Fig. 2

Scheme for predicting domain-disease relationships. Nodes represent diseases/traits, modules, proteins and domains. An edge connecting two nodes represents a known association. Steps 1-7 demonstrate the procedure that, when predicting for a specific disease, how to obtain its candidate domains. Step 1: For a given disease T _n , all module(s) containing this disease (in the figure M _j ) and all the other diseases/traits contained in M _j are extracted. Step 2: Module(s) sharing at least one disease with module M _j (in the figure $M_{j^{\prime }}$) are extracted. Step 3: All the other diseases/traits in $M_{j^{\prime }}$ are included in the prediction scheme. Step 4: All proteins associated with the set of $\left\{M_j,M_{j^{\prime }}\right\}$ (in the figure P _{i 1} and P _{i 2}) are extracted. Step 5: All domains contained in the set of {P _{i 1}, P _{i 2}} are included in the prediction scheme. Step 6: All proteins sharing domains with proteins {P _{i 1}, P _{i 2}} are included in the prediction scheme. Step 7: All the other domains in all proteins produced at Step 6 are included in the prediction scheme and the resulting set of domains are called candidate domains