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Generation of Super-resolution Images from Barcode-based Spatial Transcriptomics Using Deep Image Prior
doi: https://doi.org/10.1016/j.crmeth.2024.100937 Abstract Spatial transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. How…
포트래이-
SpatialSPM: Statistical parametric mapping for the comparison of gene expression pattern images in multiple spatial transcriptomic datasets
doi: https://doi.org/10.1101/2023.06.26.546605 Abstract Spatial transcriptomic (ST) techniques help us understand the gene expression levels in specific parts of tissues and organs, providing insight…
포트래이-
Mapping cell types in the tumor microenvironment from tissue images via deep learning trained by spatial transcriptomics of lung adenocarcinoma
doi: https://doi.org/10.1101/2023.03.04.531083 Abstract Profiling heterogeneous cell types in the tumor microenvironment (TME) is important for cancer immunotherapy. Here, we propose a method and val…
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IAMSAM : Image-based Analysis of Molecular signatures using the Segment-Anything Model
doi: https://doi.org/10.1101/2023.05.25.542052 Abstract Spatial transcriptomics is a cutting-edge technique that combines gene expression data with spatial information, allowing researchers to study …
포트래이-
GeneDART: Extending gene coverage in image-based spatial transcriptomics by deep learning-based domain adaptation with barcode-based RNA-sequencing data
doi: https://doi.org/10.1101/2023.02.07.527488 Abstract Spatial transcriptomics (ST) technologies provide comprehensive biological insights regarding cell-cell interactions and peri-cellular microenv…
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A Spatial Transcriptomics based Label-Free Method for Assessment of Human Stem Cell Distribution and Effects in a Mouse Model of Lung Fibrosis
doi: https://doi.org/10.1101/2023.05.31.542821 Abstract Recently, cell therapy has emerged as a promising treatment option for various disorders. Given the intricate mechanisms of action (MOA) and he…
포트래이-
STopover captures spatial colocalization and interaction in the tumor microenvironment using topological analysis in spatial transcriptomics data
doi: https://doi.org/10.1101/2022.11.16.516708 Abstract Unraveling the spatial configuration of the tumor microenvironment (TME) is key to understanding tumor-immune interactions to translate them in…
포트래이-
Spatial Transcriptomics-based Identification of Molecular Markers for Nanomedicine Distribution in Tumor Tissue
doi: https://doi.org/10.1101/2022.03.02.482584 Abstract The intratumoral accumulation of nanomedicine has been considered a passive process, referred to as the enhanced permeability and retention (EP…
포트래이-
CellDART: cell type inference by domain adaptation of single-cell and spatial transcriptomic data
Nucleic Acids Research, gkac084 Abstract Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tis…
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