Evaluation of subgraph searching algorithms for detecting network motifs in biological networks

Front. Comput. Sci. ›› 2009, Vol. 3 ›› Issue (3) : 412 -416.

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Front. Comput. Sci. ›› 2009, Vol. 3 ›› Issue (3) : 412 -416. DOI: 10.1007/s11704-009-0045-z
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Evaluation of subgraph searching algorithms for detecting network motifs in biological networks

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Abstract

Despite several algorithms for searching subgraphs in motif detection presented in the literature, no effort has been done for characterizing their performance till now. This paper presents a methodology to evaluate the performance of three algorithms: edge sampling algorithm (ESA), enumerate subgraphs (ESU) and randomly enumerate subgraphs (RAND-ESU). A series of experiments are performed to test sampling speed and sampling quality. The results show that RAND-ESU is more efficient and has less computational cost than other algorithms for large-size motif detection, and ESU has its own advantage in small-size motif detection.

Keywords

network motifs / subgraphs searching / subgraphs enumeration / sampling algorithm

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null. Evaluation of subgraph searching algorithms for detecting network motifs in biological networks. Front. Comput. Sci., 2009, 3(3): 412-416 DOI:10.1007/s11704-009-0045-z

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