A local average connectivity-based method for identifying essential proteins from the network level

► A protein's essentiality is determined by evaluating the relationship between it and its neighbors. ► The number of essential proteins predicted by LAC clearly exceeds that explored by Degree Centrality (DC). ► LAC outweighs the eight previous essential protein discovery methods (Degree Centrality (DC), Neighborhood Component (DMNC), Betweenness Centrality (BC), Closeness Centrality (CC), Bottle Neck (BN), Information Centrality (IC), Eigenvector Centrality (EC), and Subgraph Centrality (SC)) on the results of F-measure and accuracy. ► LAC also outperforms the eight previous essential protein discovery methods on the validation of jackknifing methodology.