The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation
Open accessAbstract
Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets. The first step is to extract the fundamental patterns of gene expression inherent in the data. This paper describes the application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data. The method has been implemented in a publicly available computer package, genecluster , that performs the analytical calculations and provides easy data visualization. To illustrate the value of such analysis, the approach is applied to hematopoietic differentiation in four well studied models (HL-60, U937, Jurkat, and NB4 cells). Expression patterns of some 6,000 human genes were assayed, and an online database was created. genecluster was used to organize the genes into biologically relevant clusters that suggest novel hypotheses about hematopoietic differentiation—for example, highlighting certain genes and pathways involved in “differentiation therapy” used in the treatment of acute promyelocytic leukemia.
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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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Cited by
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Golub, T. R., Slonim, D. K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J. P., Coller, H., Loh, M. L., Downing, J. R., Caligiuri, M. A., et al. (1999) · Science · doi:10.1126/science.286.5439.531 · Cited by 11,516
Self-citationMootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Self-citationMissing Value Estimation Methods for DNA Microarrays
Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., & Altman, R. B. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.6.520 · Cited by 4,230
Model-based analysis of oligonucleotide arrays: Expression index computation and outlier detection.
Li, C., & Wong, W. H. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.1.31 · Cited by 3,133
Metadata
- Authors
- Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E. S., & Golub, T. R.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 1999-03-16
- Volume
- 96
- Issue
- 6
- Pages
- 2907-2912
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2135187880
- Cited by
- 2,923
- References
- 2
- FWCI
- 64.48
- Type
- journal article
- Language
- en
- Open access
- green
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- Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E. S., & Golub, T. R. (1999). Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.96.6.2907
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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