Abstracts Keynote & Plenary

essential for mammalian development and health, Perturbation of its dynamics contributes to all
the major disease, including cancer. The discovery by the latestcutting-edging methylomic
approaches and following validation of the epigenetic biomarkers (DNA methylation) in the quality
clinic setting are essential to better stratify the disease and rationale use of therapeutics. In this
presentation, the vital importance of the epigenetic researches to the today’s life science will be
discussed with our own works as paradigms: 1, The potential of DNA methylation biomarker in bodily
fluids for cancer detection and prediction (bladder cancer and lung cancer); 2, the MBD affinity
approaches/the 2nd generation technologies for both low and the sequence resolution methylome in
both health and disease of human; and 3, the first high resolution methylome of the human peripheral
blood mononuclear cells by bisulphite sequencing.
PL-017
Signatures of low-dimensional chaos in the human heartbeat dynamics
Alexander V. Glushkov
ox 24a, Odessa-9, SE, 65009, Ukraine
1,2
1Odessa University, P.O.B
2Russian Academy Sciences, Troitsk, Moscow reg., 142090, Russia
E-mail: glushkov@paco.net
This paper investigates the existence of chaotic behaviour in the human heartbeat dynamics. The
mutual information approach, the correlation integral analysis, the false nearest neighbour algorithm,
the Lyapunov exponents analysis, and the surrogate data method were used in the analysis (the details
of our versions are presented in refs.[1]). In ref. [2] we will firstly adapt the cited methods in the
computational biology and physiology.
The mutual information approach provided
a time lag which is needed to reconstruct phase space. Such
an approach allowed concluding the possible nonlinear nature of process resulting in the heartbeat
amplitudes variations. The correlation dimension method provided a low fractal-dimensional attractor
thus suggesting a possibility of the existence of chaotic behaviour. Based on the attractor dimensions,
the minimum number of variables essential to model the heartbeat amplitudes dynamics for two kinds
of people (absolutely healthy and hypertonic carrier). Significant improvement can be achieved when
additional variables, up to the number of variables sufficient (6), are included in the model. The method
of surrogate data, for detecting nonlinearity, provided significant differences in the correlation
exponents between the original data series and the surrogate data sets. This finding indicates that the
null hypothesis (linear stochastic process) can be rejected. The results from the aforementioned
methods indicate that the heartbeat amplitudes variations exhibits (and hypertonic carrier) a nonlinear
behaviour and possibly low-dimensional chaos. Thus, a short-term prediction based on nonlinear
dynamics is possible. The Lyapunov exponents analysis supported this conclusion. It can be noted that
the nonleading exponents are notoriously difficult to estimate from time series data. Moreover, the
interpretation of inverse Lyapunov exponents as predictability times can results in ambiguous
conclusions. In fact, the degree of instability and predictability can vary considerably throughout phase
space. Though a large number of studies employed the ideas gained from the science of chaos, there
have also been widespread criticisms on the application of chaos theory. Important reasons for this are:
(1) the assumptions with which the chaos identification methods have been developed, i.e. infinite and
noise-free time series; and (2) the inability of the investigative methods to provide irrefutable proof
regarding the existence of chaos. On the one hand, the basis for the criticisms of studies investigating
and reporting existence of chaos in the heartbeat dynamics is our strong belief that they are influenced
by a large number of variables and, therefore, are stochastic. On the other hand, the outcomes of the