时变网络：恢复果蝇生命周期中的临时重新布线遗传网络
Time-Varying Networks: Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster
摘要：
由于生物系统的动态性质，诸如{ \it Drosophila melanogaster}的发育的时间过程的生物网络可以表现出显著的拓扑变化以促进动态调节功能。因此，它是必不可少的开发方法，捕捉网络的时间演变，这使得有可能研究的驱动力的动态重新布线的基因调控电路，并预测未来的网络结构。使用一种名为Tesla的新机器学习方法，该方法建立在一种新的时间逻辑回归技术的基础上，我们报告了在\textit{Drosophila melanogaster}的生命周期中，对超过4000个基因的时间重新布线基因网络的潜在序列的首次成功的全基因组反向工程，给定纵向基因表达测量，甚至当从每个（时间特定的）网络得到的这种测量的单个快照可用时。我们的方法提供了第一次瞥见特定时间的快照和时间的进化模式的基因网络在一个活的有机体在其整个发展过程中。以这种前所未有的分辨率恢复的网络描绘了许多基因相互作用的开始和持续时间，这些相互作用是典型的静态网络分析所错过的，并且暗示了基因网络随着时间的推移而出现的一系列以前未注意到的其他时间行为。
英文摘要：
Due to the dynamic nature of biological systems, biological networks underlying temporal process such as the development of {\it Drosophila melanogaster} can exhibit significant topological changes to facilitate dynamic regulatory functions. Thus it is essential to develop methodologies that capture the temporal evolution of networks, which make it possible to study the driving forces underlying dynamic rewiring of gene regulation circuity, and to predict future network structures. Using a new machine learning method called Tesla, which builds on a novel temporal logistic regression technique, we report the first successful genome-wide reverse-engineering of the latent sequence of temporally rewiring gene networks over more than 4000 genes during the life cycle of \textit{Drosophila melanogaster}, given longitudinal gene expression measurements and even when a single snapshot of such measurement resulted from each (time-specific) network is available. Our methods offer the first glimpse of time-specific snapshots and temporal evolution patterns of gene networks in a living organism during its full developmental course. The recovered networks with this unprecedented resolution chart the onset and duration of many gene interactions which are missed by typical static network analysis, and are suggestive of a wide array of other temporal behaviors of the gene network over time not noticed before.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
