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Partial Order-Based Bayesian Network Learning Algorithm for Estimating Gene Networks

机译:基于部分秩序的贝叶斯网络学习算法估算基因网络

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For learning Bayesian network structure from data, order-based algorithms such as K2 algorithm are widely used.In this paper, we consider a problem of constructing the order of nodes in such algorithms based on prior knowledge of gene networks.  However, in many cases the prior knowledge is given as partial order of genes and we need to extend the order-based algorithm to partial order-based one. By extending our prior work we propose an efficient  partial order-based algorithm for estimating gene networks based on Bayesian networks. The computational complexity of the proposed algorithm is shown.
机译:对于从数据学习贝叶斯网络结构,广泛使用诸如K2算法的订单的算法。本文基于基于基因网络的先验知识,考虑在这种算法中构建节点顺序的问题。然而,在许多情况下,先验知识作为基因的部分顺序给出,我们需要将基于订单的算法扩展到部分顺序的算法。通过延长我们的事先工作,我们提出了一种基于基于贝叶斯网络的基因网络的基于基于部分阶数的算法。示出了所提出的算法的计算复杂性。

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