基于监督机器学习的生物网络重构
Reconstruction of biological networks by supervised machine learning approaches
摘要：
我们回顾了计算系统生物学的一个最新趋势，其目的是使用模式识别算法来推断大规模生物网络的结构，从异质基因组数据。我们提出了几种策略，已经提出，并导致不同的模式识别问题和算法。这些方法的优势体现在模式生物代谢网络、蛋白质-蛋白质网络和调控网络的重建上。在所有情况下，报告了最先进的性能。
英文摘要：
We review a recent trend in computational systems biology which aims at using pattern recognition algorithms to infer the structure of large-scale biological networks from heterogeneous genomic data. We present several strategies that have been proposed and that lead to different pattern recognition problems and algorithms. The strenght of these approaches is illustrated on the reconstruction of metabolic, protein-protein and regulatory networks of model organisms. In all cases, state-of-the-art performance is reported.
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