Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting (...) empirical cases. The more recent modeling-based accounts still perpetuate a theory-centric view of scientific concepts, which motivated philosophers’ misplaced skepticism in the first place. (shrink)

Although contemporary metaphysics has recently undergone a neo-Aristotelian revival wherein dispositions, or capacities are now commonplace in empirically grounded ontologies, being routinely utilised in theories of causality and modality, a central Aristotelian concept has yet to be given serious attention – the doctrine of hylomorphism. The reason for this is clear: while the Aristotelian ontological distinction between actuality and potentiality has proven to be a fruitful conceptual framework with which to model the operation of the natural world, the distinction between (...) form and matter has yet to similarly earn its keep. In this chapter, I offer a first step toward showing that the hylomorphic framework is up to that task. To do so, I return to the birthplace of that doctrine - the biological realm. Utilising recent advances in developmental biology, I argue that the hylomorphic framework is an empirically adequate and conceptually rich explanatory schema with which to model the nature of organisms. (shrink)

In spite of being ubiquitous in life sciences, the concept of information is harshly criticized. Uses of the concept other than those derived from Shannon's theory are denounced as pernicious metaphors. We perform a computational experiment to explore whether Shannon's information is adequate to describe the uses of said concept in commonplace scientific practice. Our results show that semantic sequences do not have unique complexity values different from the value of meaningless sequences. This result suggests that quantitative theoretical (...) frameworks do not account fully for the complex phenomenon that the term “information” refers to. We propose a restructuring of the concept into two related, but independent notions, and conclude that a complete theory of biological information must account completely not only for both notions, but also for the relationship between them. (shrink)

The idea of homesteading can be extended to the realm of biological entities, to the ownership of information wherein organisms perform artifactual functions as a result of human development. Can the information of biological entities be ethically “homesteaded”: should humans (or businesses) have ownership rights over this information from the basis of mere development and possession, as in Locke’s theory of private property? I offer three non-consequentialist arguments against such homesteading: the information makeup of (...) biological entities is not commonly owned, and thus is not available for homesteading; the value of the individual biological entity extends to the information whereby it is constituted, and includes inalienable rights of an entity over itself and its information; and use of life as an information artifact makes an organism an unending means to an end rather than an end itself. I conclude that the information space of biological entities is not open for homesteading, not liable to private ownership, and should not be available for perpetual exploitation. (shrink)

Waters’s (2007) actual difference making and Weber’s (2013, 2017) biological normality approaches to causal selection have received many criticisms, some of which miss their target. Disagreement about whether Waters’s and Weber’s views succeed in providing criteria that uniquely singles out the gene as explanatorily significant in biology has led philosophers to overlook a prior problem. Before one can address whether Waters’s and Weber’s views successfully account for the explanatory significance of genes, one must ask whether either view satisfactorily meets (...) the necessary conditions for causal selection in the first place. An adequate defense of causal selection must meet two desiderata. First, there must be an explanatory property that sets some causes apart from others. Second, the property identified must be one that is recognized by biologists as relevant to their domain(s) of inquiry. I argue that both fall short of meeting the second condition. I demonstrate this by showing how many of the biological technologies crucial to experimentation do not fit either view very well. I offer a more adequate proposal that accommodates non-actual and artificial causal variables. A consequence of my view is the following: When analyzing the causal selection practices of biologists, philosophers should consider the explanatory targets relevant to a research program – including ones whose explanans must appeal to biological technologies. I then explain how this proposal can inform the existing debate between Weber (2017) and Griffiths et al. (2015). (shrink)

Background: how mind functions is subject to continuing scientific discussion. A simplistic approach says that, since no convincing way has been found to model subjective experience, mind cannot exist. A second holds that, since mind cannot be described by classical physics, it must be described by quantum physics. Another perspective concerns mind's hypothesized ability to interact with the world of quanta: it should be responsible for reduction of quantum wave packets; physics producing 'Objective Reduction' is postulated to form the basis (...) for mind-matter interactions. This presentation describes results derived from a new approach to these problems. It is based on well-established biology involving physics not previously applied to the fields of mind, or consciousness studies, that of critical feedback instability. -/- Methods: 'self-organized criticality' in complexity biology places system loci of control at critical instabilities, physical properties of which, including information properties, are presented. Their elucidation shows that they can model hitherto unexplained properties of experience. -/- Results: All results depend on physical properties of critical instabilities. First, at least one feed-back or feed-forward loop must have feedback gain, g = 1: information flows round the loop impress perfect images of system states back on themselves: they represent processes of perfect self-observation. This annihilates system quanta: system excitations are instability fluctuations, which cannot be quantized. Major results follow: -/- 1. Information vectors representing criticality states must include at least one attached information loop denoting self-observation. -/- 2. Such loop structures are attributed a function, 'registering the state's own existence', explaining -/- a. Subjective 'awareness of one's own presence' -/- b. How content-free states of awareness can be remembered (Jon Shear) -/- c. Subjective experience of time duration (Immanuel Kant) -/- d. The 'witness' property of experience – often mentioned by athletes 'in the zone' -/- e. The natural association between consciousness and intelligence -/- This novel, physically and biologically sound approach seems to satisfactorily model subjectivity. -/- Further significant results follow: -/- 1. Registration of external information in excited states of systems at criticality reduces external wave-packets: the new model exhibits 'Objective Reduction' of wave packets. -/- 2. High internal coherence (postulated by Domash & Penrose) leading to a. Non-separable information vector bundles. b. Non-reductive states (Chalmers's criterion for experience). -/- 3. Information that is: a. encoded in coherence negentropy; b. non-digitizable, and therefore c. computationally without digital equivalent (posited by Penrose). -/- Discussion and Conclusions: instability physics implies anharmonic motion, preventing excitation quantization, and totally different from the quantum physics of simple harmonic motion at stability. Instability excitations are different from anything hitherto conceived in information science. They can model aspects of mind never previously treated, including genuine subjectivity, objective reduction of wave-packets, and inter alia all properties given above. (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)

