Understanding biological systems in terms of scientific materialism has arguably reached a frontier, leaving fundamental questions about their complexity unanswered. In 1998, Friedrich Cramer proposed a general resonance theory as a way forward. His theory builds on the extension of the quantum physical duality of matter and wave to the macroscopic world. According to Cramer’ theory, agents constituting biological systems oscillate, akin to musical soundwaves, at specific eigenfrequencies. Biological system dynamics can be described as “Symphonies (...) of Life” emerging from the resonance (and dissonance) of eigenfrequencies within the interacting collective. His theory has potential for studying biological problems of increasing complexity in a fast‐changing Anthropocene from a new and transdisciplinary angle. Despite data becoming increasingly available for analyses, Cramer's theory remains ignored and therefore untested a quarter century after its publication. This paper discusses how the theory can move to quantitative assessments and application. Cramer's general resonance theory deserves revival. (shrink)

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: (...) class='Hi'>systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences. (shrink)

Biological systems are typically hierarchically organized, open, nonlinear systems, and inherit all of the characteristics of such systems that are found in the purely physical and chemical domains, to which all biological systems belong. In addition, biological systems exhibit functional properties, and they contain information in a form that is used internally to make required functional distinctions. The existence of these additional biological properties is widely granted, but their exact nature is (...) controversial. I will address first the issue of biological function, and then turn to the issue of information in biosystems. (shrink)

Our purpose in this essay is to introduce new concepts in a wide and recursive view of the systemic consequences of the following biological facts that I and we have presented that can be resumed as: that as living systems we human beings are molecular autopoietic system; that living systems live only as long as they find themselves in a medium that provides them with all the conditions that make the realization of their living possible, that is, (...) in the continuous conservation of their relation of adaptation to the circumstances in which they find themselves; that as a living system exists only in a relation of adaptation with the medium that operates as its ecological niche, its reproduction necessarily occurs as a process of systemic duplication or multiplication of the ecological organism-niche unity that it integrates; that the worlds of doings that we generate as languaging beings in our conversations, explanations, reflections and theories are part of our ecological niche; and that we human beings as living beings that exist in languaging, are biological–cultural beings in which our cultural and our biological manners of existences can be distinguished but cannot be separated. Of the systemic consequences of these biological facts that we consider in this essay, we wish to mention two as the principal: that the diversification of manners of living produced in biological evolution is the result of differential survival in a changing medium through the conservation of adaptation, and not through competitive survival of the best; and that we in our living as languaging human beings are the epistemological fundament of all that we do and know as such. (shrink)

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific signals (...) and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (shrink)

Living systems employ several mechanisms and behaviors to achieve robustness and maintain themselves under changing internal and external conditions. Regulation stands out from them as a specific form of higher-order control, exerted over the basic regime responsible for the production and maintenance of the organism, and provides the system with the capacity to act on its own constitutive dynamics. It consists in the capability to selectively shift between different available regimes of self-production and self-maintenance in response to specific signals (...) and perturbations, due to the action of a dedicated subsystem which is operationally distinct from the regulated ones. The role of regulation, however, is not exhausted by its contribution to maintain a living system’s viability. While enhancing robustness, regulatory mechanisms play a fundamental role in the realization of an autonomous biological organization. Specifically, they are at the basis of the remarkable integration of biological systems, insofar as they coordinate and modulate the activity of distinct functional subsystems. Moreover, by implementing complex and hierarchically organized control architectures, they allow for an increase in structural and organizational complexity while minimizing fragility. Finally, they endow living systems, from their most basic unicellular instances, with the capability to control their own internal dynamics to adaptively respond to specific features of their interaction with the environment, thus providing the basis for the emergence of minimal forms of cognition. (shrink)

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From this, an (...) information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

