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Updated: Jun 27, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

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同表达网络和机器学习 转录学数据的分析 识别了在病变性和非病变性无皮炎中不同的基因特征和途径

Eskezeia Y Dessie1, Lili Ding2, Latha Satish1

  • 1Division of Asthma Research, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, 3333 Burnet Avenue, Cincinnati, OH 45229-3039, USA.

Journal of personalized medicine
|September 28, 2024
PubMed
概括

这项研究确定了关键的基因和通路特征,区分了亚托皮炎 (AD) 皮肤与健康的皮肤. 这些发现为AD病原和潜在的治疗点提供了新的见解.

关键词:
亚托邦性皮肤炎 (AD)诊断生物标志物 生物标志物机器学习是机器学习.路径表达式分析权重的共同表达网络分析.

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