Abstract
The biological network database presents exponential growth, how to find the target network accurately from the network database becomes the difficult problem. This paper proposes a new network similarity search algorithm, the similar network of Top k is calculated by two methods, the similar networks returned by the two algorithms are then filtered by overlap fractions, the weighted reordering algorithm is used to reorder the two sets of data, a precise set of similar network data sets is returned finally.In this paper, the accuracy of the query is judged by the comparison of the edge correctness (EC) value and the maximum public connection subgraph (LCCS) value of the returned sorted similar network data set, and compare query time with other algorithms.From the results, this algorithm is superior to other algorithms in query accuracy and query speed.
Highlights
The network is widely used in bioinformatics[1], chemical informatics[2], biomedicine[3], social network analysis[4], and other application fields[5]
GString[12] is a semantic approach; GraphGrepSX[13] is an index subgraph similar search method based on suffix tree structure; SIGMA[14] is a collection based NSS method; RINQ[15] is a reference based index query method; NeMa[16] is a subgraph search method of a community; MAGE[17] is a pattern matching system that supports a random walk based network (RWR) algorithm; REFBSS[18] redefined RINQ's improvement
A network can be regarded as a directed graph N = (V, E), V represents the point in the graph, E represents the edge in the graph, and the network database is the data center used to store the biological network
Summary
The network is widely used in bioinformatics[1], chemical informatics[2], biomedicine[3], social network analysis[4], and other application fields[5]. GString[12] is a semantic approach; GraphGrepSX[13] is an index subgraph similar search method based on suffix tree structure; SIGMA[14] is a collection based NSS method; RINQ[15] is a reference based index query method; NeMa[16] is a subgraph search method of a community; MAGE[17] is a pattern matching system that supports a random walk based network (RWR) algorithm; REFBSS[18] redefined RINQ's improvement. In view of the deficiency existing in the above algorithm, proposed a new algorithm, the algorithm by combining the two similarity search of Top k network to achieve the similar network the improvement of accuracy and less time for the query
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