13th International Conference on Membrane Computing - MTA Sztaki

MP systems for systems biology
tered these genes in eight types C1, C2, C3, C4, C5, C6, C7, C8, depending on
the kind of time behaviour: linear-quick-up, linear-slow-up, linear-quick-down,
linear-slow-down, parabolic-up, parabolic-down, cubic-up-down, cubic-down-up.
To each cluster an average curve was associated, which constituted the variables
of a dynamical system under investigation. By means of the LGSS algorithm, MP
grammars over these variables were searched for generating the related curves.
The LGSS algorithm was applied with a set of regressors constituted by simple
monomials over the variables. At end, we got a number of possible MP grammars.
One of them had the most reasonable set of regulation maps, according
to the literature about gene regulatory networks. We know that the cancer cell
presents a resistance to the inhibition of the HER2 factor. Can our MP grammar
tell us something about this resistance phenomenon? A deduction, coming
from the obtained grammar, concerned with clusters with cubic behavior C7,
C8. In fact, from the MP grammar we obtained, with a very easy translation
[11], a regulation networks among clusters. In this network it appears clearly
that the HER2 factor promotes C7, while inhibits C8. However, their curves
behave in conflict with the HER2 effect. We interpreted this phenomenon as
a clue of resistance. A deep biological investigation of genes included in these
clusters provided the discovery of a gene having an unknown crucial effect in
this regulatory mechanism.
References
1. Păun G (2000) Computing with membranes. J. Comput. System Sci. 61(1):108-143.
2. Manca V (2008) The metabolic algorithm for P systems: Principles and applications.
Theoretical Computer Science 404:142-155, 2008.
3. Manca V (2010) Fundamentals of Metabolic P Systems. In [5], chap. 19, 475-498.
4. Manca V (2010) Metabolic P Dynamics. In [5], chap. 20, 499-528.
5. Păun G, Rozenberg G, Salomaa A, eds (2010). Handbook of Membrane Computing.
Oxford University Press.
6. Manca V, Marchetti L (2010) Metabolic approximation of real periodical functions.
The Journal of Logic and Algebraic Programming 79:363-373.
7. Manca V, Marchetti L (2010) Goldbeters Mitotic Oscillator Entirely Modeled by
MP Systems. LNCS 6501:273-284.
8. Manca V, Marchetti L (2011) Log-Gain Stoichiometic Stepwise regression for MP
systems. Int. Journal of Foundations of Computer Science, 22(1):97-106.
9. Manca V, Marchetti L, Pagliarini R (2011) MP Modelling of Glucose-Insulin Interactions
in the Intravenous Glucose Tolerance Test. Int. J. of Nat. Comp. Research
2(3):13-24.
10. Manca V, Marchetti L (2012) Solving Dynamical Inverse Problems by means of
Metabolic P Systems. BioSystems, 109, 78-86.
11. Marchetti L, Manca V (2012) A Methodology Based on MP Theory for Gene
Expression Analysis. LNCS 7184: 300-313.
12. Manca V, Bianco L (2008) Biological networks in metabolic P systems. BioSystems
91(3):489-498.
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