Have a personal or library account? Click to login
Pareto simulated annealing for the design of experiments: illustrated by a gene expression study Cover

Pareto simulated annealing for the design of experiments: illustrated by a gene expression study

Open Access
|Oct 2012

References

  1. [1] G. E. P. Box and N. R Draper. Empirical Model Building and Response Surfaces. New York: J. Wiley & Sons., 1987.
  2. [2] G. E. P. Box, W. G. Hunter, and J. S. Hunter. Statistics for Experimenters. New York: J. Wiley & Sons., 1978.
  3. [3] G. E. P. Box and K. B. Wilson. On the experimental attainment of optimum conditions (with discussion). Journal of the Royal Statistical Society: Series B, 13(1):1{45, 1951.10.1111/j.2517-6161.1951.tb00067.x
  4. [4] P. Czyzak and A. Jaszkiewicz. Pareto simulated annealing-a metaheuristic technique for multiple objective combinatorial optimisation. Journal of Multi- Criteria Decision Analysis, 7:34{47, 1998.10.1002/(SICI)1099-1360(199801)7:1<;34::AID-MCDA161>3.0.CO;2-6
  5. [5] G. F. V. Glonek and P. J. Solomon. Factorial and time course designs for cDNA microarray experiments. Biostatistics, 5:89{111, 2004.10.1093/biostatistics/5.1.89
  6. [6] P. A. Gregory, A. G. Bert, E. L. Paterson, S. C. Barry, A. Tsykin, G. Farshid, M. A. Vadas, Y. Khew-Goodall, and G. J. Goodall. The mir-200 family and mir205 regulate epithelial to mesenchymal transition by targeting zeb1 and sip1. Nature cell biology, 10(5):593{601, 2008.10.1038/ncb1722
  7. [7] A. Jaszkiewicz. Multiple Objective Metaheuristic Algorithms for Combinatorial Optimization. PhD thesis, Poznan University of Technology, Poznan, 2001.
  8. [8] D. Nguyen, A. Arpat, N. Wang, and R. Carroll. DNA microarray experiments: biological and technical aspects. Biometrics, 58:701{717, 2002.
  9. [9] M. Pirlot. General local search methods. European Journal of Operational Re- search, 92:493{511, 1996.10.1016/0377-2217(96)00007-0
  10. [10] R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2010. ISBN 3-900051-07-0.
  11. [11] P. S. Sanchez and G. F. V. Glonek. Optimal designs for two-colour microarray experiments. Biostatistics, 10(3):561{74, 2009.10.1093/biostatistics/kxp012
  12. [12] S. Searle. Linear Models. New York: J. Wiley & Sons., 1971.
  13. [13] G. K. Smyth, Y. H. Yang, and T. Speed. Statistical issues in cDNA microarray data analysis. Methods in Molecular Biology, 224:111{136, 2003.10.1385/1-59259-364-X:111
  14. [14] Y. H. Yang and T. P. Speed. Design and analysis of comparative microarray experiments. In T. P. Speed (Ed.), Statistical analysis of gene expression mi- croarray data. Boca Raton: CRC Press., 2003. 10.1201/9780203011232.ch2
DOI: https://doi.org/10.2478/v10209-011-0011-z | Journal eISSN: 2300-3405 | Journal ISSN: 0867-6356
Language: English
Page range: 199 - 221
Published on: Oct 1, 2012
Published by: Poznan University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2012 Penny Sanchez, Gary Glonek, Andrew Metcalfe, published by Poznan University of Technology
This work is licensed under the Creative Commons License.