title: Mining featured biomarkers associated with prostatic carcinoma based on bioinformatics.
abstract: OBJECTIVE
  To analyze the differentially expressed genes and identify featured biomarkers from prostatic carcinoma.
  
  
  METHODS
  The software "Significance Analysis of Microarray" (SAM) was used to identify the differentially coexpressed genes (DCGs). The DCGs existed in two datasets were analyzed by GO (Gene Ontology) functional annotation.
  
  
  RESULTS
  A total of 389 DCGs were obtained. By GO analysis, we found these DCGs were closely related with the acinus development, TGF-β receptor and signal transduction pathways. Furthermore, five featured biomarkers were discovered by interaction analysis.
  
  
  CONCLUSIONS
  These important signal pathways and oncogenes may provide potential therapeutic targets for prostatic carcinoma.
authors: School of Life Sciences, University of Science and Technology of China , Hefei , China and.
authors: Guanying
authors: G
authors: Piao
authors: Jiarui
authors: J
authors: Wu
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D016022:Case-Control Studies; D019295:Computational Biology; D057225:Data Mining; D063990:Gene Ontology; D052138:Genes, Neoplasm; D006801:Humans; D008297:Male; D058977:Molecular Sequence Annotation; D011379:Prognosis; D011467:Prostate / Q000378:metabolism; D011471:Prostatic Neoplasms / Q000235:genetics / Q000378:metabolism*; D060066:Protein Interaction Maps; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor