Abstract
A systems biology problem of reconstructing gene regulatory network from time-course gene expression microarray data via network component analysis (NCA) is investigated in this paper. Inspired by the idea that each column of the connectivity matrix can be estimated independently, we try to propose a fast and stable convex approach for nonnegative NCA (nnNCA). Compared with the existing method, our new method reduces the computational cost substantially, whereas maintains a reasonable accuracy. Both the simulation results and experimental results demonstrate the effectiveness of our method.
Chapter PDF
References
Friedman, N., Linial, M., Nachman, I., Peer, D.: Using bayesian networks to analyze expression data. Journal of Computational Biology 7(3), 601–620 (2000)
Shmulevich, I., Dougherty, E.R., Kim, S., Zhang, W.: Probabilistic boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18(2), 261–274 (2002)
Dougherty, E.R., Shmulevich, I., Chen, J., Wang, Z.J.: Genomic Signal Processing and Statistics. Hindawi Publishing Corporation (2005)
Alter, O., Brown, P.O.: Singular value decomposition for genome-wide expression data processing and modeling. Proceedings of the National Academy of Sciences of the United States of America 97(18), 10101–10106 (2000)
Lee, S.I., Batzoglou, S.: Application of independent component analysis to microarrays. Genome Biology 4(11), R76 (2003)
Liao, J.C., Boscolo, R., Yang, Y.L., Tran, L.M., Sabatti, C., Roychowdhury, V.P.: Network component analysis: Reconstruction of regulatory signals in biological systems. Proceedings of the National Academy of Sciences of the United States of America 100(26), 15522–15527 (2003)
Chang, C.Q., Hung, Y.S., Fung, P.C.W., Ding, Z.: Network component analysis for blind source separation. In: Proc. 2006 International Conference on Communications, Circuits and Systems, Guilin, China, pp. 323–326 (2006)
Chang, C.Q., Ding, Z., Hung, Y.S., Fung, P.C.W.: Fast network component analysis for gene regulation networks. In: Proc. 2007 IEEE International Workshop on Machine Learning for Signal Processing, Thesaloniki, Greece, pp. 21–26 (2007)
Lee, T.I., Rinaldi, N.J., Robert, F., Odom, D.T., Bar-Joseph, Z., Gerber, G.K., Hannett, N.M., Harbison, C.T., Thompson, C.M., Simon, I., Zeitlinger, J., Jennings, E.G., Murray, H.L., Gordon, D.B., Ren, B., Wyrick, J.J., Tagne, J.B., Volkert, T.L., Fraenkel, E., Gifford, D.K., Young, R.A.: Transcriptional regulatory networks in saccharomyces cerevisiae. Science 298(5594), 799–804 (2002)
Wang, C., Xuan, J., Chen, L., Zhao, P., Wang, Y., Clarke, R., Hoffman, E.: Motif-directed network component analysis for regulatory network inference. BMC Bioinformatics 9(suppl. 1), S21 (2008)
Chang, C.Q., Ding, Z., Hung, Y.S., Fung, P.C.W.: Fast network component analysis (FastNCA) for gene regulatory network reconstruction from microarray data. Bioinformatics 24(11), 1349–1358 (2008)
Chang, C.Q., Ding, Z., Hung, Y.S.: A new optimization algorithm for network component analysis based on convex programming. In: Proc. 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, Taipei, Taiwan (2009)
Chang, C.Q., Ding, Z., Hung, Y.S.: Nonnegative network component analysis by linear programming for gene regulatory network reconstruction. In: Adali, T., et al. (eds.) ICA 2009. LNCS, vol. 5441, pp. 395–402. Springer, Heidelberg (2009)
Savageau, M.A.: Biochemical Systems Analysis: A Study of Function and Design in Molecular Biology. Addison-Wesley, Reading (1976)
Alon, U.: An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/CRC, Boca Raton (2007)
Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)
Golub, G.H., van Loan, C.F.: Matrix Computation, 3rd edn. The Johns Hopkins University Press (1996)
Lay, D.C.: Linear Algebra and Its Applications, 2nd edn. Addison-Wesley, New York (2000)
Spellman, P.T., Sherlock, G., Zhang, M.Q., Iyer, V.R., Anders, K., Eisen, M.B., Brown, P.O., Botsein, D., Futcher, B.: Comprehensive identification of cell cycleregulated genes of the yeast saccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell 9(12), 3273–3297 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dai, J., Chang, C., Ye, Z., Hung, Y.S. (2009). An Efficient Convex Nonnegative Network Component Analysis for Gene Regulatory Network Reconstruction. In: Kadirkamanathan, V., Sanguinetti, G., Girolami, M., Niranjan, M., Noirel, J. (eds) Pattern Recognition in Bioinformatics. PRIB 2009. Lecture Notes in Computer Science(), vol 5780. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04031-3_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-04031-3_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04030-6
Online ISBN: 978-3-642-04031-3
eBook Packages: Computer ScienceComputer Science (R0)