Different cell lineages growing in microgravity undergo a spontaneous transition leading to the emergence of two distinct phenotypes. By returning these populations in a normal gravitational field, the two phenotypes collapse, recovering their original configuration. In this review, we hypothesize that, once the gravitational constraint is removed, the system freely explores its phenotypic space, while, when in a gravitational field, cells are “constrained” to adopt only one favored configuration. We suggest that the genome allows for a wide range of “possibilities” (...) but it is unable per se to choose among them: the emergence of a specific phenotype is enabled by physical constraints that drive the system toward a preferred solution. These findings may help in understanding how cells and tissues behave in both development and cancer. In microgravity, cells undergo spontaneous and reversible transitions between different phenotypes. In the absence of physical constraints, living systems could yield bi-stable decisions. On the contrary, physical ‘boundaries’ constrain cells to acquire only a specific configuration by selecting and shaping different gene expression patterns provided by the intrinsic genetic stochasticity. (shrink)

The living world is an exciting and inexhaustible source of high performance solutions to the multitude of biological problems, which were attained as a result of a natural selection, during the millions and millions years evolution of life on Earth. This work presents and comments some examples of high performances of living beings, in the light of the universal principle governing the realm of living matter: Optimal Design Principle. At the same time, the transfer of these optimal solutions, from (...) living matter to the technologies, is also discussed. This transfer is offering new and fertile perspectives to future technologies, which must be more efficient, cheaper and in perfect harmony with the biosphere. (shrink)

Open peer commentary on the article “Homeostats for the 21st Century? Simulating Ashby Simulating the Brain” by Stefano Franchi. Upshot: The target article proposes that Ashby’s investigations of the homeostat and ultrastability lead to a view of living systems as heteronomous, passive “sleeping” machines and thus are in fundamental conflict with concepts of autonomy developed by Jonas, Varela and others. I disagree, arguing that (1) the maintenance of essential variables within viability limits is not a passive process for living (...) systems and (2) the purpose of Ashby’s investigations of the homeostat was to investigate adaptivity, a subject that is related to, but clearly distinct from, autonomy. As such, I find Ashby’s work on adaptivity to be neither in opposition to nor in direct support of modern concepts of biological autonomy and suggest that a productive way forward involves the investigation of the intersection between these two fundamental properties of living systems. (shrink)

Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.

Due to the variation, contingency and complexity of living systems, biology is often taken to be a science without fundamental theories, laws or general principles. I revisit this question in light of the quest for design principles in systems biology and show that different views can be reconciled if we distinguish between different types of generality. The philosophical literature has primarily focused on generality of specific models or explanations, or on the heuristic role of abstraction. This paper takes (...) a different approach in emphasizing a theory-constituting role of general principles. Design principles signify general dependency-relations between structures and functions, given a set of formally defined constraints. I contend that design principles increase our understanding of living systems by relating specific models to general types. The categorization of types is based on a delineation of the scope of biological possibilities, which serves to identify and define the generic features of classes of systems. To characterize the basis for general principles through generic abstraction and reasoning about possibility spaces, I coin the term constraint-based generality. I show that constraint-based generality is distinct from other types of generality in biology, and argue that general principles play a unifying role that does not entail theory reduction. (shrink)

Living organisms are currently most often seen as complex dynamical systems that develop and evolve in relation to complex environments. Reflections on the meaning of the complex dynamical nature of living systems show an overwhelming multiplicity in approaches, descriptions, definitions and methodologies. Instead of sustaining an epistemic pluralism, which often functions as a philosophical armistice in which tolerance and so-called neutrality discharge proponents of the burden to clarify the sources and conditions of agreement and disagreement, this paper aims (...) at analysing: (i) what has been Kant's original conceptualisation of living organisms as natural purposes; (ii) how the current perspectives are to be related to Kant's viewpoint; (iii) what are the main trends in current complexity thinking. One of the basic ideas is that the attention for structure and its epistemological consequences witness to a great extent of Kant's viewpoint, and that the idea of organisational stratification today constitutes a different breeding ground within which complexity issues are raised. The various approaches of complexity in biological systems are captured in terms of two different styles, universalism and (weak and strong) constructivism, between which hybrid forms exist. (shrink)

