An Algorithm for Initial Fluxes of Metabolic P Systems

Authors

  • Roberto Pagliarini University of Verona, Italy Computer Science Department Strada Le Grazie 15, 37134 Verona, Italy
  • Giuditta Franco University of Verona, Italy Computer Science Department Strada Le Grazie 15, 37134 Verona, Italy
  • Vincenzo Manca Roberto Pagliarini, Giuditta Franco, University of Verona, Italy Computer Science Department Strada Le Grazie 15, 37134 Verona, Italy

Keywords:

Biological modeling, P systems, MP systems, Metabolic flux esti- mation, Heuristic algorithms.

Abstract

A central issue in systems biology is the study of efficient methods inferring fluxes of biological reactions by starting from experimental data. Among the different techniques proposed in the last years, the theory of Metabolic P systems, which is based on the Log-Gain principle, proved to be helpful for deducing biologi- cal fluxes from temporal series of observed dynamics. According to this approach, the algebraic systems provided by the Log-Gain principle determine the reaction fluxes underlying a system dynamics when initial fluxes are known. Here we propose a heuristic algorithm for estimating the initial fluxes, that is tested in two case studies.

References

L. von Bertalanffy. General Systems Theory: Foundations, Developments, Applications. George Braziller Inc, New York, NY, 1967.

L. Bianco, F. Fontana, G. Franco, and V. Manca. P systems for biological dynamics. In [5], 81-126, 2006.

L. Bianco, F. Fontana, and V. Manca. P systems with reaction maps. International Journal of Foundations of Computer Science, 17(1):27-48, February 2006. http://dx.doi.org/10.1142/S0129054106003681

L. Bianco, D. Pescini, P. Siepmann, N. Krasnogor, F.J. Romero-Campero, and M. Gheorghe. To- wards a P Systems Pseudomonas Quorum Sensing Model. Lecture Notes in Computer Science, 4361:197-214, 2007. http://dx.doi.org/10.1007/11963516_13

G. Ciobanu, M. J. Pérez-Jiménez, and G. Păun (Eds.). Applications of Membrane Computing (Natural Computing Series). Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2006.

F. Fontana and V. Manca. Discrete solution to differential equations by metabolic P systems. The- oretical Computer Science, 372:165-182, 2007.

J. S. Huxley. Problems of Relative Growth. 2nd Ed., Dover, New York, 1972.

D. S. Jones and B. D. Sleeman. Differential Equations and Mathematical Biology. Chapman & Hall/CRC, February 2003.

D. G. Luenberger. Optimization by Vector Space Methods, John Wiley & Sons, Inc., 1969.

V. Manca. Log-Gain Principles for Metabolic P Systems, In A. Condon et al. (Eds.), Algorithmic Bioprocesses, CHAPTER 28, Natural Computing Series, Springer-Verlag, Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88869-7_28

V. Manca. The Metabolic Algorithm for P systems: Principles and Applications. Theoretical Computer Science, 404:142-157, 2008. http://dx.doi.org/10.1016/j.tcs.2008.04.015

V. Manca. Fundamentals of metabolic P systems. In G. Păun, G. Rozenberg, and A. Salomaa, editors, Handbook of Membrane Computing, CHAPTER 16. Oxford University Press, 2009. To appear.

V. Manca. Metabolic P dynamics. In G. Păun, G. Rozenberg, and A. Salomaa, editors, Handbook of Membrane Computing, CHAPTER 17. Oxford University Press, 2009. To appear.

V. Manca and L. Bianco. Biological networks in metabolic P systems. BioSystems, 91(3):489-498, 2008. http://dx.doi.org/10.1016/j.biosystems.2006.11.009

V. Manca, L. Bianco, and F. Fontana. Evolution and oscillation in P systems: Applications to biological phenomena. Lecture Notes in Computer Science, 3365:63-84, 2005. http://dx.doi.org/10.1007/978-3-540-31837-8_4

V. Manca, R. Pagliarini, and S. Zorzan. A photosynthetic process modelled by a metabolic P system. Natural Computing, 2009. DOI 10.1007/s11047-008-9104-x. http://dx.doi.org/10.1007/s11047-008-9104-x

G. Nicolis and I. Prigogine. Exploring Complexity. An Introduction. Freeman ans Company, San Francisco, CA, 1989.

G. Păun. Membrane Computing: An Introduction. Springer, 2002. http://dx.doi.org/10.1007/978-3-642-56196-2

G. Păun and G. Rozenberg. A guide to membrane computing. Theoretical Computer Science, 287(1):73-100, September 2002. http://dx.doi.org/10.1016/S0304-3975(02)00136-6

K. S. Scott. Chemical Chaos. Cambridge University Press, Cambridge, UK, 1991.

A. M. Zhabotinsky. Proc. Acc. Sci, USRR. 157:392, 1964.

Published

2009-09-01

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