定向物理网络Orienting physical networks |
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课程网址: | http://videolectures.net/nipsworkshops2010_sharan_opn/ |
主讲教师: | Roded Sharan |
开课单位: | 特拉维夫大学 |
开课时间: | 2011-01-13 |
课程语种: | 英语 |
中文简介: | 在网络方向问题中,给出了一个混合图,包括有向和无向边,以及一组sourcetargetvertex对。目标是使无向边缘定向,使得最大数量的对允许从源到目标的有向路径。这个问题出现在分析蛋白质蛋白质和蛋白质DNA相互作用的物理网络的背景下。虽然后者是自然地从转录因子指向基因,但蛋白质相互作用中信号流动的方向通常是未知的或者甚至不能集体测量。然后,人们试图通过使用基因对的因果关系数据来推断这些信息,使得一个基因的扰动改变另一个基因的表达水平。在我的演讲中,我将讨论问题的复杂性,showapproximation算法的几个变体和presentan高效的ILP解决方案。然后,我将描述该算法在酵母中定位蛋白质蛋白质相互作用的应用,提高我们对网络结构和功能的理解。 |
课程简介: | In a network orientation problem one is given a mixed graph, consisting of directed and undirected edges, and a set of sourcetarget vertex pairs. The goal is to orient the undirected edges so that a maximum number of pairs admit a directed path from the source to the target. This problem arises in the context of analyzing physical networks of protein-protein and protein- DNA interactions. While the latter are naturally directed from a transcription factor to a gene, the direction of signal flow in protein-protein interactions is often unknown or cannot even be measured en masse. One then tries to infer this information by using causality data on pairs of genes such that the perturbation of one gene changes the expression level of the other gene. In my talk I will discuss the complexity of the problem, show approximation algorithms for several variants of it and present an efficient ILP solution for it. I will then describe the application of this algorithm to orient protein-protein interactions in yeast, improving our understanding of the structure and function of the network. |
关 键 词: | 网络方向; 混合图; 蛋白质 |
课程来源: | 视频讲座网 |
最后编审: | 2019-09-07:lxf |
阅读次数: | 63 |