Protein-Protein Networks Construction and Their Relevance Measurement Based on Multi-Epitope-Ligand-Kartographie and Gene Ontology Data of T-Cell Surface Proteins for Polymyositis

Fang-Zhen      Li; Feng      Gao

doi:10.2174/092986612801619534

Abstract

Polymyositis is an inflammatory myopathy characterized by muscle invasion of T-cells penetrating the basal lamina and displacing the plasma membrane of normal muscle fibers. In order to understand the different adhesive mechanisms at the T-cell surface, Schubert randomly selected 19 proteins expressed at the T-cell surface and studied them using MELK technique [4], among which 15 proteins are picked up for further study by us. Two types of functional similarity networks are constructed for these proteins. The first type is MELK similarity network, which is constructed based on their MELK data by using the McNemar’s test [24]. The second type is GO similarity network, which is constructed based on their GO annotation data by using the RSS method to measuring functional similarity. Then the subset surprisology theory is employed to measure the degree of similarity between two networks. Our computing results show that these two types of networks are high related. This conclusion added new values on MELK technique and expanded its applications greatly.

Keywords: GO, McNemar’s test, MELK, polymyositis, RSS, subset surprisology, proteomics technology, single combinatorial protein patterns (s-CPP), combinatorial protein pattern motifs (CPP-motifs), T-cells