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A NEW CLUSTERING METHOD AND ITS APPLICATION TO PROTEOMIC PROFILING FOR COLON CANCER.
Ou, Yongbin; Guo, Lan; Zhang, Cun-Quan.
Affiliation
  • Ou Y; Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310.
  • Guo L; MBR Cancer Center/Department of Community Medicine, West Virginia University, Morgantown, WV 26506-9300.
  • Zhang CQ; Department of Mathematics, West Virginia University, Morgantown, WV 26506-6310.
Article in En | MEDLINE | ID: mdl-26029744
In this paper, we introduce a new clustering method: quasi-clique merger, and its associated data pretreatment programs. This program constructs non-binary hierarchical trees with much smaller number of clusters in the outputs. And overlapping clusters are also allowed in the outputs. We applied this new method to cluster 60 human cancer cell lines (the NCI-60) using the previously identified proteomic determinants for chemosensitivity of 5-Fluorouracil (5-FU). All colon cancer cell lines were aggregated into a single cluster, indicating that the eight proteomic markers are potential diagnostic markers of colon cancer. The results based on the new clustering method have surpassed those based on previous methods on the same datasets.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: IASTED Int Conf Comput Syst Biol (2006) Year: 2006 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: IASTED Int Conf Comput Syst Biol (2006) Year: 2006 Document type: Article Country of publication: United States