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Network alignment is a computational technique to identify topological similarity of graph data by mapping link patterns. In bioinformatics, network alignment algorithms have been applied to protein-protein interaction (PPI) networks to discover evolutionarily conserved substructures at the system level. In particular, local network alignment of PPI networks searches for conserved functional components...
Advanced technologies are producing large-scale protein-protein interaction data at an ever increasing pace. Finding protein-protein interaction complexes from large PPI networks is a fundamental problem in bioinformatics. In order to solve the set contains false negative and false positive noise data of protein data, we develop the graph model for limitation of structural protein complex. We proposed...
In recent years, numerous protein-protein interaction (PPI) datasets have been generated with the development of high-throughput experimental techniques. These datasets enable researchers to uncover protein complexes on network level. However, the performance of the computational methods relies heavily on the quality of the underlying protein interaction data, and these datasets are usually quite...
A signaling pathway, which is represented as a chain of interacting proteins for a biological process, can be predicted from protein-protein interaction (PPI) networks. However, pathway prediction is computationally challenging because of (1) inefficiency in searching all possible paths from the large-scale PPI networks and (2) unreliability of current PPI data generated by automated high-throughput...
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