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研究领域生物医学和临床科学瘤学和致癌症预测和预后标志物
通过机器学习提升肺腺癌的预后和免疫疗法的有效性:从单细胞多组学中Anoikis调节器模式的新见解

通过机器学习提升肺腺癌的预后和免疫疗法的有效性:从单细胞多组学中Anoikis调节器模式的新见解

Shan Li ^1,2, Wenhang Zhou ³, Chen Hu ⁴, Ting Chen ³, Jinping Li ¹, Pengpeng Zhang ^1,2,3,4

Shan Li ^1,2, Wenhang Zhou ³, Chen Hu ⁴

¹Department of Laboratory Medicine, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu, China, yzsbh.com.
²Department of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China, chcmu.com.
³Department of Oncology, The Affiliated Huai'an Hospital of Xuzhou Medical University, the Second People's Hospital of Huai'an, Huai'an, Jiangsu, China, xzmc.edu.cn.
⁴Department of Anesthesiology, Huai'an Hospital of Huai'an City, Huai'an, Jiangsu, China.

⁰Department of Laboratory Medicine, Northern Jiangsu People's Hospital, Yangzhou, Jiangsu, China, yzsbh.com.

International Journal of Genomics +

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2026年一月5日

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概括

No abstract available on PubMed

关键词:

一个LUD 没有了机器学习多组学分析预后预测 scRNA-seq 在在 stRNA-seq

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Adaptive Mechanisms in Cancer Cells

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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
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