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An integrated method for the identification of novel genes related to oral cancer

Author

Listed:
  • Lei Chen
  • Jing Yang
  • Zhihao Xing
  • Fei Yuan
  • Yang Shu
  • YunHua Zhang
  • XiangYin Kong
  • Tao Huang
  • HaiPeng Li
  • Yu-Dong Cai

Abstract

Cancer is a significant public health problem worldwide. Complete identification of genes related to one type of cancer facilitates earlier diagnosis and effective treatments. In this study, two widely used algorithms, the random walk with restart algorithm and the shortest path algorithm, were adopted to construct two parameterized computational methods, namely, an RWR-based method and an SP-based method; based on these methods, an integrated method was constructed for identifying novel disease genes. To validate the utility of the integrated method, data for oral cancer were used, on which the RWR-based and SP-based methods were trained, thereby building two optimal methods. The integrated method combining these optimal methods was further adopted to identify the novel genes of oral cancer. As a result, 85 novel genes were inferred, among which eleven genes (e.g., MYD88, FGFR2, NF-κBIA) were identified by both the RWR-based and SP-based methods, 70 genes (e.g., BMP4, IFNG, KITLG) were discovered only by the RWR-based method and four genes (L1R1, MCM6, NOG and CXCR3) were predicted only by the SP-based method. Extensive analyses indicate that several novel genes have strong associations with cancers, indicating the effectiveness of the integrated method for identifying disease genes.

Suggested Citation

  • Lei Chen & Jing Yang & Zhihao Xing & Fei Yuan & Yang Shu & YunHua Zhang & XiangYin Kong & Tao Huang & HaiPeng Li & Yu-Dong Cai, 2017. "An integrated method for the identification of novel genes related to oral cancer," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-25, April.
    • Handle: RePEc:plo:pone00:0175185
    DOI: 10.1371/journal.pone.0175185
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    References listed on IDEAS

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    1. Lei Chen & Wei-Ming Zeng & Yu-Dong Cai & Kai-Yan Feng & Kuo-Chen Chou, 2012. "Predicting Anatomical Therapeutic Chemical (ATC) Classification of Drugs by Integrating Chemical-Chemical Interactions and Similarities," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, April.
    2. Stephen Oliver, 2000. "Guilt-by-association goes global," Nature, Nature, vol. 403(6770), pages 601-602, February.
    3. Lele Hu & Tao Huang & Xiaohe Shi & Wen-Cong Lu & Yu-Dong Cai & Kuo-Chen Chou, 2011. "Predicting Functions of Proteins in Mouse Based on Weighted Protein-Protein Interaction Network and Protein Hybrid Properties," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-10, January.
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