Extracting global structure from gene expression profiles

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

We have developed a program, GENECUT, for analyzing datasets from gene expression profiling. GENECUT is based on a pairwise clustering method known as Normalized Cul [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 Nystrom approximation, it is possible to perform clustering on very large genomic datasets.

Original languageEnglish
Title of host publicationMETHODS OF MICROARRAY DATA ANALYSIS II
EditorsSM Lin, KF Johnson
Number of pages10
PublisherKluwer Academic Publishers Group
Publication date2002
Pages81-90
ISBN (Print)1-4020-7111-6
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event2nd Critical Assessment of Microarray Data Analysis (CAMDA 01) - DURHAM, New Caledonia
Duration: 15 Oct 200116 Oct 2001

Conference

Conference2nd Critical Assessment of Microarray Data Analysis (CAMDA 01)
LandNew Caledonia
ByDURHAM
Periode15/10/200116/10/2001

    Research areas

  • gene expression profiles, clustering analysis, spectral partitioning, IMAGE SEGMENTATION, NORMALIZED CUTS, PATTERNS

ID: 302160853