It is argued that multiscale approaches are necessary for an explanatory modeling of biological systems. A first step, besides common to the multiscale modeling of physical and living systems, is a bottom-up integration based on the notions of effective parameters and minimal models. Top-down effects can be accounted for in terms of effective constraints and inputs. Biological systems are essentially characterized by an entanglement of bottom-up and top-down influences following from their evolutionary history. A self-consistent (...) multiscale scheme is proposed to capture the ensuing circular causality. Its differences with standard mean-field self-consistent equations and slow-fast decompositions are discussed. As such, this scheme offers a way to unravel the multilevel architecture of living systems and their regulation. Two examples, genome functions and biofilms, are detailed. (shrink)

The recent discussion of fictional models has focused on imagination, implicitly considering fictions as something nonconcrete. We present two cases from synthetic biology that can be viewed as concrete fictions. Both minimal cells and alternative genetic systems are modal in nature: they, as well as their abstract cousins, can be used to study unactualized possibilia. We approach these synthetic constructs through Vaihinger’s notion of a semi-fiction and Goodman’s notion of semifactuality. Our study highlights the relative existence of such concrete (...) fictions. Before their realizations neither minimal cells nor alternative genetic systems were any well-defined objects, and the subsequent experimental work has given more content to these originally schematic imaginings. But it is as yet unclear whether individual members of these heterogeneous groups of somewhat functional synthetic constructs will eventually turn out to be fully realizable, remain only partially realizable, or prove outright impossible. (shrink)

In their recent book, Ladyman and Wiesner (What is a complex system?, Yale University Press, 2020) delineate the bounds of the exciting interdisciplinary field of complexity science. In this work, they provide examples of generally accepted complex systems and common features which these possess to varying degrees. In this paper, I plan to extend their list to include the formal study of natural language, i.e. linguistics. In fact, I will argue that language exhibits many of the hallmarks of a (...) complex system, specifically a complex biological system. Thus, my aim is to advocate contra the the ‘Minimalist Program’ (Chomsky, The minimalist program, MIT Press, Cambridge, 1995), which motivates simple underlying mechanisms (i.e. Merge) in their idealisations, that biolinguistics should embrace a ‘Maximalist Program’ in which multiple subfields contribute component explanations to an emerging whole. (shrink)

This article proposes an abstract mathematical frame for describing some features of cognitive and biological time. We focus here on the so called “extended present” as a result of protentional and retentional activities (memory and anticipation). Memory, as retention, is treated in some physical theories (relaxation phenomena, which will inspire our approach), while protention (or anticipation) seems outside the scope of physics. We then suggest a simple functional representation of biological protention. This allows us to introduce the abstract (...) notion of “biological inertia”. (shrink)

Life as self-organization is philosophically understood by L. Polo in terms of co-causality between matter, formal configuration and intrinsic efficiency. This characterization provides a dynamic account of life and soul, capable to explain both its identity and its continuous renovation. In this article I especially highlight in this author the metaphysical notions of finality, unity and cosmos, which may be helpful to understand the sense of biological systems in the universe.

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework (...) of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. (shrink)

In this essay I examine the ways in which the Belousov–Zhabotinsky (BZ) reaction is being used by biologists to model a variety of biological systems and processes. The BZ reaction is characterized as a functional model of biological phenomena. It is able to play this role because, though based on very different substrates, the model and system modeled are examples of the same type of excitable medium. Lessons are drawn from this case about the relationships between the (...) sciences of chemistry and biology. (shrink)

We defend the fundamental ontological-pragmatic principle that where there are continua in reality science is often forced to make partly fiat terminological delimitations. In particular, this principle applies when it comes to describing biological organisms, their parts, properties, and relations. Human-made fiat delimitations are indispensable at the level of both individuals and the natural kinds which they instantiate. The kinds of pragmatically based ‘fiatness’ that we describe can create incompatibilities and lack of interoperability even between properly designed ontologies, if (...) not appropriately handled. (shrink)

