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Figure 2 | Journal of Translational Medicine

Figure 2

From: Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions

Figure 2

Similarity of disease-related PPIs and disease-comorbidity network. A. p values of disease–disease PPI similarity (μ(d i , d j )) matrix computed by ICod. B. Generated background distribution of similarity values via random permutation tests. C. Disease similarity network consisting of nodes of disease PPIs and edges of similarity values. In the present study, five diseases (T2DM, obesity, prostate cancer, colon cancer, and breast cancer) and three pathological conditions (immune response, inflammation, and insulin resistance) were analyzed. Housekeeping and essential gene-related PPIs were regarded as a control set of nondisease conditions. D. Phenomic-level disease and pathological symptom co-occurring networks based on US Medicare data. Because the clinical records utilized diagnostic codes from ICD9-CM (International Classification of Diseases, 9th Revision, Clinical Modification) to determine the disease or pathological state of patients, we manually assigned the relevant names of diseases, such as prostate cancer and obesity, to the reported codes of ICD9-CM.

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