Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Proc Natl Acad Sci U S A. 2000 Oct 24;97(22):12079-84.

Coupled two-way clustering analysis of gene microarray data.

Author information

  • 1Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel.

Abstract

We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

PMID:
11035779
[PubMed - indexed for MEDLINE]
PMCID:
PMC17297
Free PMC Article

Images from this publication.See all images (3)Free text

Figure 1
Figure 2
Figure 3
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for HighWire Icon for PubMed Central
    Loading ...
    Write to the Help Desk