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)

Abstract

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
Pages311-336
Number of pages26
Volume781
ISBN (Print)9781617792755
DOIs
Publication statusPublished - 2011

Publication series

NameMethods in Molecular Biology
Volume781
ISSN (Print)10643745

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