An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation.
An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation.
复制标题
对基因调节的局部因果途径进行主动学习因果发现方法的评估。
DOI：
10.1038/srep22558
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发表时间：
2016-03-04
影响因子：
4.6
通讯作者：
Statnikov A
中科院分区：
文献类型：
--
作者：
Ma S;Kemmeren P;Aliferis CF;Statnikov A
涉及疾病和重要细胞功能的因果途径的逆向工程是生物医学的一个基本问题。发现目标变量的局部因果通路（包括其直接原因和直接影响）对于有效干预至关重要，有助于准确诊断和预后。最近的研究提供了几种主动学习方法，这些方法可以利用被动观察的高通量数据来起草因果路径，然后通过有限数量的实验来完善推断的关系。目前的研究对主动学习方法在真实生物数据中局部因果通路发现的性能进行了全面的评估。具体而言，应用3个算法家族的54种主动学习方法/变体对酿酒酵母5个转录因子的基因调控进行局部因果通路重构。从邻接发现质量、边缘定位精度、完整路径发现质量和实验成本四个方面对方法的性能进行了评估。本研究的结果表明，一些方法比其他方法提供显著的性能优势，因此应该常规用于局部因果路径发现任务。本研究还证明了在实际生物系统中进行局部因果路径重建的可行性，并且具有显著的质量和较低的实验成本。
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost.