Partitioning Biological Networks into Highly Connected Clusters with Maximum Edge Coverage
Partitioning Biological Networks into Highly Connected Clusters with Maximum Edge Coverage
复制标题
将生物网络划分为具有最大边缘覆盖的高度连接的集群
DOI:
10.1109/tcbb.2013.177
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发表时间:
2014
期刊:
影响因子:
--
通讯作者:
R. Niedermeier
中科院分区:
文献类型:
--
作者:
F. Hüffner;C. Komusiewicz;A. Liebtrau;R. Niedermeier
A popular clustering algorithm for biological networks which was proposed by Hartuv and Shamir identifies nonoverlapping highly connected components. We extend the approach taken by this algorithm by introducing the combinatorial optimization problem Highly Connected Deletion, which asks for removing as few edges as possible from a graph such that the resulting graph consists of highly connected components. We show that Highly Connected Deletion is NP-hard and provide a fixed-parameter algorithm and a kernelization. We propose exact and heuristic solution strategies, based on polynomial-time data reduction rules and integer linear programming with column generation. The data reduction typically identifies 75 percent of the edges that are deleted for an optimal solution; the column generation method can then optimally solve protein interaction networks with up to 6,000 vertices and 13,500 edges within five hours. Additionally, we present a new heuristic that finds more clusters than the method by Hartuv and Shamir.
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作者:
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通讯作者:
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影响因子:
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期刊:
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影响因子:
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