I now understand why the invitation to contribute an article on “chaos theory” invoked both my excitement and reticience. Let me first explain my excitement in terms of intriguing developments generated by the Cosmic Background Explorer satellite. Since COBE strengthened an “inflationary” Big Bang Theory wherein the structure of the universe was induced by random statistical fluctuations, there are implications inter alia of thermodynamics for chaotic fluctuations in both the structure and biological systems formed from it. I shall (...) then explain my reticence concerning a chaosladen cosmology. Though it seems to call for an epistemological revision of deterministic scientific truth, the cosmology is as likely as one influenced by quantum mechanics to lead to either a pseudo-scientific connection of indeterminism to freedom and purpose or their dogmatic exclusion as possible “realities” by the natural and social sciences. What I will be concerned about are the conflation of physics with metaphysics and the need to metaphysically articulate the continuity between a primordial quantum fluctuation, biological “possibilities,” and human freedom. (shrink)

Boltzmann's gas model representing the second law of thermodynamics is based on the improbability of certain molecular distributions in space. Maxwell argued that a hypothetical ‘being’ with the faculty of seeing individual molecules could bring about such improbable distributions, thus violating the law of entropy. However, it appears that to render the molecules visible for any observer would increase the entropy more than the demon could decrease it, hence ‘Maxwell's Demon cannot operate’ . In the study presented here Maxwell's Demon (...) is interpreted in a general way as a biological observer system within systems which can upset thermodynamic probabilities provided that the relative magnitudes between observer system and observed system are appropriate.Maxwell's Demon within Boltzmann's Gas Model thus appears only as a special case of inappropriate, relative magnitude between the two systems. (shrink)

I defend a theory of mental representation that satisfies naturalistic constraints. Briefly, we begin by distinguishing (i) what makes something a representation from (ii) given that a thing is a representation, what determines what it represents. Representations are states of biological organisms, so we should expect a unified theoretical framework for explaining both what it is to be a representation as well as what it is to be a heart or a kidney. I follow Millikan in explaining (i) in (...) terms of teleofunction, explicated in terms of natural selection. -/- To explain (ii), we begin by recognizing that representational states do not have content, that is, they are neither true nor false except insofar as they both “point to” or “refer” to something, as well as “say” something regarding whatever it is they are about. To distinguish veridical from false representations, there must be a way for these separate aspects to come apart; hence, we explain (ii) by providing independent theories of what I call f-reference and f-predication (the ‘f’ simply connotes ‘fundamental’, to distinguish these things from their natural language counterparts). -/- Causal theories of representation typically founder on error, or on what Fodor has called the disjunction problem. Resemblance or isomorphism theories typically founder on what I’ve called the non-uniqueness problem, which is that isomorphisms and resemblance are practically unconstrained and so representational content cannot be uniquely determined. These traditional problems provide the motivation for my theory, the structural preservation theory, as follows. F-reference, like reference, is a specific, asymmetric relation, as is causation. F-predication, like predication, is a non-specific relation, as predicates typically apply to many things, just as many relational systems can be isomorphic to any given relational system. Putting these observations together, a promising strategy is to explain f-reference via causal history and f-predication via something like isomorphism between relational systems. -/- This dissertation should be conceptualized as having three parts. After motivating and characterizing the problem in chapter 1, the first part is the negative project, where I review and critique Dretske’s, Fodor’s, and Millikan’s theories in chapters 2-4. Second, I construct my theory about the nature of representation in chapter 5 and defend it from objections in chapter 6. In chapters 7-8, which constitute the third and final part, I address the question of how representation is implemented in biological systems. In chapter 7 I argue that single-cell intracortical recordings taken from awake Macaque monkeys performing a cognitive task provide empirical evidence for structural preservation theory, and in chapter 8 I use the empirical results to illustrate, clarify, and refine the theory. (shrink)

