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


Dive into the research topics of 'Classification of cancer patients using pathway analysis and network clustering'. Together they form a unique fingerprint.

Cite this