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55 articles
Engineering and evaluation of precision-glycosylated clickable albumin nanoplatform for targeting the tumor microenvironment
doi: https://doi.org/10.7150/thno.123973 https://www.thno.org/ms/acceptms Abstract Rationale: Glycosylation of drug delivery vehicles enables selective tumor microenvironment (TME) targeting but is l…
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Spatial transcriptomics unveils landscape of resistance to concurrent chemo-radiotherapy in hypopharyngeal squamous cell carcinoma: the role of SPP1+ macrophages
doi: https://doi.org/10.1101/2024.07.09.602476 Abstract Hypopharyngeal squamous cell carcinoma (SCC) is a highly aggressive cancer with a poor prognosis, particularly in advanced stages where concurr…
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Analysis of Unmapped RNA-seq Data from Cancer Spatial Transcriptome to Decipher Cancer Microbiome
doi: https://doi.org/10.1101/2024.06.09.598160 Abstract Recent research increasingly emphasizes the importance of the microbiome in the development and progression of cancer. Thus, exploring the micr…
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Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression
doi: https://doi.org/10.1101/2024.05.16.594592 Abstract While cancer-associated fibroblasts (CAFs) are crucial in influencing tumor growth and immune responses in lung cancer, we still lack a compreh…
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CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities
doi: https://doi.org/10.1101/2024.05.08.593094 Abstract Large-scale single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have transformed biomedical research into a data-driven fie…
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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…
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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…
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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 …
Portrai-WRITTEN BY
Portrai's Authors
Capturing and compounding Portrai's insights.
Daeseung Lee
CEO
Physician-scientist who left clinical practice to bring spatial biology into oncology drug discovery
Hongyoon Choi
CTO
Builds the algorithms that turn spatial transcriptomics into actionable target intelligence
Hyung-Jun Im
CSO
Nuclear medicine specialist linking imaging biomarkers to next-generation radiopharmaceuticals
Kwonjoong Na
CMO
Translates platform insights into IND-enabling decisions across oncology programs
Portrai
Official posts from the Portrai team, decoding disease with spatial intelligence