CENC - Complex Edge and Node Clustering Coefficient
Definition
This is a new method of $CENC$ coefficient to judge the essentiality of proteins by combining the features of protein complex and topology of nodes and edges. The basic considerations of $CENC$ are as follows: (1) the essential proteins that appear in complexes can have more frequency and (2) both the topology of node and edge are important factors to affect the essentiality of proteins.
$$CENC(v)=a \star{IC(v)\over IC_{max}} + b \star{NC(v)\over NC_{max}}+ c \star{C(v)\over C_{max}}$$
where $a$, $b$, $c$ are random factors ranging from 1 to 10. Under the amounts of experiments, it can get the best result of the method $CENC$ when $a$, $b$ and $c$ are 10, 1 and 1, respectively.
CENC is on the basis of the mixed clustering coefficient for complexes and edge topology.
$$CENC(v)=a \star{IC(v)\over IC_{max}} + b \star{NC(v)\over NC_{max}}+ c \star{C(v)\over C_{max}}$$
where $a$, $b$, $c$ are random factors ranging from 1 to 10. Under the amounts of experiments, it can get the best result of the method $CENC$ when $a$, $b$ and $c$ are 10, 1 and 1, respectively.
CENC is on the basis of the mixed clustering coefficient for complexes and edge topology.
References
- Lu P., Yu J.J., 2020. A mixed clustering coefficient centrality for identifying essential proteins. International Journal of Modern Physics B, 34(10).
DOI: 10.1142/S0217979220500903
