The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Coupled two-way clustering analysis of gene microarray data
Open accessAbstract
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.
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Cites
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
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Biclustering algorithms for biological data analysis: a survey
Madeira, S. C., & Oliveira, A. L. (2004) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2004.2 · Cited by 2,049
Yanai, I., Benjamin, H., Shmoish, M., Chalifa-Caspi, V., Shklar, M., Ophir, R., Bar-Even, A., Horn-Saban, S., Safran, M., Domany, E., et al. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti042 · Cited by 1,300
Self-citationDiscovering statistically significant biclusters in gene expression data
Tanay, A., Sharan, R., & Shamir, R. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s136 · Cited by 855
Automated reverse engineering of nonlinear dynamical systems
Bongard, J., & Lipson, H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609476104 · Cited by 792
Metadata
- Authors
- Getz, G., Levine, E., & Domany, E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2000-10-17
- Volume
- 97
- Issue
- 22
- Pages
- 12079-12084
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2144792853
- Cited by
- 813
- References
- 1
- FWCI
- 12.28
- Type
- journal article
- Language
- en
- Open access
- green
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- Getz, G., Levine, E., & Domany, E. (2000). Coupled two-way clustering analysis of gene microarray data. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.210134797
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