Chapter

Methods of Microarray Data Analysis II

pp 81-90

Extracting Global Structure from Gene Expression Profiles

  • Charless FowlkesAffiliated withDepartments of Computer Science, University of California at Berkeley
  • , Qun ShanAffiliated withMolecular Cell Biology, University of California at Berkeley
  • , Serge BelongieAffiliated withDepartment of Computer Science and Engineering, University of California at San Diego
  • , Jitendra MalikAffiliated withDepartments of Computer Science, University of California at Berkeley

* Final gross prices may vary according to local VAT.

Get Access

Abstract

We have developed a program, GENECUT, for analyzing datasets from gene expression profiling. GENECUT is based on a pairwise clustering method known as Normalized Cut [Shi and Malik, 1997]. GENECUT extracts global structures by progressively partitioning datasets into well-balanced groups, performing an intuitive k-way partitioning at each stage in contrast to commonly used 2-way partitioning schemes. By making use of the Nyström approximation, it is possible to perform clustering on very large genomic datasets.

Key words

gene expression profiles clustering analysis spectral partitioning