R package-dSimer: In 2015, we implemented a R package dSimer. It provides computation of nine methods for measuring disease-disease similarity, including a standard cosine similarity measure CosineDFV and eight function-based methods (BOG, CosineDFV, FuncSim, ICod, PSB, Separation, Sun_annotation, Sun_function, Sun_topology). The disease similarity matrix obtained from these 9 methods can be visualized through heatmap and network.

Python package-NetBasedDSim: In 2020, we implemented a python package: NetBasedDSim. It integrates 12 methods (ResinkSim, XuanSim, CosineDFV, MicrobeSim, MimMinner, Separation, ModuleSim, FunSim, NetSim, IDN, RADAR, mpDisNet) for the disease similarity computation and the results can be evaluated by the benchmark data set.