Integrating concepts of maintenance and of origins is essential to explaining biological diversity. The unified theory of evolution attempts to find a common theme linking production rules inherent in biological systems, explaining the origin of biological order as a manifestation of the flow of energy and the flow of information on various spatial and temporal scales, with the recognition that natural selection is an evolutionarily relevant process. Biological systems persist in space and time by (...) transfor ming energy from one state to another in a manner that generates structures which allows the system to continue to persist. Two classes of energetic transformations allow this; heat-generating transformations, resulting in a net loss of energy from the system, and conservative transformations, changing unusable energy into states that can be stored and used subsequently. All conservative transformations in biological systems are coupled with heat-generating transformations; hence, inherent biological production, or genealogical proesses, is positively entropic. There is a self-organizing phenomenology common to genealogical phenomena, which imparts an arrow of time to biological systems. Natural selection, which by itself is time-reversible, contributes to the organization of the self-organized genealogical trajectories. The interplay of genealogical (diversity-promoting) and selective (diversity-limiting) processes produces biological order to which the primary contribution is genealogical history. Dynamic changes occuring on times scales shorter than speciation rates are microevolutionary; those occuring on time scales longer than speciation rates are macroevolutionary. Macroevolutionary processes are neither redicible to, nor autonomous from, microevolutionary processes. (shrink)

Complex, multigenic biological traits are shaped by the emergent interaction of proteins being the main functional units at the molecular scale. Based on a phenomenological approach, algorithms for quantifying two different aspects of emergence were introduced (Wegner and Hao in Progr Biophys Mol Biol 161:54–61, 2021) describing: (i) pairwise reciprocal interactions of proteins mutually modifying their contribution to a complex trait (denoted as weak emergence), and (ii) formation of a new, complex trait by a set of n ‘constitutive’ proteins (...) at concentrations exceeding individual threshold values (strong emergence). The latter algorithm is modified here to take account of protein redundancy with respect to a complex trait (‘full redundancy’). Irreducibility is considered a necessary and sufficient criterion for strong biological emergence; if one constitutive protein is missing, or its concentration drops below the threshold the trait is lost. A definition based on ‘unpredictability’ is dismissed, because this criterion is irrelevant for the evolution of a complex trait, and apparent unpredictability may rather reflect our basic deficits in understanding unless we can provide an unequivocal proof for it. The phenomenological approach advocated here allows to identify hidden rules according to which strongly emergent traits may be organized. This is of high value for understanding the evolution of complex traits which seems to require the saltational advent of all constitutive proteins ‘in one turn’ to arrive at a functional trait providing for an improved fitness of the organism. Rather than being a purely random process, it may be guided by fundamental structural principles. (shrink)

Biologists often study particular biological systems as models of a phenomenon of interest even if they already know that the phenomenon is produced by diverse mechanisms and hence none of those systems alone can sufficiently represent it. To understand this modeling practice, the present paper provides an account of how multiple model systems can be used to study a phenomenon that is produced by diverse mechanisms. Even if generalizability of results from a single model system is (...) significantly limited, generalizations concerning specific aspects of mechanisms often hold across certain ranges of biological systems, which enables multiple model systems to jointly represent such a phenomenon. Comparing mechanisms that operate in different biological systems as examples of the same phenomenon also facilitates characterization and investigation of individual mechanisms. I also compare my account with two existing accounts of the use of multiple model systems and argue that my account is distinct from and complementary to them. (shrink)

