A mixed clustering coefficient centrality for identifying essential proteins

DiffSLC: A graph centrality method to detect essential proteins of a protein-protein interaction network

Identification of central genes and proteins in biomolecular networks provides credible candidates for pathway analysis, functional analysis, and essentiality prediction. The DiffSLC centrality measure predicts central and essential genes and proteins using a protein-protein interaction network. Network centrality measures prioritize nodes and edges based on their importance to the network topo...

Alternatives to Betweenness Centrality: a Measure of Correlation Coefficient

In this paper, we measure and analyze the correlation of betweenness centrality (BWC) to five centrality measures, including eigenvector centrality (EVC), degree centrality (DEG), clustering coefficient centrality (CCC), farness centrality (FRC), and closeness centrality (CLC). We simulate the evolution of random networks and small-world networks to test the correlation between BWC and the five...

Evolution of Centrality Measurements for the Detection of Essential Proteins in Biological Networks

a framework for identifying and prioritizing factors affecting customers’ online shopping behavior in iran

the purpose of this study is identifying effective factors which make customers shop online in iran and investigating the importance of discovered factors in online customers’ decision. in the identifying phase, to discover the factors affecting online shopping behavior of customers in iran, the derived reference model summarizing antecedents of online shopping proposed by change et al. was us...

Clustering function: another view on clustering coefficient

Assuming that actors u and v have r common neighbors in a social network we are interested in how likely is that u and v are adjacent. This question is addressed by studying the collection of conditional probabilities, denoted cl(r), r = 0, 1, 2, . . . , that two randomly chosen actors of the social network are adjacent, given that they have r common neighbors. The function r → cl(r) describes ...