Studying Gene Expression System Regulation at the Program Level

Understanding how gene expression systems influence biological outcomes is an important goal for diverse areas of research. Gene expression profiling allows for the simultaneous measurement of expression levels for thousands of genes and the opportunity to use this information to increase biological understanding. Yet, the best way to relate this immense amount of information to biological outcomes is far from clear. Here, a novel approach to gene expression systems research is presented that focuses on understanding gene expression systems at the level of gene expression program regulation. It is suggested that such an approach has important advantages over current techniques and may provide novel insights into how gene expression systems are regulated to shape biological outcomes such as the development of disease or response to treatment.     

Structured modelling of animal cells

Recent advances in computer technology have promoted the design and use of detailed, computer-based models for biological systems. For many non-biological systems, the complexity of such simulations may be considered inappropriate and unwieldy, but in biological systems, and more specifically in animal cell culture, this level of complexity simply mimics what is only beginning to be understood about metabolic processs. With this in mind, we contend that complex, structured models are vital tools in the investigation of fundamental biological processes. An example of such a simulation, which describes the commercial production of therapeutic proteins by animal cell cultures, is considered.     

Ins and Outs of Systems Biology vis-à-vis Molecular Biology: Continuation or Clear Cut?

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems biology ‘revolutionizes’ molecular biology and ‘transcends’ its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology’s use of modelling and bioinformatics, and by its scale enlargement.     

The manipulation of calcium oscillations by harnessing self-organisation

This paper investigates how self-organisation might be harnessed for the manipulation and control of calcium oscillations. Calcium signalling mechanisms are responsible for a number of important functions within biological systems, such as fertilization, secretion, contraction, neuronal signalling and learning. In this paper, calcium oscillations are investigated as a biological periodic process. Within biological systems such periodic behaviour is one of the outcomes from self-organisation. The understanding of periodic processes in living systems can enable more accurate diagnosis and physiologically suitable clinical therapies to be proposed, for diseases such as cancer, epilepsy, cardiac diseases and other dynamic diseases. In this paper these ideas are investigated by means of the calcium-induced calcium release (CICR) model and a number of representative simulations of intra and inter-cellular calcium oscillations are used to illustrate the manipulation and control of these oscillations in normal and pathological situations.     

Scale invariance of biosystems: From embryo to community

Phenomena having the property of a scale invariance (that is, maintaining invariable structure in certain range of scales) are typical for biosystems of different levels. In this review, main manifestations of the scale-invariant phenomena at different levels of biological organization (including ontogenetic aspects) are stated, and the reasons of such wide distribution of fractal structures in biology are discussed. Almost all biological systems can be described in terms of synergetics as open nonequilibrium systems that exist due to substance and energy flow passing through them. The phenomenon of self-organization is typical for such dissipative systems; maintenance of energy flow requires the existence of complex structures that emerge spontaneously in the presence of the appropriate gradient. Critical systems, which form as a results of their activity scale-invariant structures (that are a kind of distribution channels), are optimal relative to the efficiency of substance and energy distribution. Thus, scale invariance of biological phenomena is a natural consequence of their dissipative nature.     

Set-point: Is it a distinct structural entity in biological control?

Interest in biological control mechanisms focusses largely on quantities that are held relatively constant, in contrast to those which adapt to varying conditions. Studies of the former, via systems engineering concepts, often utilize the notion of set-point. Although set-point serves a useful purpose to configure control systems, there is no basis to conclude the existence of separate structural entities which provide such reference in biological systems.     

The emergence of scaling in sequence-based physical models of protein evolution

It has recently been discovered that many biological systems, when represented as graphs, exhibit a scale-free topology. One such system is the set of structural relationships among protein domains. The scale-free nature of this and other systems has previously been explained using network growth models that, although motivated by biological processes, do not explicitly consider the underlying physics or biology. In this work we explore a sequence-based model for the evolution protein structures and demonstrate that this model is able to recapitulate the scale-free nature observed in graphs of real protein structures. We find that this model also reproduces other statistical feature of the protein domain graph. This represents, to our knowledge, the first such microscopic, physics-based evolutionary model for a scale-free network of biological importance and as such has strong implications for our understanding of the evolution of protein structures and of other biological networks.     

