Abstract
Many issues in bio-molecular networks can be boiled down to the identification of important nodes or gene prioritization. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness, k-shell, clustering coefficient, closeness, semi-local centrality, PageRank, and LeaderRank. Different measures consider different aspects of complex networks. In this chapter, based on network motifs and principal component analysis, we introduced a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks. Further using the principal component analysis technique to integrate some existing centrality measures, we introduced a new integrative measure to find the structurally dominant proteins in protein interaction networks. Finally, the recently proposed SpectralRank and the weighted SpectralRank will be introduced, which can be used in various kinds of networks.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
