles for how individual cells exert tissue …
data analysis to uncover spatial organization principles for how individual cells exert tissue …
SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution
Integrating single cell RNAseq (scRNAseq) and spatial transcriptomics (ST) data is still
challenging especially when the spatial resolution is poor. For cellular resolution spatial …
challenging especially when the spatial resolution is poor. For cellular resolution spatial …
[HTML][HTML] Deep learning in spatial transcriptomics: Learning from the next next-generation sequencing
AA Heydari, SS Sindi - Biophysics Reviews, 2023 - pubs.aip.org
Spatial transcriptomics (ST) technologies are rapidly becoming the extension of single-cell
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …
RNA sequencing (scRNAseq), holding the potential of profiling gene expression at a single …
iSORT: An Integrative Method for Reconstructing Spatial Organization of Cells using Transfer Learning
Understanding the cellular spatial organization is a paramountly important direction of
exploring the intricate functionalities of tissues and organs. However, conventional single …
exploring the intricate functionalities of tissues and organs. However, conventional single …
STEM: A method for mapping single-cell and spatial transcriptomics data with transfer learning
Profiling spatial variations of cellular composition and transcriptomic characteristics is
important for understanding the physiology and pathology of tissues in health or diseases …
important for understanding the physiology and pathology of tissues in health or diseases …
STellaris: a web server for accurate spatial mapping of single cells based on spatial transcriptomics data
X Li, C Xiao, J Qi, W Xue, X Xu, Z Mu… - Nucleic acids …, 2023 - academic.oup.com
Single-cell RNA sequencing (scRNA-seq) provides insights into gene expression
heterogeneities in diverse cell types underlying homeostasis, development and pathological …
heterogeneities in diverse cell types underlying homeostasis, development and pathological …
stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics
Motivation Single-cell RNA sequencing (scRNA-seq) techniques have revolutionized the
investigation of transcriptomic landscape in individual cells. Recent advancements in spatial …
investigation of transcriptomic landscape in individual cells. Recent advancements in spatial …