Network Intervention, a Method to Address Complex Therapeutic Strategies.

Network Intervention, a Method to Address Complex Therapeutic Strategies.
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网络干预,一种解决复杂治疗策略的方法

DOI:
10.3389/fphar.2018.00754
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发表时间:
2018
影响因子:
5.6
通讯作者:
Lu AP
Lu AP
中科院分区:
医学2区
文献类型:
--
作者:
Zhang C;Zhou W;Guan DG;Wang YH;Lu AP

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目的:基于网络的方法成为研究复杂疾病的有力工具。我们在这篇文章中的目的是提高人们对生物网络背景下新治疗策略的益处的认识,并对这一主题进行介绍。研究方法:本文将讨论网络干预的合理性,并概述一些重要方面的破译目标在网络中的活动和未来的网络干预的实施方式。我们还提出了基于这些方法使用的策略的网络干预的例子。结果如下:网络干预寻求目标组合来扰乱疾病网络中的特定节点子集,以抑制系统级的旁路机制。实验结果来自我们的研究进行了讨论,与结论,导致未来的研究方向。设计了一个简单的图,给出了一种基于图论的方法来寻找网络干预所需的最小外部输入数量,并得到最小输入的解析值。结论:因此,以这种方式创建解决失明和不假思索的行为的网络干预可以提供比多靶点治疗更多的益处。我们希望这篇文章能让读者对一种新的治疗策略有一个了解,这种策略是通过采用基于网络的方法来提高临床效益,并深入了解它们的特性。
Objective: Network-based approaches emerged as powerful tools for studying complex diseases. Our intention in this article was to raise awareness of the benefits of new therapeutic strategy in biological networks context and provide an introduction to this topic. Methods: This article will discuss the rational for network intervention, and outline some of the important aspects of deciphering targets activities in the network and future embodiments of network intervention. We also present examples of network intervention based on the strategies these approaches use. Results: Network intervention seeks for target combinations to perturb a specific subset of nodes in disease networks to inhibit the bypass mechanisms at systems level. Experimental results derived from our studies are discussed, with conclusions that lead to future research directions. A simple diagram is designed to give a way to find the minimum number of external input required for a network intervention based on the graph theory and get the analytical value of the least input. Conclusion: Creating network intervention that addresses blindness and unthinking action in this way could, therefore, provide more benefit than multi-target therapy. We hope that this article will give readers an appreciation for a new therapeutic strategy that has been proposed for improving clinical benefit by adopting network-based approaches as well as insight into their properties.
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