The article presents a perspective on the scientific explanation of the subjectivity of conscious experience. It proposes plausible answers for two empirically valid questions: the ‘how’ question concerning the developmental mechanisms of subjectivity, and the ‘why’ question concerning its function. Biological individuation, which is acquired in several different stages, serves as a provisional description of how subjective perspectives may have evolved. To the extent that an individuated informational space seems the most efficient way for a given organism to select (...) biologically valuable information, subjectivity is deemed to constitute an adaptive response to informational overflow. One of the possible consequences of this view is that subjectivity might be (at least functionally) dissociated from consciousness, insofar as the former primarily facilitates selection, the latter action. (shrink)

Two decades ago, Rolf Landauer (1991) argued that “information is physical” and ought to have a role in the scientific analysis of reality comparable to that of matter, energy, space and time. This would also help to bridge the gap between biology and mathematics and physics. Although it can be argued that we are living in the ‘golden age’ of biology, both because of the great challenges posed by medicine and the environment and the significant advances that have been (...) made—especially in genetics and molecular and cell biology—we feel that information as an essential aspect of life has been neglected, or at least misunderstood. We therefore summon Maxwell’s Demon and its distant relative the ratchet, and apply these to biology. (shrink)

Biosemiotics is a growing fi eld that investigates semiotic processes in the living realm in an attempt to combine the fi ndings of the biological sciences and semiotics. Semiotic processes are more or less what biologists have typically referred to as “ signals, ” “ codes, ”and “ information processing ”in biosystems, but these processes are here understood under the more general notion of semiosis, that is, the production, action, and interpretation of signs. Thus, biosemiotics can be seen (...) as biology interpreted as a study of living sign systems — which also means that semiosis or sign process can be seen as the very nature of life itself. In other words, biosemiotics is a field of research investigating semiotic processes (meaning, signification, communication, and habit formation in living systems) and the physicochemical preconditions for sign action and interpretation. -/- (...). (shrink)

The idea that development is the expression of information accumulated during evolution and that heredity is the transmission of this information is surprisingly hard to cash out in strict, scientific terms. This paper seeks to do so using the sense of information introduced by Francis Crick in his sequence hypothesis and central dogma of molecular biology. It focuses on Crick's idea of precise determination. This is analysed using an information-theoretic measure of causal specificity. This allows us (...) to reconstruct some of Crick's claims about information in transcription and translation. Crick's approach to information has natural extensions to non-coding regions of DNA, to epigenetic marks, and to the genetic or environmental upstream causes of those epigenetic marks. Epigenetic information cannot be reduced to genetic information. The existence of biological information in epigenetic and exogenetic factors is relevant to evolution as well as to development. (shrink)

The selected effects or ‘etiological’ theory of Proper function is a naturalistic and realist account of biological teleology. It is used to analyse normativity in philosophy of language, philosophy of mind, philosophy of medicine and elsewhere. The theory has been developed with a simple and intuitive view of natural selection. Traits are selected because of their positive effects on the fitness of the organisms that have them. These ‘selected effects’ are the Proper functions of the traits. Proponents argue that (...) this analysis of biological teleology has the unique advantage that the selected effect function of a trait is also a causal explanation of the trait: the trait exists because it performs this function. We show, however, that selected effect functions as currently defined explain the existence of traits only under highly restrictive assumptions about evolutionary dynamics. In many common scenarios in which traits evolve by natural selection, selected effect functions do not explain those traits. This is because definitions of selected effect function extract from any evolutionary scenario only the information that would be explanatorily relevant in the simple evolutionary scenario implicit in those definitions. When applied to more complex scenarios selected effect functions omit the key information that is explanatorily relevant in those scenarios. The assumptions required for selected effect functions to be explanatory are particularly unlikely to hold in the domain that its proponents care most about - the evolution of representation. A more adequate selected effects theory of Proper functions may be possible, but will require much greater attention to the structure of actual evolutionary explanations. (shrink)

