期刊
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
卷 61, 期 1, 页码 152-163出版社
WILEY
DOI: 10.1002/prot.20532
关键词
protein chain universe graph; real-world networks; eigenvalue and eigenvector components of graphs; sub-graph density; weighted graphs
We present a simple method for the analysis of large networks based on their graph spectral properties. One of the advantages of this method is that it uses a single numerical computation to identify subclusters in a connected graph, which can significantly simplify the complexity involved in analyzing large graphs. This is illustrated using a network of protein chains constructed on the basis of their structural similarities. The largescale network properties and the cluster and subcluster organization of the protein chain network are presented. We summarize the results of structural and functional analyses of the nodes present in these clusters and elucidate the implications of structural similarity in the protein chain universe.
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