On the number of experiments required to find the causal structure of complex systems

The need to capture the complexity of biological systems in a simpler formalism is the underlying impetus of biological sciences. Understanding the function of many biological complex systems, such as genetic networks or molecular signalling pathways, requires precise identification of the interactions between their individual components. A number of questions in the study of complex systems are then important-in particular, what can be inferred about the interactions in a complex system from an arbitrary set of experiments, and, what is the minimum number of experiments required to characterize the system? This paper shows that the problem of finding the minimal causal structure of a system based on a set of observations is computationally intractable for even moderately sized systems (it is NP-hard), but a reasonable approximation can be found in a relatively short (polynomial) time. Next, it is shown that the number of experiments required to characterize a complex system grows exponentially with the upper bound on the number of immediate upstream influences of each element, but only logarithmically with the number of elements in the system. This makes it possible to study biological systems with extremely large number of interacting elements and relatively sparse interconnections, such as gene regulatory and cell signalling networks. Finally, the construction of a randomized experimental sequence which achieves this bound is discussed.     

A note on the nature and origin of life

Some relational aspects of the property of self-reproduction of biological systems are studied. If in addition to the requirement of the property of self-reproduction we add also the requirement of adaptability of the organism to changing environment, this imposes certain conditions on the topology of the graphs which represent such systems. A further study of the relational properties of such systems seems to offer the possibility of deriving the principle of biological mapping from the requirement of self-reproduction and adaptability. An examination of the problem of the original formation of such self-reproducing systems in connection with the established fact of impossibility of spontaneous generation leads to the conclusion that an organism must inhibit such processes which, in the absence of organisms, would lead to spontaneous generation.     

Interaction of radiofrequency and microwave radiation with living systems

Summary Human health aspects and biological effects of radio frequency (RF) and microwave radiation have been in the focus of research efforts in the last decade. An understanding of the interaction mechanisms between such radiation and living systems is essential in interpreting experimental results and assessing potential health hazards.A comprehensive review of basic biophysical interaction mechanisms between RF and microwaves in the frequency range between 10 MHz and 300 GHz and biological systems is provided in this paper. The interactions at various levels of organization of a living organisms such as molecular, cellular and macroscopic are discussed.     

Orientation in Systems with Asymmetric Density Distribution

The hen's egg is a convenient and suitable model for biological systems in which mass is asymmetrically distributed. Under the influence of an acceleration field (such as provided by gravity on earth), such systems will become oriented, and this may have biological significance. However, depending upon the viscous and elastic properties of the system, some minimal force, i.e. a threshold, will be necessary for movement in the system. This threshold, and the restraining properties of the yolk-albumen boundary, have been evaluated for the hen's egg and are reported herein.     

Critical-like self-organization and natural selection: Two facets of a single evolutionary process?

We argue that critical-like dynamics self-organize relatively easily in non-equilibrium systems, and that in biological systems such dynamics serve as templates upon which natural selection builds further elaborations. These critical-like states can be modified by natural selection in two fundamental ways, reflecting the selective advantage (if any) of heritable variations either among avalanche participants or among whole systems. First, reproducing (avalanching) units can differentiate, as units adopt systematic behavioural variations. Second, whole systems that are exposed to natural selection can become increasingly or decreasingly critical. We suggest that these interactions between SOC-like dynamics and natural selection have profound consequences for biological systems because they could have facilitated the evolution of division of labour, compartmentalization and computation, key features of biological systems. The logical conclusion of these ideas is that the fractal geometry of nature is anything but coincidental, and that natural selection is itself a fractal process, occurring on many temporal and spatial scales.     

Is phosphatidylglycerol essential for terrestrial life?

