Classification of cancer patients using pathway analysis and network clustering

David C Y Fung, Amy Lo, Lucy Jankova, Stephan J. Clarke, Mark Molloy, Graham R. Robertson, Marc R. Wilkins*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    5 Citations (Scopus)


    Molecular expression patterns have often been used for patient classification in oncology in an effort to improve prognostic prediction and treatment compatibility. This effort is, however, hampered by the highly heterogeneous data often seen in the molecular analysis of cancer. The lack of overall similarity between expression profiles makes it difficult to partition data using conventional data mining tools. In this chapter, the authors introduce a bioinformatics protocol that uses REACTOME pathways and patient-protein network structure (also called topology) as the basis for patient classification.

    Original languageEnglish
    Title of host publicationNetwork Biology: Methods and Applications
    EditorsGerard Cagney, Andrew Emili
    Place of PublicationNew York
    PublisherHumana Press
    Number of pages26
    ISBN (Print)9781617792755
    Publication statusPublished - 2011

    Publication series

    NameMethods in Molecular Biology
    ISSN (Print)10643745


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