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RANGI:一种快速的列表着色图模式发现算法。

RANGI: a fast list-colored graph motif finding algorithm.

机构信息

Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran, PO Box 14115-194, Tehran, Iran.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2013 Mar-Apr;10(2):504-13. doi: 10.1109/TCBB.2012.167.

Abstract

Given a multiset of colors as the query and a list-colored graph, i.e., an undirected graph with a set of colors assigned to each of its vertices, in the NP-hard list-colored graph motif problem the goal is to find the largest connected subgraph such that one can select a color from the set of colors assigned to each of its vertices to obtain a subset of the query. This problem was introduced to find functional motifs in biological networks. We present a branch-and-bound algorithm named RANGI for finding and enumerating list-colored graph motifs. As our experimental results show, RANGI's pruning methods and heuristics make it quite fast in practice compared to the algorithms presented in the literature. We also present a parallel version of RANGI that achieves acceptable scalability.

摘要

给定一个颜色的多重集作为查询和一个带颜色的列表图,即一个带有一组颜色分配给每个顶点的无向图,在 NP 难的带颜色的列表图基元问题中,目标是找到最大的连通子图,使得可以从分配给每个顶点的颜色集中选择一种颜色,从而得到查询的一个子集。这个问题是为了在生物网络中找到功能基元而引入的。我们提出了一种名为 RANGI 的分支定界算法,用于发现和枚举带颜色的列表图基元。正如我们的实验结果所示,与文献中提出的算法相比,RANGI 的剪枝方法和启发式算法使其在实践中非常快速。我们还提出了 RANGI 的并行版本,实现了可接受的可扩展性。

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