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高斯过程与基因调控

Gaussian Processes and Gene Regulation
课程网址: http://videolectures.net/prib2010_lawrence_gpg/  
主讲教师: Neil D. Lawrence
开课单位: 谢菲尔德大学
开课时间: 2010-10-14
课程语种: 英语
中文简介:
计算生物学模型通常缺少信息,例如感兴趣的生物化学物质的浓度。处理这种缺失信息的一种方法是在遗漏数据上放置概率先验。这种先验的一种可能选择是高斯过程。在本教程中,我们将介绍高斯过程。我们将给出回归和插值中高斯过程的简单例子。然后,我们将展示高斯过程如何与微分方程模型结合,以给出转录的概率模型。然后可以使用这些模型对给定转录因子的潜在靶标进行排序。
课程简介: Computational biology models are often missing information, such as the concentration of biochemical species of interest. One approach to dealing with this missing information is to place a probabilistic prior over the missing data. One possible choice for such a prior is a Gaussian process. In this tutorial we will give an introduction to Gaussian processes. We will give simple examples of Gaussian processes in regression and interpolation. We will then show how Gaussian processes can be incorporated with differential equation models to give probabilistic models for transcription. Such models can then be used to rank potential targets of given transcription factors.
关 键 词: 化学物质; 概率先验; 高斯过程
课程来源: 视频讲座网
最后编审: 2020-01-13:chenxin
阅读次数: 53