title: Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.
abstract: OBJECTIVE
  To identify significant biomarkers for detection of pneumococcal meningitis based on ego network.
  
  
  METHODS
  Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis.
  
  
  RESULTS
  By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively.
  
  
  CONCLUSIONS
  The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.
authors.affiliation: Department of Pediatrics, Jiyang Public Hospital, Jinan, Shandong Province, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Department of Pediatrics, Jiyang Public Hospital, Jinan, Shandong Province, China.
authors.forename: Zhifeng
authors.initials: Z
authors.lastname: Lou
authors.affiliation: Department of Orthopedics, Jiyang Public Hospital, Jinan, Shandong Province, China.
authors.forename: Liansuo
authors.initials: L
authors.lastname: Zhai
authors.affiliation: Department of Neurology, Jiyang Public Hospital, No. 17 Xinyuan Street, Jibei Development Zone, Jiyang Country, Jinan, Shandong Province, 251400, China. haibinzhao82@sina.com.
authors.forename: Haibin
authors.initials: H
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D020869:Gene Expression Profiling / Q000379:methods; D053263:Gene Regulatory Networks / Q000235:genetics; D005819:Genetic Markers; D006801:Humans; D007223:Infant; D008586:Meningitis, Pneumococcal / Q000097:blood / Q000175:diagnosis* / Q000235:genetics; D059467:Transcriptome
chemical_list: D005819:Genetic Markers
keywords: Differential co-expression network; Ego gene; EgoNet algorithm; Pathway; Pneumococcal meningitis