I present and defend a novel version of the homeostatic property cluster account of natural kinds. The core of the proposal is a development of the notion of co-occurrence, central to the HPC account, along information-theoretic lines. The resulting theory retains all the appealing features of the original formulation, while increasing its explanatory power, and formal perspicuity. I showcase the theory by applying it to the problem of reconciling the thesis that biological species are natural kinds with the (...) fact that many such species are polymorphic. (shrink)

We describe an approach to measuring biological information where ‘information’ is understood in the sense found in Francis Crick’s foundational contributions to molecular biology. Genes contain information in this sense, but so do epigenetic factors, as many biologists have recognized. The term ‘epigenetic’ is ambiguous, and we introduce a distinction between epigenetic and exogenetic inheritance to clarify one aspect of this ambiguity. These three heredity systems play complementary roles in supplying information for development. -/- We (...) then consider the evolutionary significance of the three inheritance systems. Whilst the genetic inheritance system was the key innovation in the evolution of heredity, in modern organisms the three systems each play important and complementary roles in heredity and evolution. -/- Our focus in the earlier part of the paper is on ‘proximate biology’, where information is a substantial causal factor that causes organisms to develop and causes offspring to resemble their parents. But much philosophical work has focused on information in ‘ultimate biology’. Ultimate information is a way of talking about the evolutionary design of the mechanisms of development and inheritance. We conclude by clarifying the relationship between the two. Ultimate information is not a causal factor that acts in development or heredity, but it can help to explain the evolution of proximate information, which is. (shrink)

This paper connects information with computation and cognition via concept of agents that appear at variety of levels of organization of physical/chemical/cognitive systems – from elementary particles to atoms, molecules, life-like chemical systems, to cognitive systems starting with living cells, up to organisms and ecologies. In order to obtain this generalized framework, concepts of information, computation and cognition are generalized. In this framework, nature can be seen as informational structure with computational dynamics, where an (info-computational) agent is needed (...) for the potential information of the world to actualize. Starting from the definition of information as the difference in one physical system that makes a difference in another physical system – which combines Bateson and Hewitt’s definitions, the argument is advanced for natural computation as a computational model of the dynamics of the physical world, where information processing is constantly going on, on a variety of levels of organization. This setting helps us to elucidate the relationships between computation, information, agency and cognition, within the common conceptual framework, with special relevance for biology and robotics. (shrink)

The context for biological emergence is modular hierarchical structures; their existence is what enables functional complexity to arise. Because of the openness of organisms to their environment, complete initial data (position, momentum) of all particles making up their structure is insufficient to determine future outcomes, because unpredictable new matter, energy, and information impacts each organism from the exterior. Consequently, through Darwinian evolution, life has developed processes to handle this issue functionally on short time scales as well on longer (...) developmental timescales. Symbolism and technology are the transforming factors handling this issue at the social levels, which is where the most sophisticated outcomes of openness occur. Considering the cosmological context, the issue is, should the universe itself be regarded as an open system over time? I make the case that is indeed so, because radically new outcomes occur such as the existence of aircraft, iPads, and the internet, which could not plausibly have been encoded in some form of data on the Last Scattering Surface in the expanding universe. (shrink)

Cross cultural studies have played a pivotal role in elucidating the extent to which behavioral and mental characteristics depend on specific environmental influences. Surprisingly, little field research has been carried out on a fundamentally important perceptual ability, namely the perception of biological motion. In this report, we present details of studies carried out with the help of volunteers from the Mundurucu indigene, a group of people native to Amazonian territories in Brazil. We employed standard biological motion perception tasks (...) inspired by over 30 years of laboratory research, in which observers attempt to decipher the walking direction of point-light (PL) humans and animals. Do our effortless skills at perceiving biological activity from PL animations, as revealed in laboratory settings, generalize to people who have never before seen representational depictions of human and animal activity? The results of our studies provide a clear answer to this important, previously unanswered question. Mundurucu observers readily perceived the coherent, global shape depicted in PL walkers, and experienced the classic inversion effects that are typically found when such stimuli are turned upside down. In addition, their performance was in accord with important recent findings in the literature, in the abundant ease with which they extracted direction information from local motion invariants alone. We conclude that the effortless, veridical perception of PL biological motion is a spontaneous and universal perceptual ability, occurring both inside and outside traditional laboratory environments. (shrink)

