bioinformatics approach for pattern of myelin-specific proteins and related human disorders

conclusions the growth rate of information in bioinformatics databases could facilitate studies of live organisms prior to observation studies. two different protein classes could be causative agents of one disease. however, two related diseases from one disease group could consist of different protein classes. future research in the field of proteomics could allow modern insight to reshuffling of proteins in different diseases, and lead to the discovery of the etiology of such diseases. background recent neuroinformatic studies, on the structure-function interaction of proteins, causative agents basis of human disease have implied that dysfunction or defect of different protein classes could be associated with several related diseases. objectives the aim of this study was the use of bioinformatics approaches for understanding the structure, function and relationship of myelin protein 2 (pmp2), a myelin-basic protein in the basis of neuronal disorders. methods a collection of databases for exploiting classification information systematically, including, protein structure, protein family and classification of human disease, based on a new approach was used. knowledge discovery was carried out based on collections criteria and in silico integrative in vitro studies. results the results of the evaluation of bioinformatics comorbid proteomics studies revealed that pmp2, an intracellular and membrane myelin protein, is specific for a neuritis disease and collaborative to other diseases. leprosy, another neuronal disease that could be related to neuritis, consists of interferon gamma (ifng), a secreted protein included various protein classes from what is neuritis.