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Updated: Mar 7, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Published on: December 7, 2021

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在用于动态网络分析的随机行为者导向模型中计算边缘不确定性

Heather M Shappell1, Mark A Kramer2, Catherine J Chu3

  • 1Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston Salem, NC, USA.

Network science (Cambridge University Press)
|March 6, 2026
PubMed
概括

本研究引入了一个隐藏的马尔科夫模型 (HMM) 扩展到随机行为者导向模型 (SAOMs),以准确分析杂的网络数据. 这种新方法可以提高动态网络 (包括功能性脑网络) 的估计准确度.

关键词:
大脑网络 大脑网络预期最大化算法是指期望最大化算法.隐藏的马尔科夫模型纵向网络分析 纵向网络分析颗粒过器 颗粒过器社交网络 社交网络

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