In this paper, we advocate the idea that an adequate explanation of biological systems requires appealing to organizational closure as an emergent causal regime. We first develop a theoretical justification of emergence in terms of relatedness, by arguing that configurations, because of the relatedness among their constituents, possess ontologically irreducible properties, providing them with distinctive causal powers. We then focus on those emergent causal powers exerted as constraints, and we claim that biological systems crucially differ from (...) other natural systems in that they realize a closure of constraints, i.e. a second-order emergent regime of causation such that the constituents, each of them acting as a constraint, realize a mutual dependence among them, and are collectively able to self-maintain. Lastly, we claim that closure can be justifiably taken as an emergent regime of causation, without admitting that it inherently involves whole-parts causation, which would require to commit to stronger ontological and epistemological assumptions. (shrink)

Even the simplest known living organisms are complex chemical processing systems. But how sophisticated is the behaviour that arises from this? We present a framework in which even bacteria can be identified as capable of representing information in arbitrary signal molecules, to facilitate altering their behaviour to optimise their food supplies, for example. Known asion/Representation theory, this framework makes precise the relationship between physical systems and abstract concepts. Originally developed to answer the question of when a physical system (...) is computing, AR theory naturally extends to the realm of biological systems to bring clarity to questions of computation at the cellular level. (shrink)

The key assumption behind evolutionary epistemology is that animals are active learners or ‘knowers’. In the present study, I updated the concept of natural learning, developed by Henry Plotkin and John Odling-Smee, by expanding it from the animal-only territory to the biosphere-as-a-whole territory. In the new interpretation of natural learning the concept of biological information, guided by Peter Corning’s concept of “control information”, becomes the ‘glue’ holding the organism–environment interactions together. The control information guides biological systems, from (...) bacteria to ecosystems, in the process of natural learning executed by the universal algorithm. This algorithm, summarized by the acronym IGPT (information-gain-process-translate) incorporates natural cognitive methods including sensing/perception, memory, communication, and decision-making. Finally, the biosphere becomes the distributed network of communicative interactions between biological systems termed the interactome. The concept of interactome is based on Gregory Bateson’s natural epistemology known as the “ecology of mind”. Mimicking Bateson’s approach, the interactome may also be designated “physiology of mind”—the principle behind regulating the biosphere homeostasis. (shrink)

Emergence is much discussed by both philosophers and scientists. But, as noted by Mitchell (2012), there is a significant gulf; philosophers and scientists talk past each other. We contend that this is because philosophers and scientists typically mean different things by emergence, leading us to distinguish being emergence and pattern emergence. While related to distinctions offered by others between, for example, strong/weak emergence or epistemic/ontological emergence (Clayton, 2004, pp. 9–11), we argue that the being vs. pattern distinction better captures what (...) the two groups are addressing. In identifying pattern emergence as the central concern of scientists, however, we do not mean that pattern emergence is of no interest to philosophers. Rather, we argue that philosophers should attend to, and even contribute to, discussions of pattern emergence. But it is important that this discussion be distinguished, not conflated, with discussions of being emergence. In the following section we explicate the notion of being emergence and show how it has been the focus of many philosophical discussions, historical and contemporary. In section 3 we turn to pattern emergence, briefly presenting a few of the ways it figures in the discussions of scientists (and philosophers of science who contribute to these discussions in science). Finally, in sections 4 and 5, we consider the relevance of pattern emergence to several central topics in philosophy of biology: the emergence of complexity, of control, and of goal-directedness in biological systems. (shrink)

Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecendented in its combination of biology with a ...

The theory of chemical symbiosis suggests that biological systems started with the collaboration of two polymeric molecules existing in early Earth: nucleic acids and peptides. Chemical symbiosis emerged when RNA-like nucleic acid polymers happened to fold into 3D structures capable to bind amino acids together, forming a proto peptidyl-transferase center. This folding catalyzed the formation of quasi-random small peptides, some of them capable to bind this ribozyme structure back and starting to form an initial layer that would produce (...) the larger subunit of the ribosome by accretion. TCS suggests that there is no chicken-and-egg problem into the emergence of biological systems as RNAs and peptides were of equal importance to the origin of life. Life has initially emerged when these two macromolecules started to interact in molecular symbiosis. Further, we suggest that life evolved into progenotes and cells due to the emergence of new layers of symbiosis. Mutualism is the strongest force in biology, capable to create novelties by emergent principles; on which the whole is bigger than the sum of the parts. TCS aims to apply the Margulian view of biology into the origins of life field. (shrink)

