Generalizations of the topological overlap measure for neighborhood analysis and module detection in gene and protein networks

Motivation. In network analysis the goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes while the goal of module detection is to find the sets of genes which are highly interacted with each other. These two analysis are important in systems biology. If individual network connections are susceptible to noise, it can he advantageous to define similarity between nodes on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. It can be advantageous to define multi-node similarity measures because such multiple nodes similarity provides a direct view of the relationship among a set of nodes instead of only pair-wise relationship.; Results. The pairwise topological overlap measure is generalized to multiple network nodes(MTOM). For neighborhood analysis MTOM is subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. For module detection we propose the Module Affinity Search Technique (MAST) which is a modification of Cluster Affinity Search Technique and feed it with MTOM. We provide empirical and simulation evidence that the resulting neighborhoods and modules are biologically meaningful, e.g. we use neighborhood analysis and module detection to brain cancer gene co-expression network.; Availability. A executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the following webpage:; http://www.genetics.ucla.edu/labs/horvath/MTOM/...