A network-based approach that ranks a given set of networks based on its "similarity" to a reference network. TINTIN exploits target feature-based network similarity in order to determine if two networks are similar. Specifically, it leverages topological and dynamic features of targets to compute similarity distances between signaling networks and rank them accordingly. TINTIN is useful to address problems such target prioritization and drug target repositioning.
Runnable .jar: TINTIN.jar is found in the release (https://github.com/trove2017/Tintin/releases).