Matrix factorisation methods applied in microarray data analysis

Andrew V. Kossenkov, Michael F. Ochs

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


Numerous methods have been applied to microarray data to group genes into clusters that show similar expression patterns. These methods assign each gene to a single group, which does not reflect the widely held view among biologists that most, if not all, genes in eukaryotes are involved in multiple biological processes and therefore will be multiply regulated. Here, we review several methods of matrix factorisation that identify patterns of behaviour in transcriptional response and assign genes to multiple patterns. We focus on these methods rather than traditional clustering methods applied to microarray data, which assign one gene to one cluster.

Original languageEnglish (US)
Pages (from-to)72-90
Number of pages19
JournalInternational Journal of Data Mining and Bioinformatics
Issue number1
StatePublished - Jan 2010


  • Gene expression
  • Matrix factorisation
  • Microarray
  • MRNAs
  • Statistics

ASJC Scopus subject areas

  • Library and Information Sciences
  • Information Systems
  • Biochemistry, Genetics and Molecular Biology(all)


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