As historian Henning Schmidgen notes, the scientific study of the nervous system would have been “unthinkable” without the industrialization of communication in the 1830s. Historians have investigated extensively the way nerve physiologists have borrowed concepts and tools from the field of communications, particularly regarding the nineteenth-century work of figures like Helmholtz and in the American Cold War Era. The following focuses specifically on the interwar research of the Cambridge physiologist Edgar Douglas Adrian, and on the technology that led to his (...) Nobel-Prize-winning research, the thermionic vacuum tube. Many countries used the vacuum tube during the war for the purpose of amplifying and intercepting coded messages. These events provided a context for Adrian's evolving understanding of the nerve fiber in the 1920s. In particular, they provide the background for Adrian's transition around 1926 to describing the nerve impulse in terms of “information,” “messages,” “signals,” or even “codes,” and for translating the basic principles of the nerve, such as the all-or-none principle and adaptation, into such an “informational” context. The following also places Adrian's research in the broader context of the changing relationship between science and technology, and between physics and physiology, in the first few decades of the twentieth century. (shrink)

Biology and theology are interdependent theoretical sciences for Aristotle. In prominent discussions of the divine things (the stars and their unmoved movers) Aristotle appeals to the science of living things, and in prominent discussions of the nature of plants and animals Aristotle appeals to the nature of the divine. There is in fact a single continuous series of living things that includes gods, humans, animals, and plants, all of them in a way divine. Aristotle has this continuum of divine beings, (...) and a theory of value that corresponds to it, in mind not only in key parts of his theology and biology, but also in his practical philosophy. Here I call attention to some important texts and attempt to offer a coherent account of them, without being able to enter into the usual interpretive disputes. I begin by clarifying the terms “theology” and “biology” and their place in Aristotle's division of philosophy. Next, I discuss how Aristotle’s theology is informed by his biology, and then how his biology is informed by his theology. I end by discussing some implications of the interdependence of biology and theology for Aristotle’s ethics and exhortation to philosophy. (shrink)

The theory of evolution, which provides the conceptual framework for all modern research in organismal biology and informs research in molecular bi- ology, has gone through several stages of expansion and refinement. Darwin and Wallace (1858) of course proposed the original idea, centering on the twin concepts of natural selection and common descent. Shortly thereafter, Wallace and August Weismann worked toward the complete elimination of any Lamarckian vestiges from the theory, leaning in particular on Weismann’s (1893) concept of the separation (...) of soma and germ, resulting in what is some- times referred to as “neo-Darwinism”. (shrink)

Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- (...) tantly, modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists’ use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as ‘‘irreducible complexity’’ and on flawed analogies between living cells and mechanical factories. However, the living organ- ism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume’s criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume’s original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public. (shrink)

One of the central aims of science is explanation: scientists seek to uncover why things happen the way they do. This chapter addresses what kinds of explanations are formulated in biology, how explanatory aims influence other features of the field of biology, and the implications of all of this for biology education. Philosophical treatments of scientific explanation have been both complicated and enriched by attention to explanatory strategies in biology. Most basically, whereas traditional philosophy of science based explanation on derivation (...) from scientific laws, there are many biological explanations in which laws play little or no role. Instead, the field of biology is a natural place to turn for support for the idea that causal information is explanatory. Biology has also been used to motivate mechanistic accounts of explanation, as well as criticisms of that approach. Ultimately, the most pressing issue about explanation in biology may be how to account for the wide range of explanatory styles encountered in the field. This issue is crucial, for the aims of biological explanation influence a variety of other features of the field of biology. Explanatory aims account for the continued neglect of some central causal factors, a neglect that would otherwise be mysterious. This is linked to the persistent use of models like evolutionary game theory and population genetic models, models that are simplified to the point of unreality. These explanatory aims also offer a way to interpret many biologists’ total commitment to one or another methodological approach, and the intense disagreements that result. In my view, such debates are better understood as arising not from different theoretical commitments, but commitments to different explanatory projects. Biology education would thus be enriched by attending to approaches to biological explanation, as well as the unexpected ways that these explanatory aims influence other features of biology. I suggest five lessons for teaching about explanation in biology that follow from the considerations of this chapter. (shrink)

Synthetic biology aims at reconstructing life to put to the test the limits of our understanding. It is based on premises similar to those which permitted invention of computers, where a machine, which reproduces over time, runs a program, which replicates. The underlying heuristics explored here is that an authentic category of reality, information, must be coupled with the standard categories, matter, energy, space and time to account for what life is. The use of this still elusive category permits (...) us to interact with reality via construction of self-consistent models producing predictions which can be instantiated into experiments. While the present theory of information has much to say about the program, with the creative properties of recursivity at its heart, we almost entirely lack a theory of the information supporting the machine. We suggest that the program of life codes for processes meant to trap information which comes from the context provided by the environment of the machine. (shrink)

