Abstract
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.
Bibliography
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, 96(6), 2907â2912.
References
28
Referenced
2,062
10.1038/nbt1296-1675
10.1126/science.278.5338.680
10.1038/nbt1297-1359
10.1016/S1097-2765(00)80114-8
10.1126/science.282.5389.699
10.1007/978-1-4612-0921-8
- J Hartigan Clustering Algorithms (Wiley, New York, 1975). / Clustering Algorithms by Hartigan J (1975)
- A E Gordon Classification: Methods for the Exploratory Analysis of Multivariate Data (Chapman & Hall, New York, 1981). / Classification: Methods for the Exploratory Analysis of Multivariate Data by Gordon A E (1981)
10.1109/5.58325
10.1007/978-3-642-97966-8
10.1091/mbc.9.12.3273
10.1073/pnas.95.25.14863
10.1073/pnas.95.1.334
10.2307/2986199
- S Kaski, J Kangas, T Kohonen Neural Comp Surv 1, 102–350 (1997). / Neural Comp Surv by Kaski S (1997)
10.1093/jnci/86.24.1853
10.1016/0377-2217(96)00038-0
10.1046/j.1432-0436.1997.6150321.x
10.1016/S0021-9258(19)49856-6
10.1073/pnas.94.26.14500
10.1093/emboj/16.20.6209
10.1016/0092-8674(91)90113-D
10.1016/0092-8674(91)90112-C
10.1089/dna.1991.10.581
- H Yoshida, K Kitamura, K Tanaka, S Omura, T Miyazaki, T Hachiya, R Ohno, T Naoe Cancer Res 56, 2945–2948 (1996). / Cancer Res by Yoshida H (1996)
10.1016/0022-2836(92)90832-5
10.1038/24628
10.1073/pnas.90.13.6071
Dates
Type | When |
---|---|
Created | 23 years ago (July 26, 2002, 10:39 a.m.) |
Deposited | 3 years, 4 months ago (April 13, 2022, 5:58 p.m.) |
Indexed | 2 weeks, 6 days ago (Aug. 5, 2025, 9 a.m.) |
Issued | 26 years, 5 months ago (March 16, 1999) |
Published | 26 years, 5 months ago (March 16, 1999) |
Published Online | 26 years, 5 months ago (March 16, 1999) |
Published Print | 26 years, 5 months ago (March 16, 1999) |
@article{Tamayo_1999, title={Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation}, volume={96}, ISSN={1091-6490}, url={http://dx.doi.org/10.1073/pnas.96.6.2907}, DOI={10.1073/pnas.96.6.2907}, number={6}, journal={Proceedings of the National Academy of Sciences}, publisher={Proceedings of the National Academy of Sciences}, author={Tamayo, Pablo and Slonim, Donna and Mesirov, Jill and Zhu, Qing and Kitareewan, Sutisak and Dmitrovsky, Ethan and Lander, Eric S. and Golub, Todd R.}, year={1999}, month=mar, pages={2907–2912} }