Chaos: principles and implications in biology

In this paper we review some of the basic principles of thetheory of dynamical systems. We introduce the reader to thedefinition of chaos and strange attractors and we discuss theirimplications in biology. Received on June 9, 1988; accepted on October 24, 1988     

Problems in estimating the dimensions of strange attractors in the analysis of biophysical data

Basic algorithms of calculating the dimensions of strange attractors from experimental data are considered. A special emphasis is placed on difficulties arising when the methods of solution of the reverse nonlinear dynamic problem are used in the analysis of the behavior of biological systems. These difficulties are associated with a poor convergence and weak stability of estimated values as well as a low degree of statistical confidence. Factors that hamper the estimation of strange attractor dimensions with reasonable accuracy are discussed by the example of analysis of human electrocardiograms. A method for the statistcal estimation of dimensions of attractors is proposed based on multidimensional imitational modeling.     

DNA Codes and Information: Formal Structures and Relational Causes

Recently the terms "codes" and "information" as used in the context of molecular biology have been the subject of much discussion. Here I propose that a variety of structural realism can assist us in rethinking the concepts of DNA codes and information apart from semantic criteria. Using the genetic code as a theoretical backdrop, a necessary distinction is made between codes qua symbolic representations and information qua structure that accords with data. Structural attractors are also shown to be entailed by the mapping relation that any DNA code is a part of (as the domain). In this framework, these attractors are higher-order informational structures that obviate any "DNA-centric" reductionism. In addition to the implications that are discussed, this approach validates the array of coding systems now recognized in molecular biology.     

Mesoscopic biochemical basis of isogenetic inheritance and canalization: stochasticity, nonlinearity, and emergent landscape

Biochemical reaction systems in mesoscopic volume, under sustained environmental chemical gradient(s), can have multiple stochastic attractors. Two distinct mechanisms are known for their origins: (a) Stochastic single-molecule events, such as gene expression, with slow gene on-off dynamics; and (b) nonlinear networks with feedbacks. These two mechanisms yield different volume dependence for the sojourn time of an attractor. As in the classic Arrhenius theory for temperature dependent transition rates, a landscape perspective provides a natural framework for the system's behavior. However, due to the nonequilibrium nature of the open chemical systems, the landscape, and the attractors it represents, are all themselves emergent properties of complex, mesoscopic dynamics. In terms of the landscape, we show a generalization of Kramers' approach is possible to provide a rate theory. The emergence of attractors is a form of self-organization in the mesoscopic system; stochastic attractors in biochemical systems such as gene regulation and cellular signaling are naturally inheritable via cell division. Delbrück-Gillespie's mesoscopic reaction system theory, therefore, provides a biochemical basis for spontaneous isogenetic switching and canalization.     

Boolean dynamics of biological networks with multiple coupled feedback loops

Boolean networks have been frequently used to study the dynamics of biological networks. In particular, there have been various studies showing that the network connectivity and the update rule of logical functions affect the dynamics of Boolean networks. There has been, however, relatively little attention paid to the dynamical role of a feedback loop, which is a circular chain of interactions between Boolean variables. We note that such feedback loops are ubiquitously found in various biological systems as multiple coupled structures and they are often the primary cause of complex dynamics. In this article, we investigate the relationship between the multiple coupled feedback loops and the dynamics of Boolean networks. We show that networks have a larger proportion of basins corresponding to fixed-point attractors as they have more coupled positive feedback loops, and a larger proportion of basins for limit-cycle attractors as they have more coupled negative feedback loops.     

