Abstract
Mutual Information is a measure of correlation between two discrete random variables: the aim of this work is to provide a new definition of Mutual Information using concepts from Fuzzy Sets theory, to extend it to continuous variables. With this approach, we extended the model on which the well known REVEAL algorithm for Reverse Engineering of gene regulatory networks is based and we designed a new flexible version of it, called FuzzyReveal, able to avoid the loss of information caused by the binarization of the continuous biological variables.The predictive power of our new version of the algorithm is promising, being both significantly higher than the one of REVEAL and comparable with a state-of-the-art algorithm on a set of simulated problems.
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
Liang, S., Fuhrman, S., Somogyi, R.: Reveal: a general reverse engineering algorithm for inference of genetic network architectures. In: Pacific Symposium on Biocomputing, pp. 18–29 (1998)
Coletti, G., Scozzafava, R.: Conditional probability, fuzzy sets, and possibility: a unifying view. Fuzzy Sets and Systems 144, 227–249 (2004)
Shannon, C.E.: A mathematical theory of communication. The Bell Systems Technical Journal 27, 379–423 (1948)
Coletti, G., Scozzafava, R.: Probabilistic Logic in a Coherent Setting. Kluwer Academic Publishers, Dordrecht (2002)
Coletti, G., Scozzafava, R.: Conditional probability and fuzzy information. Computational Statistics & Data Analysis 51, 115–132 (2006)
de Finetti, B.: Teoria della Probabilità , Einaudi, Torino (1970)
Reka, A., Barabási, A.L.: Statistical mechanics of complex networks. Reviews of Modern Physics 74, 47–97 (2002)
Grilly, C., Stricker, J., Pang, W.L., et al.: A synthetic gene network for tuning protein degradation in saccharomyces cerevisiae. Mol. Syst. Biol. 3, 127 (2007)
Smith, V.A., Jarvis, E.D., Hartemink, A.J.: Evaluating functional network inference using simulations of complex biological systems. Bioinformatics 18, 216–224 (2002)
Mendes, P., Sha, W., Ye, K.: Artificial gene networks for objective comparison of analysis algorithms. Bioinformatics 19, 122–129 (2003)
Di Camillo, B., Toffolo, G., Cobelli, C.: A gene network simulator to assess reverse engineering algorithms. Ann. N Y Acad. Sci. 1158, 125–142 (2009)
Margolin, A.A., Nemenman, I., Basso, K., Wiggins, C., Stolovitzky, G., Dalla Favera, R., Califano, A.: Aracne: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7 (2006)
Mitra, S., Hayashi, T.: Bioinformatics with soft computing. IEEE Transactions on Systems, Man, and Cybernetics 36, 616–635 (2006)
Zhou, X., Wang, X., Dougherty, E.R., Russ, D., de Suh, E.: Gene clustering based on clusterwide mutual information. Journal of Computational Biology 11, 147–161 (2004)
Maji, P., Pal, K.S.: Fuzzy-rough sets for information measures and selection of relevant genes from microarray data. IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics (2010) (retrieved on April 2010) (to appear)
Xu, F., Miao, D., Wei, L.: Fuzzy-rough attribute reduction via mutual information with an application to cancer classification. Computers and Mathematics with Applications (2008)
Ding, S.F., Xia, S.X., Jin, F.X., Shi, Z.Z.: Novel fuzzy information proximity measures. Journal of Information Science 33, 678–685 (2007)
De Luca, A., Termini, S.: A definition of a non-probabilistic entropy in the setting of fuzzy sets theory. Information and Control 20, 301–312 (1972)
Nam, D., Seo, S., Kim, S.: An efficient top-down search algorithm for learning boolean networks of gene expression. Machine Learning 65, 229–245 (2006)
Sambo, F., Di Camillo, B., Falda, M., Toffolo, G., Badaloni, S.: CNET: an algorithm for the inference of gene regulatory interactions from gene expression time series. In: Proceedings of the 14th Workshop on Intelligent Data Analysis in Medicine and Pharmacology IDAMAP 2009, Verona, Italy, pp. 23–28 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Badaloni, S., Falda, M., Massignan, P., Sambo, F. (2011). Redefinition of Mutual Information in the Fuzzy Sets Framework for Computational Genomics. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2009. Studies in Computational Intelligence, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20206-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-20206-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20205-6
Online ISBN: 978-3-642-20206-3
eBook Packages: EngineeringEngineering (R0)