Nanoscience has enabled the understanding of organisation of the atomic and molecular world. Due to the unique chemical, electronic and magnetic properties nanomaterials have wide applications in the chemical, manufacturing, medical sector etc., Single walled carbon nanotubes, buckyballs, ZnSe quantum dots, TiO 2 nanoparticle based products are nearing commercialisation. Research is on-going worldwide on suitable delivery systems for nanomaterial based drugs. Nanomaterials are highly reactive in biological systems due to the large surface area. While the benefits of (...) nanomaterials are evident there are studies which indicate the potential risk to biological systems. Substances known to be harmless in bulk can be potentially toxic in certain fibrous and nanoparticle form. Risk assessment studies with nanomaterials largely focus on mouse models. There are very few studies on their effects on aquatic species and plants which form the largest in the productivity chain with respect to the ecological pyramid. This study reviews the research done worldwide in the area of risk assessment of nanomaterials, particularly the effects on aquatic and plant systems. Risk assessment is the foundation for regulatory decision making. A general comparison of the regulatory regime in nanotechnology is performed to understand the extent of development. (shrink)

Self-organized criticality (SOC) is based upon the idea that complex behavior can develop spontaneously in certain multi-body systems whose dynamics vary abruptly. This book is a clear and concise introduction to the field of self-organized criticality, and contains an overview of the main research results. The author begins with an examination of what is meant by SOC, and the systems in which it can occur. He then presents and analyzes computer models to describe a number of systems, (...) and he explains the different mathematical formalisms developed to understand SOC. The final chapter assesses the impact of this field of study, and highlights some key areas of new research. The author assumes no previous knowledge of the field, and the book contains several exercises. It will be ideal as a textbook for graduate students taking physics, engineering, or mathematical biology courses in nonlinear science or complexity. (shrink)

A longstanding philosophical premise perceives simplicity as a desirable attribute of scientific theories. One of several raised justifications for this notion is that simple theories are more likely to indicate the true makeup of natural systems. Qualitatively parsimonious hypotheses and theories keep to a minimum the number of different postulated entities within a system. Formulation of such ontologically simple working hypotheses proved to be useful in the experimental probing of narrowly defined bio systems. It is less certain, however, (...) whether qualitatively parsimonious theories are effective indicators of the true nature of complex biological systems. This paper assesses the success of ontologically simple theories in envisaging the makeup of three complex systems in bacteriology, immunology, and molecular biology. Evidence shows that parsimonious theories completely misconstrued the actual ontologically complex constitutions of the three examined systems. Since evolution and selective pressures typically produce ontologically intricate rather than simple bio systems, qualitatively parsimonious theories are mostly inapt indicators of the true nature of complex biological systems. (shrink)

Mechanistic accounts of explanation have recently found popularity within philosophy of science. Presently, we introduce the idea of an extended mechanistic explanation, which makes explicit room for the role of environment in explanation. After delineating Craver and Bechtel’s account, we argue this suggestion is not sufficiently robust when we take seriously the mechanistic environment and modeling practices involved in studying contemporary complex biological systems. Our goal is to extend the already profitable mechanistic picture by pointing out the importance (...) of the mechanistic environment. It is our belief that extended mechanistic explanations, or mechanisms that take into consideration the temporal sequencing of the interplay between the mechanism and the environment, allow for mechanistic explanations regarding a broader group of scientific phenomena. (shrink)

