Construction of gene/protein interaction networks and enrichment pathway analysis for paroxysmal nocturnal hemoglobinuria and aplastic anemia

Background:To develop a protein-protein interaction network of Paroxysmal nocturnal hemoglobinuria(PNH)and Aplastic anemia(AA)based on genetic genes and to predict pathways underlying the molecular complexes in the network.Methods:In this research,the PNH and AA-related genes were screened through Online Mendelian Inheritance in Man(OMIM).The plugins and Cytoscape were used to search literature and build a protein-protein interaction network.Results:The protein-protein interaction network contains two molecular complexes that are five higher than the correlation integral values.The target genes of this study were obtained:CD59,STAT3,TERC,TNF,AKT1,C5AR1,EPO,IL6,IL10 and so on.We also found that many factors regulate biological behaviors:neutrophils,macrophages,vascular endothelial growth factor,immunoglobulin,interleukin,cytokine receptor,interleukin-6 receptor,tumor necrosis factor,and so on.This research provides a bioinformatics foundation for further explaining the mechanism of common development of both.Conclusion:This indicates that the PNH and AA is a complex process regulated by many cellular pathways and multiple genes.

EFFICIENT ALGORITHMS FOR IDENTIFYING ORTHOLOGOUS SIMPLE SEQUENCE REPEATS OF DISEASE GENES

Dynamic mutations of simple sequence repeats （SSRs） have been demonstrated to affect normal gene function and cause different genetic disorders. Several conserved and even partial functional SSR patterns are discovered in inherited orthologous disease genes. To explore a wide range of SSRs in genetic diseases, a comprehensive system focusing on identifying orthologous SSRs of disease genes through a comparative genomics mechanism is constructed and accomplished by adopting online Mendelian inheritance in man （OMIM） and NCBI HomoloGene databases as the fundamental resources of human genetic diseases and homologous gene information. In addition, an efficient and effective algorithm for searching SSR patterns is also developed for providing annotated SSR information among various model species. By integrating these data resources and mining technologies, biologists and doctors can systematically retrieve novel and important conserved SSR information among orthologous disease genes. The proposed system, Orthologous SSR for Disease Genes （OSDG）, is the first comprehensive framework for identifying orthologous SSRs as potential causative factors of genetic disorders and is freely available at http：//osdg.cs.ntou.edu.tw/.