Portrai Insights
Insights on data analysis, AI, and the platform we're building at Portrai.
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96 articles
Integrative analysis of imaging and transcriptomic data of the immune landscape associated with tumor metabolism in lung adenocarcinoma: clinical and prognostic implications.
Although metabolic modulation in the tumor microenvironment (TME) is one of the key mechanisms of cancer immune escape, there is a lack of understanding of the…
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SpatialSPM: Statistical parametric mapping for the comparison of gene expression pattern images in multiple spatial transcriptomic datasets
Spatial transcriptomic (ST) techniques help us understand the gene expression levels in specific parts of tissues and organs, providing…
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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
Recently, cell therapy has emerged as a promising treatment option for various disorders.
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IAMSAM : Image-based Analysis of Molecular signatures using the Segment-Anything Model
Spatial transcriptomics is a cutting-edge technique that combines gene expression data with spatial information, allowing researchers to…
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Deep learning-based mapping of tertiary lymphoid structure scores from H&E images of renal cell carcinoma trained by spatial transcriptomics data
Tertiary lymphoid structures are organized aggregates of immune cells present in the tumor microenvironment (TME) in which novel targets as well as beneficial biomarkers for immunotherapy in cancer...
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Peptide-based theranostics targeting ANTXR1 in cancer stroma Available
ANTXR1 is one of the pancreatic ductal adenocarcinoma (PDAC) stroma-specific cell surface markers (Ref 1), which is also overexpressed in the stroma of various cancer types. Radiotheranostics refers..
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Mapping cell types in the tumor microenvironment from tissue images via deep learning trained by spatial transcriptomics of lung adenocarcinoma
Profiling heterogeneous cell types in the tumor microenvironment (TME) is important for cancer immunotherapy.
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GeneDART: Extending gene coverage in image-based spatial transcriptomics by deep learning-based domain adaptation with barcode-based RNA-sequencing data
Spatial transcriptomics (ST) technologies provide comprehensive biological insights regarding cell-cell interactions and peri-cellular…
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STopover captures spatial colocalization and interaction in the tumor microenvironment using topological analysis in spatial transcriptomics data
Unraveling the spatial configuration of the tumor microenvironment (TME) is key to understanding tumor-immune interactions to translate them…
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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