Modern life sciences research is increasingly relying on artificial intelligence (AI) approaches to model biological systems, primarily centered around the use of machine learning (ML) models. Although ML is undeniably useful for identifying patterns in large, complex data sets, its widespread application in biological sciences represents a significant deviation from traditional methods of scientific inquiry. As such, the interplay between these models and scientific understanding in biology is a topic with important implications for the future of scientific research, (...) yet it is a subject that has received little attention. Here, we draw from an epistemological toolkit to contextualize recent applications of ML in biological sciences under modern philosophical theories of understanding, identifying general principles that can guide the design and application of ML systems to model biological phenomena and advance scientific knowledge. We propose that conceptions of scientific understanding as information compression, qualitative intelligibility, and dependency relation modelling provide a useful framework for interpreting ML-mediated understanding of biological systems. Through a detailed analysis of two key application areas of ML in modern biological research – protein structure prediction and single cell RNA-sequencing – we explore how these features have thus far enabled ML systems to advance scientific understanding of their target phenomena, how they may guide the development of future ML models, and the key obstacles that remain in preventing ML from achieving its potential as a tool for biological discovery. Consideration of the epistemological features of ML applications in biology will improve the prospects of these methods to solve important problems and advance scientific understanding of living systems. (shrink)

This article explores the usefulness of interdisciplinarity as method of enquiry by proposing an investigation of the concept of information in the light of semiotics. This is because, as Kull, Deacon, Emmeche, Hoffmeyer and Stjernfelt state, information is an implicitly semiotic term (Biological Theory 4(2):167–173, 2009: 169), but the logical relation between semiosis and information has not been sufficiently clarified yet. Across the history of cybernetics, the concept of information undergoes an uneven development; that is, (...) information is an ‘objective’ entity in first order cybernetics, and becomes a ‘subjective’ entity in second order cybernetics. This contradiction relegates the status of information to that of a ‘true’ or ‘false’ formal logic problem. The present study proposes that a solution to this contradiction can be found in Deely’s reconfiguration of Peirce’s ‘object’ (as found in his triadic model of semiosis) into ‘thing’ and ‘object’ (Deely 1981). This ontology allows one to argue that information is neither ‘true’ nor ‘false’, and to suggest that, when considered in light of its workability, information can be both true and false, and as such it constitutes an organism’s purely objective reality (Deely 2009b). It is stated that in the process of building such a reality, information is ‘motivated’ by environmental, physiological, emotional (including past feelings and expectations) constraints which are, in turn, framed by observership. Information is therefore found in the irreducible cybersemiotic process that links at once all these conditions and that is simultaneously constrained by them. The integration of cybernetics’ and semiotics’ understanding of information shows that history is the analytical principle that grants scientific rigour to interdisciplinary investigations. As such, in any attempt to clarify its epistemological stance (e.g. the semiotic aspect of information), it is argued that biosemiotics does not need only to acknowledge semiotics (as it does), but also cybernetics in its interdisciplinary heritage. (shrink)

The concept of information and its relation to biosemiotics is a major area of contention among biosemioticians. Biosemioticians influenced by von Uexküll, Sebeok, Bateson and Peirce are critical of the way the concept as developed in information science has been applied to biology, while others believe that for biosemiotics to gain acceptance it will have to embrace information science and distance biosemiotics from Peirce’s philosophical work. Here I will defend the influence of Peirce on biosemiotics, arguing that (...) information science and biosemiotics as these were originally formulated are radically opposed research traditions. Failure to appreciate this will undermine the challenge of biosemiotics and other anti-reductionist traditions to mainstream science with its reductionist ambition to explain everything through physics. However, for this challenge to be successful, it will be necessary to respond to criticisms of Peircian ideas, jettisoning ideas that are no longer defensible and integrating ideas allied to his anti-reductionist agenda. Here I will argue that the natural philosophy of Gilbert Simondon, offering a searching critique of the application of the new concept of information and cybernetics to the life and human sciences, provides the means to defend and advance Peirce’s core ideas and thereby defend post-reductionist biosemiotics. (shrink)

Psychopathy is increasingly in the public eye. However, it is yet to be fully and effectively understood. Within the context of the DSM-IV, for example, it is best regarded as a complex family of disorders. The upside is that this family can be tightly related along common dimensions. Characteristic marks of psychopaths include a lack of guilt and remorse for paradigm case immoral actions, leading to the common conception of psychopathy rooted in affective dysfunctions. An adequate portrait of psychopathy is (...) much more complicated, however. Though some neural regions and corresponding functions are commonly indicated, they range across those responsible for action planning and learning, as well as emotional processes. Accordingly, a complete fine-grained map of all neural mechanisms responsible for psychopathy has not been realized, and even if it were, such a map would have limited utility outside of the context of surgical or chemical intervention. The utility of a neural-level understanding of psychopathy is further limited by the fact that it is only applicable in the clinical identification of individual subjects, and the neuro-chemical/biological correction of those subjects after they are positively identified as psychopaths. On the other hand, an information processing model of moral cognition provides for wider-ranging applications. The theoretical and practical implications for such a feasible working model of psychopathic personalities are assessed. Finally, this chapter raises the possibility of directed modification of social-environmental factors discouraging the development of psychopathic personalities in the first place, modifications which are also open to simulation and testing in terms of the same model of moral cognition. (shrink)

