Gene Ontology Assisted Exploratory Microarray Clustering and Its Application to Cancer

  • Geoff Macintyre
  • James Bailey
  • Daniel Gustafsson
  • Alex Boussioutas
  • Izhak Haviv
  • Adam Kowalczyk
Conference paper

DOI: 10.1007/978-3-540-88436-1_34

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5265)
Cite this paper as:
Macintyre G., Bailey J., Gustafsson D., Boussioutas A., Haviv I., Kowalczyk A. (2008) Gene Ontology Assisted Exploratory Microarray Clustering and Its Application to Cancer. In: Chetty M., Ngom A., Ahmad S. (eds) Pattern Recognition in Bioinformatics. PRIB 2008. Lecture Notes in Computer Science, vol 5265. Springer, Berlin, Heidelberg

Abstract

Gene expression profiling provides insight into the functions of genes at a molecular level. Clustering of gene expression profiles can facilitate the identification of the underlying driving biological program causing genes’ co-expression. Standard clustering methods, grouping genes based on similar expression values, fail to capture weak expression correlations potentially causing genes in the same biological process to be grouped separately. We have developed a novel clustering algorithm which incorporates functional gene information from the Gene Ontology into the clustering process, resulting in more biologically meaningfull clusters. We have validated our method using a multi-cancer microarray dataset. In addition, we show the potential of such methods for the exploration of cancer etiology.

Keywords

Microarray Gene Ontology Clustering Cancer 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Geoff Macintyre
    • 1
    • 2
  • James Bailey
    • 1
    • 2
  • Daniel Gustafsson
    • 4
  • Alex Boussioutas
    • 3
  • Izhak Haviv
    • 5
    • 6
  • Adam Kowalczyk
    • 2
  1. 1.Department of Computer Science and Software EngineeringUniversity of MelbourneVictoriaAustralia
  2. 2.National ICT AustraliaVictorian Research LabAustralia
  3. 3.Ian Potter Centre for Cancer Genomics and Predictive MedicinePeter MacCallum Cancer CentreEast MelbourneAustralia
  4. 4.Department of Computer Science and Computer EngineeringLa Trobe UniversityVictoriaAustralia
  5. 5.The Alfred Medical Research and Education PrecinctBaker Medical Research Institute, Epigenetics GroupMelbourneAustralia
  6. 6.Department of Biochemistry and Molecular BiologyUniversity of MelbourneVictoriaAustralia

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