Skip to main content
SpringerLink
Log in

Automatic Computational Discovery of Chemical Reaction Networks Using Genetic Programming

  • Chapter
Computational Discovery of Scientific Knowledge

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4660))

Abstract

The concentrations of substances participating in networks of chemical reactions are often modeled by non-linear continuous-time differential equations. Recent work has demonstrated that genetic programming is capable of automatically creating complex networks (such as analog electrical circuits and controllers) whose behavior is modeled by linear and non-linear continuous-time differential equations and whose behavior matches prespecified output values. This chapter demonstrates that it is possible to automatically induce (reverse engineer) a network of chemical reactions from observed time-domain data. Genetic programming starts with observed time-domain concentrations of substances and automatically creates both the topology of the network of chemical reactions and the rates of each reaction of a network such that the behavior of the automatically created network matches the observed time-domain data. Specifically, genetic programming automatically created a network of four chemical reactions that consume glycerol and fatty acid as input, use ATP as a cofactor, and produce diacyl-glycerol as the final product. The network was created from 270 data points. The topology and sizing of the entire network was automatically created using the time-domain concentration values of diacyl-glycerol (the final product). The automatically created network contains three key topological features, including an internal feedback loop, a bifurcation point where one substance is distributed to two different reactions, and an accumulation point where one substance is accumulated from two sources.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Arkin, A., Shen, P., Ross, J.: A test case of correlation metric construction of a reaction pathway from measurements. Science. 277, 1275–1279 (1997)

    Article  Google Scholar 

  • Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetic Programming – An Introduction. Morgan Kaufmann and Heidelberg dpunkt, San Francisco, CA (1998)

    Google Scholar 

  • Barnum, H., Bernstein, H.J., Spector, L.: Quantum circuits for OR and AND of ORs. Journal of Physics A: Mathematical and General 33, 8047–8057 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  • Comisky, W., Yu, J., Koza, J.: Automatic synthesis of a wire antenna using genetic programming. In: Late Breaking Papers at the 2000 Genetic and Evolutionary Computation Conference, Las Vegas, NV, pp. 179–186 (2000)

    Google Scholar 

  • D’haeseleer, P., Wen, X., Fuhrman, S., Somogyi, R.: Linear modeling of mRNA expression levels during CNS development and injury. In: Proceedings of the Pacific Symposium on Biocomputing, pp. 41–52. World Scientific, Island of Hawaii, HI (1999)

    Google Scholar 

  • Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.): Proceedings of the Fifth European Conference on Genetic Programming, Kinsale, Ireland. Springer, Heidelberg (2002)

    Google Scholar 

  • Holland, J.H.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, 2nd edn. The MIT Press, Cambridge (1992)

    Google Scholar 

  • Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  • Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge (1994a)

    MATH  Google Scholar 

  • Koza, J.R.: Genetic Programming II Videotape: The Next Generation. MIT Press, Cambridge (1994b)

    Google Scholar 

  • Koza, J.R., Banzhaf, W., Chellapilla, K., Deb, K., Dorigo, M., Fogel, D.B., Garzon, M.H., Goldberg, D.E., Iba, H., Riolo, R.: Proceedings of the Third Annual Conference on Genetic Programming. Morgan Kaufmann, Madison (1998)

    Google Scholar 

  • Koza, J.R., Bennett, F.H., Andre, D., Keane, M.A.: Genetic Programming III: Darwinian Invention and Problem Solving. Morgan Kaufmann, San Francisco (1999a)

    MATH  Google Scholar 

  • Koza, J.R., Bennett, F.H, Andre, D., Keane, M.A., Brave, S.: Genetic Programming III Videotape: Human-Competitive Machine Intelligence. Morgan Kaufmann, San Francisco (1999b)

    Google Scholar 

  • Koza, J.R., Bennett, F.H., Stiffelman, O.: Genetic programming as a Darwinian invention machine. In: Proceedings of the Second European Workshop on Genetic Programming, Göteborg, Sweden, pp. 93–108. Springer, Heidelberg (1999c)

    Google Scholar 

  • Koza, J.R., Keane, M.A., Yu, J., Bennett, F.H., Mydlowec, W.: Automatic creation of human-competitive programs and controllers by means of genetic programming. Genetic Programming and Evolvable Machines 1, 121–164 (2000)

    Article  MATH  Google Scholar 

  • Koza, J.R., Keane, M.A., Yu, J., Bennett, F.H., Mydlowec, W., Stiffelman, O.: Automatic synthesis of both the topology and parameters for a robust controller for a non-minimal phase plant and a three-lag plant by means of genetic programming. In: Proceedings of the Thirtyeighth Conference on Decision and Control, Phoenix, AZ, pp. 5292–5300 (1999d)

    Google Scholar 

  • Koza, J.R., Mydlowec, W., Lanza, G., Yu, J., Keane, M.A.: Reverse Engineering and Automatic Synthesis of Metabolic Pathways from Observed Data Using Genetic Programming. Stanford Medical Informatics Technical Report SMI-2000-0851 (2000)

