Background Drug repositioning can reduce the time, costs and risks of drug development by
identifying new therapeutic effects for known drugs. It is challenging to reposition drugs as
pharmacological data is large and complex. Subnetwork identification has already been
used to simplify the visualization and interpretation of biological data, but it has not been
applied to drug repositioning so far. In this paper, we fill this gap by proposing a new
Physarum-inspired Prize-Collecting Steiner Tree algorithm to identify subnetworks for drug …