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分层转录网络图案的推论

Inference in hierarchical transcriptional network motifs
课程网址: http://videolectures.net/mlsb2010_ocone_iht/  
主讲教师: Andrea Ocone
开课单位: 爱丁堡大学
开课时间: 2010-11-08
课程语种: 英语
中文简介:
我们提出了一种新的推理方法,用于在诸如前馈循环的分层网络模型中反转引擎转录因子(TF)的动态。我们提出的方法基于系统的连续时间表示,其中高级主控TF被表示为驱动微分方程系统的两状态马尔可夫跳跃过程。我们提出了一种近似的变分推理算法,并在实际仿真数据集上显示了有希望的初步结果。
课程简介: We present a novel inference methodology to reverse engineer the dynamics of transcription factors (TFs) in hierarchical network motifs such as feed-forward loops. The approach we present is based on a continuous time representation of the system where the high level master TF is represented as a two state Markov jump process driving a system of differential equations. We present an approximate variational inference algorithm and show promising preliminary results on a realistic simulated data set.
关 键 词: 前馈循环; 分层网络模型; 变分推理
课程来源: 视频讲座网
最后编审: 2019-07-02:cwx
阅读次数: 47