The paper provides an axiological analysis of the concepts of respect for information and of information dignity from the vantage point provided by Information Ethics and the conceptual paradigm of object-oriented analysis (OOA). The general perspective adopted is that of an ontocentric approach to the philosophy of information ethics, according to which the latter is an expansion of environmental ethics towards a less biologically biased concept of a ‘centre of ethical worth’. The paper attempts to answer (...) the following question: what is the lowest possible common set of attributes which characterises something as intrinsically valuable and an object of respect, and without which something would rightly be considered intrinsically worthless or even positively unworthy and therefore rightly disrespectable in itself? The thesis developed and defended in the paper is that the minimal condition of possibility of an object’s least intrinsic worthiness can be identified with its abstract nature as an information entity. Thus, all entities, interpreted as clusters of information, have a minimal moral worth qua information objects (i.e. qua information), that deserves to be respected. The principles elaborated in the course of the analysis are those of ‘reflective respect’ (A’s respect towards all members of A’s class motivated by A’s respect towards A not qua individual, but qua instantiation of a class of entities), ‘ontic uniformity’ (A’s recognition of A’s membership to the class of information entities) and ‘ontic solidarity’ (A’s recognition of any information entity’s dignity). (shrink)

This paper adds to the philosophical literature on mechanistic explanation by elaborating two related explanatory functions of idealisation in mechanistic models. The first function involves explaining the presence of structural/organizational features of mechanisms by reference to their role as difference-makers for performance requirements. The second involves tracking counterfactual dependency relations between features of mechanisms and features of mechanistic explanandum phenomena. To make these functions salient, we relate our discussion to an exemplar from systems biological research on the mechanism for (...) countering heat shock—the heat shock response system—in Escherichia coli bacteria. This research also reinforces a more general lesson: ontic constraint accounts in the literature on mechanistic explanation provide insufficiently informative normative appraisals of mechanistic models. We close by outlining an alternative view on the explanatory norms governing mechanistic representation. (shrink)

Cultural evolution is normally framed in informational terms. However, it is not clear whether this is an adequate way to model cultural evolutionary phenomena and what, precisely, “information” is supposed to mean in this context. Would cultural evolutionary theory benefit from a well-developed theory of cultural information? The prevailing sentiment is that, in contradistinction to biology, informational language should be used nontechnically in this context for descriptive, but not explanatory, purposes. Against this view, this article makes the case (...) for the need to take a proper biology-based “informational turn” in the cultural evolutionary sciences. I argue that the current vague use of informational language misses out on the potential benefits for advancing understanding of phenomena that information-theoretic reasoning has provided in other sciences, especially genetics. In particular, by emphasizing the informational aspects of cultural evolutionary processes, this approach can clarify some conceptual and methodological problems that have plagued cultural evolutionary theory since its inception, including (1) how to determine the channel conditions of cultural information flow, (2) the nature and scope of cultural information, and (3) how to quantify trends of cultural cumulation. More generally, theories of cultural evolution will be incomplete until the mechanisms underlying cultural processes are better understood and integrated into the explanations. This article explores the adequacy of an information-theoretic framework to accomplish these purposes. (shrink)

Essentialism in philosophy is the position that things, especially kinds of things, have essences, or sets of properties, that all members of the kind must have, and the combination of which only members of the kind do, in fact, have. It is usually thought to derive from classical Greek philosophy and in particular from Aristotle’s notion of “what it is to be” something. In biology, it has been claimed that pre-evolutionary views of living kinds, or as they are sometimes called, (...) “natu-ral kinds”, are essentialist. This static view of living things presumes that no tran-sition is possible in time or form between kinds, and that variation is regarded as accidental or inessential noise rather than important information about taxa. In contrast it is held that Darwinian, and post-Darwinian, biology relies upon varia-tion as important and inevitable properties of taxa, and that taxa are not, therefore, kinds but historical individuals. Recent attempts have been made to undercut this account, and to reinstitute essentialism in biological kind terms. Others argue that essentialism has not ever been a historical reality in biology and its predecessors. In this chapter, I shall outline the many meanings of the notion of essentialism in psychology and social science as well as science, and discuss pro- and anti-essentialist views, and some recent historical revisionism. It turns out that nobody was essentialist to speak of in the sense that is antievolutionary in biology, and that much confusion rests on treating the one word, “essence” as meaning a single notion when in fact there are many. I shall also discuss the philosophical implica-tions of essentialism, and what that means one way or the other for evolutionary biology. Teaching about evolution relies upon narratives of change in the ways the living world is conceived by biologists. This is a core narrative issue. (shrink)

