The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
CLICK and EXPANDER: a system for clustering and visualizing gene expression data
Open accessAbstract
Motivation: Microarrays have become a central tool in biological research. Their applications range from functional annotation to tissue classification and genetic network inference. A key step in the analysis of gene expression data is the identification of groups of genes that manifest similar expression patterns. This translates to the algorithmic problem of clustering genes based on their expression patterns. Results: We present a novel clustering algorithm, called CLICK, and its applications to gene expression analysis. The algorithm utilizes graph-theoretic and statistical techniques to identify tight groups (kernels) of highly similar elements, which are likely to belong to the same true cluster. Several heuristic procedures are then used to expand the kernels into the full clusters. We report on the application of CLICK to a variety of gene expression data sets. In all those applications it outperformed extant algorithms according to several common figures of merit. We also point out that CLICK can be successfully used for the identification of common regulatory motifs in the upstream regions of co-regulated genes. Furthermore, we demonstrate how CLICK can be used to accurately classify tissue samples into disease types, based on their expression profiles. Finally, we present a new java-based graphical tool, called EXPANDER, for gene expression analysis and visualization, which incorporates CLICK and several other popular clustering algorithms. Availability: http://www.cs.tau.ac.il/~rshamir/expander/expander.html
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Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
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
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205
Whitfield, M. L., Sherlock, G., Saldanha, A. J., Murray, J. I., Ball, C. A., Alexander, K. E., Matese, J. C., Perou, C. M., Hurt, M. M., Brown, P. O., et al. (2002) · Molecular Biology of the Cell · doi:10.1091/mbc.02-02-0030 · Cited by 1,527
Jelinsky, S. A., Estep, P., Church, G. M., & Samson, L. D. (2000) · Molecular and Cellular Biology · doi:10.1128/mcb.20.21.8157-8167.2000 · Cited by 335 · cited 2×
“We analyzed the data set published by Jelinsky et al. (2000).”
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Cited by
A systematic comparison and evaluation of biclustering methods for gene expression data
Prelić, A., Bleuler, S., Zimmermann, P., Wille, A., Bühlmann, P., Gruissem, W., Hennig, L., Thiele, L., & Zitzler, E. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl060 · Cited by 910
Identification and classification of chromosomal aberrations in human induced pluripotent stem cells
Mayshar, Y., Ben-David, U., Lavon, N., Biancotti, J.-C., Yakir, B., Clark, A. T., Plath, K., Lowry, W. E., & Benvenisty, N. (2010) · Cell stem cell · doi:10.1016/j.stem.2010.07.017 · Cited by 756
Zhang, Y.-C., Liao, J.-Y., Li, Z.-Y., Yu, Y., Zhang, J.-P., Li, Q.-F., Qu, L.-H., Shu, W.-S., & Chen, Y.-Q. (2014) · Genome Biology · doi:10.1186/s13059-014-0512-1 · Cited by 554
EXPANDER – an integrative program suite for microarray data analysis
Shamir, R., Maron-Katz, A., Tanay, A., Linhart, C., Steinfeld, I., Sharan, R., Shiloh, Y., & Elkon, R. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-232 · Cited by 340
Self-citationGerhauser, C., Favero, F., Risch, T., Simon, R., Feuerbach, L., Assenov, Y., Heckmann, D., Sidiropoulos, N., Waszak, S. M., Hübschmann, D., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.10.016 · Cited by 293
Metadata
- Authors
- Sharan, R., Maron-Katz, A., & Shamir, R.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-09-22
- Volume
- 19
- Issue
- 14
- Pages
- 1787-1799
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- OpenAlex
- W2109174028
- Cited by
- 370
- References
- 6
- FWCI
- 6.86
- Type
- journal article
- Language
- en
- Open access
- bronze
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