    Google Scholar 

  • Koza, J.R., Rice, J.P.: Genetic Programming: The Movie. MIT Press, Cambridge (1992)

    Google Scholar 

  • Laing, S., Fuhrman, S., Somogyi, R.: REVEAL: A general reverse engineering algorithm for inference of genetic network architecture. In: Proceedings of the Pacific Symposium on Biocomputing, pp. 18–29. World Scientific, Maui, HI (1998)

    Google Scholar 

  • Langdon, W.B.: Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming! Kluwer, Amsterdam (1998)

    Google Scholar 

  • Loomis, W.F., Sternberg, P.W.: Genetic networks. Science 269, 649 (1995)

    Article  Google Scholar 

  • McAdams, H.H., Shapiro, L.: Circuit simulation of genetic networks. Science 269, 650–656 (1995)

    Article  Google Scholar 

  • Mendes, P., Kell, D.B.: Non-linear optimization of biochemical pathways: Applications to metabolic engineering and parameter estimation. Bioinformatics 14, 869–883 (1998)

    Article  Google Scholar 

  • Mittenthal, J.E., Ao, Y., Bertrand, C., Scheeline, A.: Designing metabolism: Alternative connectivities for the pentose phosphate pathway. Bulletin of Mathematical Biology 60, 815–856 (1998)

    Article  MATH  Google Scholar 

  • Ptashne, M.: A Genetic Switch: Phage λ and Higher Organisms, 2nd edn. Cell Press and Blackwell Scientific Publications, Cambridge (1992)

    Google Scholar 

  • Quarles, T., Newton, A.R., Pederson, D.O., Sangiovanni-Vincentelli, A.: SPICE 3 Version 3F5 User’s Manual. Department of Electrical Engineering and Computer Science, University of California. Berkeley, CA (1994)

    Google Scholar 

  • Spector, L., Barnum, H., Bernstein, H.J.: Genetic programming for quantum computers. In: Proceedings of the Third Annual Conference on Genetic Programming, pp. 365–373. Morgan Kaufmann, Madison (1998)

    Google Scholar 

  • Spector, L., Barnum, H., Bernstein, H.J.: Quantum computing applications of genetic programming. In: Advances in Genetic Programming 3, pp. 135–160. MIT Press, Cambridge (1999a)

    Google Scholar 

  • Spector, L., Barnum, H., Bernstein, H.J., Swamy, N.: Finding a better-than-classical quantum AND/OR algorithm using genetic programming. In: Proceedings of the 1999 Congress on Evolutionary Computation, pp. 2239–2246. IEEE Press, Washington (1999b)

    Chapter  Google Scholar 

  • Spector, L., Langdon, W.B., O’Reilly, U., Angeline, P.: Advances in Genetic Programming 3. MIT Press, Cambridge (1999c)

    Google Scholar 

  • Spector, L., Goodman, E., Wu, A., Langdon, W.B., Voigt, H.-M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M., Burke, E.: Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann Publishers, San Francisco (2001)

    Google Scholar 

  • Sterling, T.L., Salmon, J., Becker, D.J., Savarese, D.F.: How to Build a Beowulf: A Guide to Implementation and Application of PC Clusters. MIT Press, Cambridge (1999)

    Google Scholar 

  • Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T.S., Matsuzaki, Y., Miyoshi, F., Saito, K., Tanida, S., Yugi, K., Venter, J.C., Hutchison, C.A.: E-CELL: Software environment for whole cell simulation. Bioinformatics 15, 72–84 (1999)

    Article  Google Scholar 

  • Voit, E.O.: Computational Analysis of Biochemical Systems. Cambridge University Press, Cambridge (2000)

    Google Scholar 

  • Yuh, C.-H., Bolouri, H., Davidson, E.H.: Genomic cis-regulatory logic: Experimental and computational analysis of a sea urchin gene. Science. 279, 1896–1902 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biomedical Informatics, Department of Medicine, Department of Electrical Engineering, Stanford University, Stanford, California, USA

    John R. Koza

  2. Genetic Programming Inc., Los Altos, California, USA

    William Mydlowec, Guido Lanza & Jessen Yu

  3. Econometrics Inc., Chicago, Illinois, USA

    Martin A. Keane

Authors
  1. John R. Koza
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. William Mydlowec
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guido Lanza
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jessen Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Martin A. Keane
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Sašo Džeroski Ljupčo Todorovski

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Koza, J.R., Mydlowec, W., Lanza, G., Yu, J., Keane, M.A. (2007). Automatic Computational Discovery of Chemical Reaction Networks Using Genetic Programming. In: Džeroski, S., Todorovski, L. (eds) Computational Discovery of Scientific Knowledge. Lecture Notes in Computer Science(), vol 4660. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73920-3_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-73920-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73919-7

  • Online ISBN: 978-3-540-73920-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation