Measurement in Biological Systems

Dalibor Štys, Jan Urban, Renata Rychtáriková, Anna Zhyrova, and Petr Císař

University of South Bohemia in Ceske Budejovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Institute of Complex Systems, Zámek 136, 373 33 Nové Hrady, Czech Republic

The system theory of Zampa [1] gives the framework for the analysis of information provided by the measurement. It explains the crucial importance of the system model for understanding of measurement in dynamic systems. Crucial term in this respect is the complete immediate cause  of the consequence

where k and i demarcate time instants at which the measurement is performed and l and j are time instants which make provision for the causality between measurements.

In many technical systems, i.e. electrical or mechanical, we have rather good models which enable us both to determine the extent of time needed for determination of the  and to analyze the causality within intervals between measurements. Non-linear dynamical system may also reach recurrent behaviour which may be in ergodic state [2, 3]  or, in other words, be Lyapunov stable [4].

In the physico-chemical equilibrium systems we assume no system memory, the state of the system does not depend on the path by which it was achieved, i.e.

Biological systems are not in chemical equilibrium and we also do not have good models for their time evolution. They are dynamical self-organized systems, structured outside equilibrium, and for their time evolution we may refer to qualitative simplified models of time evolution of cellular automata [5]. We consider travel through the zone of attraction along which a few well defined, common and structured states are visited and observed. Biological systems such as living cells are re-started before achievement of the recurrent / ergodic state, higher organisms evolve more freely and are “alive” only through their offsprings. Consequences of these findings for measurement in self-organised systems and adequate models will be shown and solutions for adequate reporting of biological systems will be shown [6]. Our findings also explain sources of inconsistences and irreproducibilities in contemporary biology [7, 8].  

1.         P. Zampa, R. Arnošt, in Proc. of the 4th WSEAS conference, Wisconsin, USA (2004)

2.         H. Poincare, Acta Math. Stockh., 13, 17 (1890)

3.         G.D. Birkhoff, Proc. Natl. Acad. Sci. USA, 17 (12), 656{660 (1931)

4.         A.M. Lyapunov, Kharkov Mathematical Society, (1892)

5.         A. Wuensche, Exploring Discrete Dynamics. Luniver Press (2011)

6.         D. Štys, J. Urban, R. Rychtáriková, A. Zhyrova, P. Císař, arXiv:1502.02419

7.         F. Prinz, T. Schlange, K. Asadullah, Believe It or Not: How Much CanWe Rely on Published Data on Potential Drug Targets. Nat. Rev. Drug Discov 10, 712 (2011)

8.         C.G. Begley, L.M. Ellis, Drug Development: Raise Standards for Preclinical Cancer Research, Nature 483, 531{533 (2012)

This work was financially supported by Postdok JU CZ.1.07/2.3.00/30.0006, by the GAJU 134/2013/Z and by the Ministry of Education, Youth and Sports of the Czech Republic projects CENAKVA (No. CZ.1.05/2.1.00/01.0024) and CENAKVA II (No. LO1205 under the NPU I program).