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Updated: Jun 3, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

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细胞系扰乱实验中的因果模型和预测

James P Long1, Yumeng Yang2, Shohei Shimizu3

  • 1Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. jplong@mdanderson.org.

BMC bioinformatics
|January 8, 2025
PubMed
概括

计算模型可以预测细胞对干扰的反应. 线性回归 (LR) 和因果结构回归 (CSR) 进行了比较,LR在黑色素瘤细胞系数据上表现比Cellbox更好或更好.

关键词:
因果推理的原因推理.扰动生物学的生物学预测 预测 预测系统生物学 系统生物学

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