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DEEP - Differential Evolution Entirely Parallel Method for Gene Regulatory Networks

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Parallel Computing Technologies (PaCT 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5698))

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Abstract

DEEP - Differential Evolution Entirely Parallel method is applied to the biological data fitting problem. We introduce a new migration scheme, in which the best member of the branch substitutes the oldest member of the next branch, that provides a high speed of the algorithm convergence. We analyze the performance and efficiency of the developed algorithm on a test problem of finding the regulatory interactions within the network of gap genes that control the development of early Drosophila embryo. The parameters of a set of nonlinear differential equations are determined by minimizing the total error between the model behavior and experimental observations. The age of the individuum is defined by the number of iterations this individuum survived without changes. We used a ring topology for the network of computational nodes. The computer codes are available upon request.

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References

  1. Storn, R., Price, K.: Differential Evolution. A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Technical Report TR-95-012, ICSI (1995)

    Google Scholar 

  2. Fan, H.-Y., Lampinen, J.: A Trigonometric Mutation Operation to Differential Evolution. Journal of Global Optimization 27, 105–129 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  3. Gaemperle, R., Mueller, S.D., Koumoutsakos, P.: A Parameter Study for Differential Evolution. In: Grmela, A., Mastorakis, N.E. (eds.) Advances in Intelligent Systems, Fuzzy Systems, Evolutionary Computation, pp. 293–298. WSEAS Press (2002)

    Google Scholar 

  4. Zaharie, D.: Parameter Adaptation in Differential Evolution by Controlling the Population Diversity. In: Petcu, D., et al. (eds.) Proc. of 4th InternationalWorkshop on Symbolic and Numeric Algorithms for Scientific Computing, Timisoara, Romania, pp. 385–397 (2002)

    Google Scholar 

  5. Tasoulis, D.K., Pavlidis, N.G., Plagianakos, V.P., Vrahatis, M.N.: Parallel differential evolution. In: Congress on Evolutionary Computation (CEC 2004), Portland, Oregon (2004)

    Google Scholar 

  6. Chu, K.-W., Deng, Y., Reinitz, J.: Parallel simulated annealing by mixing of states. Journal of Computational Physics 148, 646–662 (1999)

    Article  MATH  Google Scholar 

  7. Lawrence, P.A.: The Making of a Fly. Blackwell Sci. Publ., Oxford (1992)

    Google Scholar 

  8. Reinitz, J., Sharp, D.: Mechanism of Formation of Eve Stripes. Mechanisms of Development 49, 133–158 (1995)

    Article  Google Scholar 

  9. Jaeger, J., Jaeger, J., Surkova, S., Blagov, M., Janssens, H., Kosman, D., Kozlov, K.N., Manu, Myasnikova, E., Vanario-Alonso, C.E., Samsonova, M., Sharp, D.H., Reinitz, J.: Dynamic control of positional information in the early drosophila embryo. Nature 430, 368–371 (2004)

    Article  Google Scholar 

  10. Pisarev, A., Poustelnikova, E., Samsonova, M., Reinitz, J.: FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution. Nucl. Acids Res. (2008), doi:10.1093/nar/gkn717

    Google Scholar 

  11. Gursky, V.V., Jaeger, J., Kozlov, K.N., Reinitz, J., Samsonov, A.M.: Pattern formation and nuclear divisions are uncoupled in drosophila segmentation: Comparison of spatially discrete and continuous models. PhysicaD 197, 286–302 (2004)

    MATH  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Kozlov, K., Samsonov, A. (2009). DEEP - Differential Evolution Entirely Parallel Method for Gene Regulatory Networks. In: Malyshkin, V. (eds) Parallel Computing Technologies. PaCT 2009. Lecture Notes in Computer Science, vol 5698. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03275-2_13

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  • DOI: https://doi.org/10.1007/978-3-642-03275-2_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03274-5

  • Online ISBN: 978-3-642-03275-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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