Lipids are of increasing importance in understanding biological systems. Lipids carrying an anionic charge are noted in particular for their electrostatic interactions with both proteins and divalent cations. However, the biological, analytical, chemical and biophysical data of such species are rarely considered together, limiting our ability to assess the true role of such lipids in vivo. In this review, evidence from a range of studies about the lipid phosphatidylglycerol is considered. This evidence supports the conclusions that this lipid is ubiquitous in living systems and generally of low abundance but probably fundamental for terrestrial life. Possible reasons for this are discussed and further questions posed.     

Hybrid semi-parametric mathematical systems: bridging the gap between systems biology and process engineering

Systems biology is an integrative science that aims at the global characterization of biological systems. Huge amounts of data regarding gene expression, proteins activity and metabolite concentrations are collected by designing systematic genetic or environmental perturbations. Then the challenge is to integrate such data in a global model in order to provide a global picture of the cell. The analysis of these data is largely dominated by nonparametric modelling tools. In contrast, classical bioprocess engineering has been primarily founded on first principles models, but it has systematically overlooked the details of the embedded biological system. The full complexity of biological systems is currently assumed by systems biology and this knowledge can now be taken by engineers to decide how to optimally design and operate their processes. This paper discusses possible methodologies for the integration of systems biology and bioprocess engineering with emphasis on applications involving animal cell cultures. At the mathematical systems level, the discussion is focused on hybrid semi-parametric systems as a way to bridge systems biology and bioprocess engineering.     

Applications of carbon nanotubes for cancer research

Carbon nanotubes have many unique properties such as high surface area, hollow cavities, and excellent mechanical and electrical properties. Interfacing carbon nanotubes with biological systems could lead to significant applications in various disease diagnoses. Significant progress in interfacing carbon nanotubes with biological materials has been made in key areas such as aqueous solubility, chemical and biological functionalization for biocompatibility and specificity, and electronic sensing of proteins. In addition, the bioconjugated nanotubes combined with the sensitive nanotube-based electronic devices would enable sensitive biosensors toward medical diagnostics. Furthermore, recent findings of improved cell membrane permeability for carbon nanotubes would also expand medical applications to therapeutics using carbon nanotubes as carriers in gene delivery systems. This article reviews the current trends in biological functionalization of carbon nanotubes and their potential applications for breast cancer diagnostics. The article also reports the applications of confocal microscopy for use in understanding the interactions of biological materials such as antibodies on carbon nanotubes that are specific to surface receptors in breast cancer cells. Furthermore, a nanotube-field-effect transistor is demonstrated for electronic sensing of antibodies that are specific to surface receptors in cancer cells.     

Global dynamics of biological systems from time-resolved omics experiments

The emergent properties of biological systems, organized around complex networks of irregularly connected elements, limit the applications of the direct scientific method to their study. The current lack of knowledge opens new perspectives to the inverse scientific paradigm where observations are accumulated and analysed by advanced data-mining techniques to enable a better understanding and the formulation of testable hypotheses about the structure and functioning of these systems. The current technology allows for the wide application of omics analytical methods in the determination of time-resolved molecular profiles of biological samples. Here it is proposed that the theory of dynamical systems could be the natural framework for the proper analysis and interpretation of such experiments. A new method is described, based on the techniques of non-linear time series analysis, which is providing a global view on the dynamics of biological systems probed with time-resolved omics experiments.     

Does Help in Decision-Making in Biology Help in Decision-Making in Human Sciences and Conversely?

A link between biological and human sciences may be established, under the condition that we should admit the existence of reciprocal influences between them. The model for the regulation of agonistic antagonistic couples (MRAAC) is built from the study of biological systems and gives rise to specific types of control. This model can be helpful in decision processes in some human sciences such as management, economical and political strategies. The reason for such an opportunity lies in the fact that MRAAC is a general and phenomenological model able to incorporate the whole of the agonistic antagonistic systems. This type of regulation might be related to the concept of the viability of a system (yet also valid for human science systems) and to a functional and structural pattern which is the basis for agonistic antagonistic networks.