网络逼近图案数Approximating the Number of Network Motifs |
|
课程网址: | http://videolectures.net/waw09_gonen_annm/ |
主讲教师: | Mira Gonen, Yuval Shavitt |
开课单位: | 特拉维夫大学 |
开课时间: | 2009-03-12 |
课程语种: | 英语 |
中文简介: | 万维网,互联网,耦合的生物和化学系统,神经网络和社会相互作用物种,只是由大量高度互联的动力单元组成的系统的几个例子。这些网络包含称为网络图案的特征模式,其发生频率远高于具有相同度序列的随机网络。已经提出了几种算法用于计数或检测以树的形式的网络图案的诱导或非诱导发生的次数以及大小为O(log(n))的有界树宽子图,并且对于一些图案,大小为7。另外,最近建议计算节点所属的图案的数量作为对网络中的节点进行分类的方法。承诺是节点参与的主题的分布是其在网络中的功能的指示。因此,计算节点所属的网络图案的数量提供了主要挑战。但是,不存在这样的实用算法。我们提出了几种时间复杂度为O((e ^ 2k)* k * n * | E | * log((1 / delta)/ epsilon ^ 2))的算法,这是第一次近似每个顶点的数量对于k长度循环,具有和弦的k长度循环,以及(k −  1) - 长度路径,其中k和thinsp; =  O(log)的非诱导出现的顶点是其一部分的主题(n)),并且所有图案的尺寸最多为四个。此外,当没有有效的算法存在时,我们显示的算法接近这些网络图案的非诱导发生的总数。我们的一些算法使用颜色编码技术。 |
课程简介: | World Wide Web, the Internet, coupled biological and chemical systems, neural networks, and social interacting species, are only a few examples of systems composed by a large number of highly interconnected dynamical units. These networks contain characteristic patterns, termed network motifs, which occur far more often than in randomized networks with the same degree sequence. Several algorithms have been suggested for counting or detecting the number of induced or non-induced occurrences of network motifs in the form of trees and bounded treewidth subgraphs of size O(log(n)), and of size at most 7 for some motifs. In addition, counting the number of motifs a node is part of was recently suggested as a method to classify nodes in the network. The promise is that the distribution of motifs a node participate in is an indication of its function in the network. Therefore, counting the number of network motifs a node is part of provides a major challenge. However, no such practical algorithm exists. We present several algorithms with time complexity O((e^2k) * k * n * |E| * log((1/delta)/epsilon^2)) that, for the first time, approximate for every vertex the number of non-induced occurrences of the motif the vertex is part of, for k-length cycles, k-length cycles with a chord, and (k − 1)-length paths, where k = O(log(n)), and for all motifs of size of at most four. In addition, we show algorithms that approximate the total number of non-induced occurrences of these network motifs, when no efficient algorithm exists. Some of our algorithms use the color coding technique. |
关 键 词: | 网络; 基序; 图案 |
课程来源: | 视频讲座网 |
最后编审: | 2020-06-12:邬启凡(课程编辑志愿者) |
阅读次数: | 66 |