Autogenous Formation of Spiral Waves by Coupled Chaotic Attractors

When large arrays of strange attractors are coupled diffusively through one of the variables, chaotic systems become periodic and form large archimedean spirals or concentric bands. This observation may have importance for many applications in the field of deterministic chaos and seems particularly relevant to the question of the formal temporal structure of the biological clock in metazoan organisms. In particular, although individual cellular oscillators, as manifested in the cell cycle, may have deep basins of attraction and appear to be more or less periodic, we suggest that cells oscillate with chaotic dynamics in the ultradian domain. Only when large aggregates of these cells are tightly coupled can a precise circadian clock emerge. For changing coupling strength or parameter values, period increase occurs through quantal or integral multiple increments of the fundamental. All calculations were implemented on a 386AT, using a Mercury MC6400 floating point processor.     

Autogenous Formation of Spiral Waves by Coupled Chaotic Attractors

When large arrays of strange attractors are coupled diffusively through one of the variables, chaotic systems become periodic and form large archimedean spirals or concentric bands. This observation may have importance for many applications in the field of deterministic chaos and seems particularly relevant to the question of the formal temporal structure of the biological clock in metazoan organisms. In particular, although individual cellular oscillators, as manifested in the cell cycle, may have deep basins of attraction and appear to be more or less periodic, we suggest that cells oscillate with chaotic dynamics in the ultradian domain. Only when large aggregates of these cells are tightly coupled can a precise circadian clock emerge. For changing coupling strength or parameter values, period increase occurs through quantal or integral multiple increments of the fundamental. All calculations were implemented on a 386AT, using a Mercury MC6400 floating point processor.     

Correlations in one-dimensional fully developed chaos

Correlations in the baker map and the tent map as examples of one-dimensional, fully developed chaos are considered. It is shown, utilizing symbolic dynamical systems derived from these maps, that the vanishing second-order correlation function is not sufficient to guarantee uncorrelatedness. Importance of the higher-order, especially third-order, correlation functions is emphasized for chaotic systems. In search of the quantities that grasp correlational behaviors as a whole in chaotic systems, it is proposed to use the fixed-separation correlation integral, which is a modified quantity of the usual correlation integral devised to calculate the fractal dimension of strange attractors, for these maps. It is shown that the new quantity contains all the even-number orders of autocorrelation function that are commonly considered.     

Statistical properties of flip-flop processes associated to the chaotic behavior of systems with strange attractors

The chaotic behavior of systems with strange attractors can be discussed by examining the flip-flop process associated to the system dynamics. This was already shown by Lorenz (1963) in his first seminal paper. A somewhat surprising result was obtained by Aizawa (1982), who, studying the same Lorenz attractor at the parameter valuer=28, reached the conclusion that the associated flip-flop was a typical Markov process. Since the process is generated in a deterministic way, one may wonder if the Aizawa result is accidental, depending on the particular parameter value, or if a similar conclusion can be extended to other systems, with different attractors. Our conclusions are that the Aizawa result is mostly accidental, because for other parameter values and for other attractors there are sharp deviations from the Markovian process.     

Numerical simulation of collapsible-tube flows with sinusoidal forced oscillations

Collapsible-tube flow with self-excited oscillations has been extensively investigated. Though physiologically relevant, forced oscillation coupled with self-excited oscillation has received little attention in this context. Based on an ODE model of collapsible-tube flow, the present study applies modern dynamics methods to investigate numerically the responses of forced oscillation to a limit-cycle oscillation which has topological characteristics discovered in previous unforced experiments. A devil's staircase and period-doubling cascades are presented with forcing frequency and amplitude as control parameters. In both cases, details are provided in a bifurcation diagram. Poincaré sections, a frequency spectrum and the largest Lyapunov exponents verify the existence of chaos in some circumstances. The thin fractal structure found in the strange attractors is believed to be a result of high damping and low stiffness in such systems.     

