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데이터 분석과 AI 기술, 그리고 포트래이가 만들어가는 플랫폼의 생각을 전합니다.
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글 15편
Detecting cancer microbiota using unmapped RNA reads on spatial transcriptomics
Recently, the study of microbiota has emerged as a novel area in cancer research. While next-generation sequencing (NGS) technologies are becoming more prevalent in the area, the acquisition of spa...
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Data-driven discovery of cancer-specific targets for hepatocellular carcinoma using spatial transcriptomics
Hepatocellular carcinoma (HCC) is frequently diagnosed in advanced stages, with limited options available for systemic treatment. Given the significant investment of time, the high costs, and the...
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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
NTXR1 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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Discovery of stromal targets in pancreatic cancer Available
-5007-Discovery-of-stromal-targets-in Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the…
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Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data
Spatial characterization of cell types of the tumor microenvironment (TME) is a key to finding new targets as well as developing biomarkers for immuno-oncology treatment. Here, we develop and validate
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