• DocumentCode
    2501933
  • Title

    Common Features Identification of Differently Expressed Genes Related to Endemic Osteoarthritis Disease

  • Author

    Wu, Xiaoming ; Du, Jianqiang ; Wang, Bo ; Liu, Lili ; Wang, Shuang ; Guo, Xiong

  • Author_Institution
    Key Lab. of Biomed. Inf. Eng. of Minist. of Educ., Xi´´an Jiaotong Univ., Xi´´an, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Kashin-Beck disease (KBD) is a chronic, endemic osteochondropathy in China. cDNA microarray techniques were used to select the differentially expressed genes between the healthy and KBD patients. 227 differently expressed genes were used to identify common characteristics. By using GeneMerge anaysis, the common functions of these genes were identified and some of which are related to metal ion binding, such as magnesium ion binding and zinc ion binding. The upstream sequences of these genes were also downloaded from genomic databases and a sequence dataset was constructed. A distance tree was then achieved according to sequences similarity comparing. Finally, 7 gene clusters, each of which contained 2~3 genes with similar function were obtained.
  • Keywords
    diseases; genetics; lab-on-a-chip; medical computing; GeneMerge anaysis; KBD patients; Kashin-Beck disease; cDNA microarray techniques; endemic osteoarthritis disease; gene clusters; genes expression; genomic databases; magnesium ion binding; metal ion binding; osteochondropathy; sequence dataset; zinc ion binding; Biomedical engineering; Blood; Bone diseases; Databases; Degenerative diseases; Fluorescence; Gene expression; Humans; Laboratories; Osteoarthritis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2901-1
  • Electronic_ISBN
    978-1-4244-2902-8
  • Type

    conf

  • DOI
    10.1109/ICBBE.2009.5162527
  • Filename
    5162527