Pathway-specific protein domains are predictive for human diseases
Fig 1
Overview of scoring pathway specificity of the protein domains.
(A) A co-pathway protein network was constructed based on similarity of the protein domain profiles (0 and 1 represent absence and presence of each domain, respectively, in the protein). Sub-networks that represent pathway f1, f2, and f3 were enriched for domain d1, d2, and d3, respectively. Probability operating the same pathway is proportional to the edge thickness. (B) Next, each protein received a protein-pathway association (PPA) score for a specific pathway f by sum of edge scores to all member proteins of the pathway f. (C) Domain-pathway association (DPA) score of each domain was assigned by the average PPA of all proteins that harbor the domain. In this example, DPA of domain d3 for pathway f3, DPA3(f3), was assigned by the average of PPA8(f3), PPA9(f3), and PPA10(f3). Gini Index (GI) was used to measure the impurity of the data. (D) Subsequently, pathway specificity (PS) was calculated. In this example, because domain d1, d2, and d3 have high PSs for pathway f1, f2, and f3, respectively, they were classified as pathway-specific domains (PSDs) for the corresponding pathways. However, domain d4 was classified as a non-specific domain (NSD) due to the low PS for all pathways.