The dynamic systems approach to control and regulation of intracellular networks

Systems theory and cell biology have enjoyed a long relationship that has received renewed interest in recent years in the context of systems biology. The term 'systems' in systems biology comes from systems theory or dynamic systems theory: systems biology is defined through the application of systems- and signal-oriented approaches for an understanding of inter- and intra-cellular dynamic processes. The aim of the present text is to review the systems and control perspective of dynamic systems. The biologist's conceptual framework for representing the variables of a biochemical reaction network, and for describing their relationships, are pathway maps. A principal goal of systems biology is to turn these static maps into dynamic models, which can provide insight into the temporal evolution of biochemical reaction networks. Towards this end, we review the case for differential equation models as a 'natural' representation of causal entailment in pathways. Block-diagrams, commonly used in the engineering sciences, are introduced and compared to pathway maps. The stimulus-response representation of a molecular system is a necessary condition for an understanding of dynamic interactions among the components that make up a pathway. Using simple examples, we show how biochemical reactions are modelled in the dynamic systems framework and visualized using block-diagrams.     

Coated-vesicle formation in vitro: conflicting results using different assays

Cell-free systems provide essential tools for elucidating the molecular mechanisms underlying complex cellular processes such as vesicular transport. The biochemical utility of these model systems is strengthened by assays that allow rapid, quantitative detection of the events being studied. Two model systems have recently been developed to reconstitute coated-vesicle budding, and two different biochemical assays are used to detect this event. Striking differences in the biochemical requirements for 'coated-vesicle budding' are detected by these two assays, suggesting that two distinct events are being measured. These findings have wide implications for the use of cell-free assay systems in cell biology.     

Circular causality in integrative multi-scale systems biology and its interaction with traditional medicine

This paper discusses the concept of circular causality in “biological relativity” (Noble, Interface Focus. 2, 56-64, 2012) in the context of integrative and multi-scale systems approaches to biology. It also discusses the relationship between systems biology and traditional medicine (sometimes called scholarly medical traditions) mainly from East Asia and India. Systems biology helps illuminate circular processes identified in traditional medicine, while the systems concept of attractors in complex systems will also be important in analysing dynamic balance in the body processes that traditional medicine is concerned with. Ways of nudging disordered processes towards good attractors through the use of traditional medicines can lead to the development of new ways not only of curing disease but also of its prevention. Examples are given of cost-effective multi-component remedies that use integrative ideas derived from traditional medicine.     

Two-patch dispersal-linked compensatory-overcompensatory spatially discrete population models

We study the role of asynchronous and synchronous dispersals on discrete-time two-patch dispersal-linked population models, where the pre-dispersal local patch dynamics are of mixed compensatory and overcompensatory types. Single-species dispersal-linked models behave as single-species single-patch models whenever all pre-dispersal local patch dynamics are compensatory and dispersal is synchronous. However, the dynamics of the corresponding two-patch population model connected by asynchronous dispersal depends on the dispersal rates. The species goes extinct on at least one patch when the asynchronous dispersal rates are high, while it persists when the rates are low. We use numerical simulations to show that in both synchronous and asynchronous mixed compensatory and overcompensatory systems, symmetric and asymmetric dispersals can control and impede the onset of cyclic population oscillations via period-doubling reversal bifurcations. Also, we show that in mixed systems both asynchronous and synchronous dispersals are capable of altering the pre-dispersal local patch dynamics from overcompensatory to compensatory dynamics. Dispersal-linked population models with 'unstructured' overcompensatory pre-dispersal local dynamics connected by synchronous dispersal can generate multiple attractors with fractal basin boundaries. However, mixed compensatory and overcompensatory systems appear to exhibit single attractors and not coexisting (multiple) attractors.     