Despite wide acceptance that the attributes of living creatures have appeared through a cumulative evolutionary process guided chiefly by natural selection, many human activities have seemed analytically inaccessible through such an approach. Prominent evolutionary biologists, for example, have described morality as contrary to the direction of biological evolution, and moral philosophers rarely regard evolution as relevant to their discussions. -/- The Biology of Moral Systems adopts the position that moral questions arise out of conflicts of interest, and that (...) moral systems are ways of using confluences of interest at lower levels of social organiation to deal with conflicts of interest at higher levels. Moral systems are described as systems of indirect reciprocity: humans gain and lose socially and reproductively not only by direct transactions, but also by the reputations they gain from the everyday flow of social interactions. -/- The author develops a general theory of human interests, using senescence and effort theory from biology, to help analye the patterning of human lifetimes. He argues that the ultimate interests of humans are reproductive, and that the concept of morality has arisen within groups because of its contribution to unity in the context, ultimately, of success in intergroup competition. He contends that morality is not easily relatable to universals, and he carries this argument into a discussion of what he calls the greatest of all moral problems, the nuclear arms race. (shrink)

In this essay we aim to present some considerations regarding a minimal but concrete notion of agency and goal-directed behavior that are useful for characterizing biological systems at different scales. These considerations are a particular perspective, bringing together concepts from dynamical systems, combinatorial problem-solving, and connectionist learning with an emphasis on the relationship between parts and wholes. This perspective affords some ways to think about agents that are concrete and quantifiable, and relevant to some important biological (...) issues. Instead of advocating for a strict definition of minimally agential characteristics, we focus on how (even for a modest notion of agency) the agency of a system can be more than the sum of the agency of its parts. We quantify this in terms of the problem-solving competency of a system with respect to resolution of the frustrations between its parts. This requires goal-directed behavior in the sense of delayed gratification, i.e., taking dynamical trajectories that forego short-term gains (or sustain short-term stress or frustration) in favor of long-term gains. In order for this competency to belong to the system (rather than to its parts or given by its construction or design), it can involve distributed systemic knowledge that is acquired through experience, i.e., changes in the organization of the relationships among its parts (without presupposing a system-level reward function for such changes). This conception of agency helps us think about the ways in which cells, organisms, and perhaps other biological scales, can be agential (i.e., more agential than their parts) in a quantifiable sense, without denying that the behavior of the whole depends on the behaviors of the parts in their current organization. (shrink)

Habituation, a form of non‐associative learning, isno longer studied exclusively within the fields of psychology and neuroscience. Indeed, the same stimulus–response pattern is observed at the molecular, cellular, and organismal scales and is not dependent upon the presence of neurons. Hence, a more inclusive theory is required to accommodate aneural forms of habituation. Here an abstraction of the habituation process that does not rely upon particular biological pathways or substrates is presented. Instead, five generalizable elements that define the habituation (...) process are operationalized. The formulation can be applied to interrogate systems as they respond to several stimulation paradigms, providing new insights and supporting existing behavioral data. The model can be used to deduce the relative contribution of elements that contribute to the measurable output of the system. The results suggest that habituation serves as a general biological strategy that any system can implement to adaptively respond to harmless, repetitive stimuli. (shrink)

Spatial evolutionary game theory explains how cooperative traits can survive the intense competition in biological systems. If the spatial distribution allows cooperators to interact with each other frequently, the benefits of cooperation will outweigh the losses due to exploitation by selfish organisms. However, for a cooperative behavior to get established in a system, it needs to be found initially in a sufficiently large cluster to allow a high frequency of intracooperator interactions. Since mutations are rare events, this poses (...) the question of how cooperation can arise in a biological system in the first place. We present a simple model which captures two concepts from genetics that can explain how evolution overcomes the emergence problem. The first concept is, often in nature, a gene may not express its phenotype except under specific environmental conditions, rendering it to be a “silent” gene. The second key idea is that a neutral gene, one that does not harm or improve an organism’s survival chances, can still spread through a population if it is physically near to another gene that is positively selected. Through these two ideas, our model offers a possible solution to the fundamental problem of emergence of cooperation in biological systems. (shrink)