Abstract
We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outliers that interrupt the estimation of accurate gene networks. In addition, some relationships between genes are nonlinear, and linear models thus are not enough for capturing such a complex structure. In this paper, we utilize the moving boxcel median filter and the residual bootstrap for constructing a Bayesian network in order to attain robust estimation of gene networks. We conduct Monte Carlo simulations to examine the properties of the proposed method. We also analyze Saccharomyces cerevisiae cell cycle data as a real data example.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Akutsu, T., Miyano, S., Kuhara, S.: Identification of genetic networks from a small number of gene expression patterns under the Boolean network model. Pac. Symp. Biocomput. 4, 17–28 (1999)
Chen, T., He, H.L., Church, G.M.: Modeling gene expression with differential equations. Pac. Symp. Biocomput. 4, 29–40 (1999)
De Hoon, M.J.L., Imoto, S., Kobayashi, K., Ogasawara, N., Miyano, S.: Inferring gene regulatory networks from time-ordered gene expression data of Bacillus subtilis using differential equations. Pac. Symp. Biocomput. 8, 17–28 (2003)
Efron, B., Tibshirani, R.J.: An Introduction to the Bootstrap. Chapman and Hall/CRC (1993)
Friedman, N., Linial, M., Nachman, I., Pe’er, D.: Using Bayesian network to analyze expression data. J. Comp. Biol. 7, 601–620 (2000)
Hartemink, A.J., Gifford, D.K., Jaakkola, T.S., Young, R.A.: Combining location and expression data for principled discovery of genetic regulatory network models. Pac. Symp. Biocomput. 7, 437–449 (2002)
Horak, C.E., Luscombe, N.M., Qian, J., Bertone, P., Piccirrillo, S., Gerstein, M., Snyder, M.: Complex transcriptional circuitry at the G1/S transition in Saccharomyces cerevisiae. Genes & Development 16, 3017–3033 (2002)
Huberman, J.A.: Cell cycle control of S phase: a comparison of two yeasts. Chromosoma 105, 197–203 (1996)
Imoto, S., Goto, T., Miyano, S.: Estimation of genetic networks and functional structures between genes by using Bayesian network and nonparametric regression. Pac. Symp. Biocomput. 7, 175–186 (2002)
Imoto, S., Kim, S., Goto, T., Aburatani, S., Tashiro, K., Kuhara, S., Miyano, S.: Bayesian network and nonparametric heteroscedastic regression for nonlinear modeling of genetic network. J. Bioinform. Comp. Biol. 1(2), 231–252 (2003)
Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., Miyano, S.: Combining microarrays and biological knowledge for estimating gene networks via Bayesian networks. J. Bioinform. Comp. Biol. 2(1), 77–98 (2004)
Jensen, F.V.: An Introduction to Bayesian Networks. University College London Press (1996)
Marcotte, E.M., Pellegrini, M., Thompson, M.J., Yeates, T.O., Eisenberg, D.: A combined algorithm for genome-wide prediction of protein function. Nature 402, 83–86 (1999)
Nariai, N., Kim, S., Imoto, S., Miyano, S.: Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks. Pac. Symp. Biocomput. 9, 336–347 (2004)
Ott, S., Imoto, S., Miyano, S.: Finding optimal models for small gene networks. Pac. Symp. Biocomput. 9, 557–567 (2004)
Pe’er, D., Regev, A., Elidan, G., Friedman, N.: Inferring subnetworks from perturbed expression profiles. Bioinformatics 17 (ISBM 2001), S215–S224
Pramila, T., Shawna, M., GuhaThakurta, D., Jemiolo, D., Breeden, L.L.: Conserved homeodomain proteins interact with MADS box protein Mcm1 to restrict ECB-dependent transcription to the M/G1 phase of the cell cycle. Genes & Development 16, 3034–3045 (2002)
Segal, E., Wang, H., Koller, D.: Discovering molecular pathways from protein interaction and gene expression data. Bioinformatics 19 (ISMB 2003), i264–i272
Spellman, P.T., Sherlock, G., Zhang, M.Q., Iyer, V.R., Anders, K., Eisen, M.B., Brown, P.O., Botstein, D., Futcher, B.: Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell 9, 3273–3297 (1998)
Tamada, Y., Kim, S., Bannai, H., Imoto, S., Tashiro, K., Kuhara, S., Miyano, S.: Estimating gene networks from gene expression data by combining Bayesian network model with promoter element detection. Bioinformatics (ECCB 2003) 19, 227–236 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Imoto, S., Higuchi, T., Kim, S., Jeong, E., Miyano, S. (2005). Residual Bootstrapping and Median Filtering for Robust Estimation of Gene Networks from Microarray Data. In: Danos, V., Schachter, V. (eds) Computational Methods in Systems Biology. CMSB 2004. Lecture Notes in Computer Science(), vol 3082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25974-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-25974-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25375-4
Online ISBN: 978-3-540-25974-9
eBook Packages: Computer ScienceComputer Science (R0)