Two-patch dispersal-linked compensatory-overcompensatory spatially discrete population models

We study the role of asynchronous and synchronous dispersals on discrete-time two-patch dispersal-linked population models, where the pre-dispersal local patch dynamics are of mixed compensatory and overcompensatory types. Single-species dispersal-linked models behave as single-species single-patch models whenever all pre-dispersal local patch dynamics are compensatory and dispersal is synchronous. However, the dynamics of the corresponding two-patch population model connected by asynchronous dispersal depends on the dispersal rates. The species goes extinct on at least one patch when the asynchronous dispersal rates are high, while it persists when the rates are low. We use numerical simulations to show that in both synchronous and asynchronous mixed compensatory and overcompensatory systems, symmetric and asymmetric dispersals can control and impede the onset of cyclic population oscillations via period-doubling reversal bifurcations. Also, we show that in mixed systems both asynchronous and synchronous dispersals are capable of altering the pre-dispersal local patch dynamics from overcompensatory to compensatory dynamics. Dispersal-linked population models with ‘unstructured’ overcompensatory pre-dispersal local dynamics connected by synchronous dispersal can generate multiple attractors with fractal basin boundaries. However, mixed compensatory and overcompensatory systems appear to exhibit single attractors and not coexisting (multiple) attractors.     

Complex behaviour in four species food-web model

A four-dimensional food-web system consisting of a bottom prey, two middle predators and a generalist predator has been developed with modified functional response. The system is well posed and dissipative. Some results on uniform persistence have been developed. The dynamics of the system is found to be chaotic for certain choice of parameters. The coexistence of all four species is possible in the form of periodic orbits/strange attractors for suitably chosen set of parameters.     

Complex behaviour in four species food-web model

A four-dimensional food-web system consisting of a bottom prey, two middle predators and a generalist predator has been developed with modified functional response. The system is well posed and dissipative. Some results on uniform persistence have been developed. The dynamics of the system is found to be chaotic for certain choice of parameters. The coexistence of all four species is possible in the form of periodic orbits/strange attractors for suitably chosen set of parameters.     

Dynamics of unperturbed and noisy generalized Boolean networks

For years, we have been building models of gene regulatory networks, where recent advances in molecular biology shed some light on new structural and dynamical properties of such highly complex systems. In this work, we propose a novel timing of updates in random and scale-free Boolean networks, inspired by recent findings in molecular biology. This update sequence is neither fully synchronous nor asynchronous, but rather takes into account the sequence in which genes affect each other. We have used both Kauffman's original model and Aldana's extension, which takes into account the structural properties about known parts of actual GRNs, where the degree distribution is right-skewed and long-tailed. The computer simulations of the dynamics of the new model compare favorably to the original ones and show biologically plausible results both in terms of attractors number and length. We have complemented this study with a complete analysis of our systems’ stability under transient perturbations, which is one of biological networks defining attribute. Results are encouraging, as our model shows comparable and usually even better behavior than preceding ones without loosing Boolean networks attractive simplicity.     

Problems of biomimetic chemistry]

The main goals of biomimetic chemistry have been formulated on the basis of the concept of biochemical organization. Biomimetic chemistry is defined as a science which employs the principles of biochemical organization (i. e., the principles of structural organization, functioning and regulation of biological systems at the levels corresponding to biomacromolecules, supramolecular complexes and subcellular structures) for the construction of artificial systems with predetermined properties or for conferring desired properties on natural biochemical systems with the help of artificial elements. The relationships between biomimetics and biochemical modelling are discussed. As examples of biomimetic systems, some enzymes entrapped into hydrated reverse micelles of a surfactant in an organic solvent and conjugates of proteins with polyalkylene oxidases are considered.     

Applications and trends in systems biology in biochemistry

Systems biology has received an ever increasing interest during the last decade. A large amount of third-party funding is spent on this topic, which involves quantitative experimentation integrated with computational modeling. Industrial companies are also starting to use this approach more and more often, especially in pharmaceutical research and biotechnology. This leads to the question of whether such interest is wisely invested and whether there are success stories to be told for basic science and/or technology/biomedicine. In this review, we focus on the application of systems biology approaches that have been employed to shed light on both biochemical functions and previously unknown mechanisms. We point out which computational and experimental methods are employed most frequently and which trends in systems biology research can be observed. Finally, we discuss some problems that we have encountered in publications in the field.