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Tri-Clustering Analysis for Dissecting Epigenetic Patterns Across Multiple Cancer Types

  • Yanglan Gan
  • Zhiyuan Dong
  • Xia Zhang
  • Guobing Zou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10955)

Abstract

Tumor cells not only harbor genetic and epigenetic alterations, but also are regulated by various epigenetic modifications. Identification of tumor epigenetic similarities across different cancer types is useful for the discovery of treatments that can be extended to different cancers. Nowadays, abundant epigenetic modification profiles have provided good opportunity to achieve this goal. Here, we proposed a tri-clustering approach for integrative pan-cancer epigenomic analysis, named TriPCE. We applied TriPCE to uncover epigenetic mode among seven cancer types. This approach can identify significant cross-cancer epigenetic modification similarities. The associated gene analysis demonstrates strong relevance with cancer development and reveals consistent tendency among cancer types.

Keywords

Tri-clustering Epigenetic pattern Pan-cancer 

Notes

Acknowledgment

This work was supported in part by the Fundamental Research Funds for the Central Universities (2232016A3-05), the National Natural Science Foundation of China (61772128), and Shanghai Natural Science Foundation (17ZR1400200).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Yanglan Gan
    • 1
  • Zhiyuan Dong
    • 1
  • Xia Zhang
    • 2
  • Guobing Zou
    • 2
  1. 1.School of Computer Science and TechnologyDonghua UniversityShanghaiChina
  2. 2.School of Computer Engineering and ScienceShanghai UniversityShanghaiChina

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