@phdthesis{Gao2016,
  type      = {Master Thesis},
  author    = {Yantao Gao},
  title     = {Analysis and Classification of Transcription Data for the Detection of Potential Biomarkers in Cancer},
  journal    = {Analyse und Klassifizierung von Transkriptionsdaten f{\"u}r die Detektion von m{\"o}glichen Biomarkern bei Karzinomen},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mit1-opus4-84303},
  year      = {2016},
  abstract  = {Cancer is one of the main causes of death in developed countries, and cancer treatment heavily depends on successful early detection and diagnosis. Tumor biomarkers are helpful for early diagnose. The goal of this discovery method is to identify genetic variations as well as changes in gene expression or activity that can be linked to a typical cancer state. First, several cancer gene signaling pathways were introduced and then combined. 27 candidate genes were selected, through the analysis of several data sets in the GEO database, a few expression difference matrices were established. Those candidate genes were tested in the matrices and found five genes PLA1A, MMP14, CCND1, BIRC5 and MYC that have the potential to be tumor biomarkers. Two of these genes have been further discussed, PLA1A is a potential biomarker for prostate cancer, and MMP14 can be considered as a biomarker for NSC lung cancer. Finally, the significance of this study and the potential value of the two genes are discussed, and the future research in this direction is a prospect.},
  language  = {en}
}