The first use of the term "information" to describe the content of nervous impulse occurs 20 years prior to Shannon`s (1948) work, in Edgar Adrian`s The Basis of Sensation (1928). Although, at least throughout the 1920s and early 30s, the term "information" does not appear in Adrian`s scientific writings to describe the content of nervous impulse, the notion that the structure of nervous impulse constitutes a type of message subject to certain constraints plays an important role in all (...) of his writings throughout the period. The appearance of the concept of information in Adrian`s work raises at least two important questions: (i) what were the relevant factors that motivated Adrian`s use of the concept of information? (ii) What concept of information does Adrian appeal to, and how can it be situated in relation to contemporary philosophical accounts of the notion of information in biology? The first question involves an account of the application of communications technology in neurobiology as well as the historical and scientific background of Adrian`s major scientific achievement, which was the recording of the action potential of a single sensory neuron. The response to the second question involves an explication of Adrian`s concept of information and an evaluation of how it may be situated in relation to more contemporary philosophical explications of a semantic concept of information. I suggest that Adrian`s concept of information places limitations on the sorts of systems that are referred to as information carriers by causal and functional accounts of information. (shrink)

Clark and Chalmers claim that an external resource satisfying the following criteria counts as a memory: the agent has constant access to the resource; the information in the resource is directly available; retrieved information is automatically endorsed; information is stored as a consequence of past endorsement. Research on forgetting and metamemory shows that most of these criteria are not satisfied by biological memory, so they are inadequate. More psychologically realistic criteria generate a similar classification of standard (...) putative external memories, but the criteria still do not capture the function of memory. An adequate account of memory function, compatible with its evolution and its roles in prospection and imagination, suggests that external memory performs a function not performed by biological memory systems. External memory is thus not memory. This has implications for: extended mind theorizing, ecological validity of memory research, the causal theory of memory. (shrink)

Griffiths et al. (2015) have proposed a quantitative measure of causal specificity and used it to assess various attempts to single out genetic causes as being causally more specific than other cellular mechanisms, for example, alternative splicing. Focusing in particular on developmental processes, they have identified a number of important challenges for this project. In this discussion note, I would like to show how these challenges can be met.

The presentation proposes to complement an existing development on meaning generation for animals, humans and artificial agents by looking at what could have existed at pre-biotic times and what could be a post-human meaning generation. The core of the approach is based on an existing model for meaning generation: the Meaning Generator System (MGS). The MGS is part of an agent submitted to an internal constraint. The MGS generates a meaning when it receives information that has a connection with (...) the constraint. The generated meaning is used by the agent to implement an action (physical, biological or mental) aimed at satisfying the constraint. The action can be in or out the agent. The purpose of the presentation is to widen the MGS approach in order to reach a coverage for information, constraint and meaning from a pre-biotic level to a possible post-human one. We present the MGS for animals, humans and artificial agents with the corresponding constraints. We then look at what could have been a constraint at a pre-biotic far from thermodynamic equilibrium level. At the other end of the spectrum we look at a possible post-human status with an evolution of a ‘limit anxiety’ human constraint and also with AAs submitted to animal or human type constraints. Such approach links information science with physics, evolution, anthropology, semiotics and human mind. Continuations are proposed. (shrink)

The brain is composed of electrically excitable neuronal networks regulated by the activity of voltage-gated ion channels. Further portraying the molecular composition of the brain, however, will not reveal anything remotely reminiscent of a feeling, a sensation or a conscious experience. In classical physics, addressing the mind–brain problem is a formidable task because no physical mechanism is able to explain how the brain generates the unobservable, inner psychological world of conscious experiences and how in turn those conscious experiences steer the (...) underlying brain processes toward desired behavior. Yet, this setback does not establish that consciousness is non-physical. Modern quantum physics affirms the interplay between two types of physical entities in Hilbert space: unobservable quantum states, which are vectors describing what exists in the physical world, and quantum observables, which are operators describing what can be observed in quantum measurements. Quantum no-go theorems further provide a framework for studying quantum brain dynamics, which has to be governed by a physically admissible Hamiltonian. Comprising consciousness of unobservable quantum information integrated in quantum brain states explains the origin of the inner privacy of conscious experiences and revisits the dynamic timescale of conscious processes to picosecond conformational transitions of neural biomolecules. The observable brain is then an objective construction created from classical bits of information, which are bound by Holevo’s theorem, and obtained through the measurement of quantum brain observables. Thus, quantum information theory clarifies the distinction between the unobservable mind and the observable brain, and supports a solid physical foundation for consciousness research. (shrink)

Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological (...) research practice shows the need for quantitative, probabilistic models of mechanisms, too. In this paper we argue that the formal framework of causal graph theory is well-suited to provide us with models of biological mechanisms that incorporate quantitative and probabilistic information. On the ba-sis of an example from contemporary biological practice, namely feedback regulation of fatty acid biosynthesis in Brassica napus, we show that causal graph theoretical models can account for feedback as well as for the multi-level character of mechanisms. However, we do not claim that causal graph theoretical representations of mechanisms are advantageous in all respects and should replace common qualitative models. Rather, we endorse the more balanced view that causal graph theoretical models of mechanisms are useful for some purposes, while being insufficient for others. (shrink)

A model of brain function is presented that is consistently based on the biological principle of equilibrium. The neuronal modules of the cerebral cortex are proposed as units in which equilibrium between incoming signals and the synaptic structure is determined or established. Because of the electromagnetic activity of the brain, the electromagnetic properties of thecells are brought into focus. Due to the synaptic changes of the modules -essentially during sleep -an electromagnetic resting balance between the modules is established. Incoming (...) signals during the day, disturb the electromagnetic resting equilibrium and are detected and understood by this. The connecting nodes within the neuronal network are given by the equilibrium modules. Incoming information is represented in the form of the specific pathway of the network, while recognized information is represented by the equilibrium states within the modules. The paper leads to an understanding of information storage and processing in the brain. It even provides a hypothesis for understanding the emergence of the "self". Finally, the consideration of electromagnetic wave properties of neurons opens up a biophysical starting point to understanding conscious perceptions. In neuroscience, we lack a unifying theory of the brain. The reason for this may be an important detail –a missing link –that we do not yet see. Following the "track of biological equilibrium" in this paper leads to the hypothesis that the electromagnetic properties of the neurons are potential candidates to fill that gap. A hypothesis is developed describing their physiological significance in the processing of neurological information. (shrink)

As biological and biomedical research increasingly reference the environmental context of the biological entities under study, the need for formalisation and standardisation of environment descriptors is growing. The Environment Ontology (ENVO) is a community-led, open project which seeks to provide an ontology for specifying a wide range of environments relevant to multiple life science disciplines and, through an open participation model, to accommodate the terminological requirements of all those needing to annotate data using ontology classes. This paper summarises (...) ENVO’s motivation, content, structure, adoption, and governance approach. (shrink)

Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value (...) from data sets them. However, such ‘minimum information’ MI checklists are usually developed independently by groups working within representatives of particular biologically- or technologically-delineated domains. Consequently, an overview of the full range of checklists can be difficult to establish without intensive searching, and even tracking thetheir individual evolution of single checklists may be a non-trivial exercise. Checklists are also inevitably partially redundant when measured one against another, and where they overlap is far from straightforward. Furthermore, conflicts in scope and arbitrary decisions on wording and sub-structuring make integration difficult. This presents inhibit their use in combination. Overall, these issues present significant difficulties for the users of checklists, especially those in areas such as systems biology, who routinely combine information from multiple biological domains and technology platforms. To address all of the above, we present MIBBI (Minimum Information for Biological and Biomedical Investigations); a web-based communal resource for such checklists, designed to act as a ‘one-stop shop’ for those exploring the range of extant checklist projects, and to foster collaborative, integrative development and ultimately promote gradual integration of checklists. (shrink)

Racial constructionists, anti-naturalists, and anti-realists have challenged users of the biological race concept to provide and defend, from the perspective of biology, biological philosophy, and ethics, a biologically informed concept of race. In this paper, an ontoepistemology of biology is developed. What it is, by this, to be "biological real" and "biologically meaningful" and to represent a "biological natural division" is explained. Early 18th century race concepts are discussed in detail and are shown to be both (...) sensible and not greatly dissimilar to modern concepts. A general biological race concept (GBRC) is developed. It is explained what the GBRC does and does not entail and how this concept unifies the plethora of specific ones, past and present. Other race concepts as developed in the philosophical literature are discussed in relation to the GBRC. The sense in which races are both real and natural is explained. Racial essentialism of the relational sort is shown to be coherent. Next, the GBRC is discussed in relation to anthropological discourse. Traditional human racial classifications are defended from common criticisms: historical incoherence, arbitrariness, cluster discordance, etc. Whether or not these traditional human races could qualify as taxa subspecies – or even species – is considered. It is argued that they could qualify as taxa subspecies by liberal readings of conventional standards. Further, it is pointed out that some species concepts potentially allow certain human populations to be designated as species. It is explained why, by conventional population genetic and statistical standards, genetic differences between major human racial groups are at least moderate. Behavioral genetic differences associated with human races are discussed in general and in specific. The matter of race differences in cognitive ability is briefly considered. Finally, the race concept is defended from various criticisms. First, logical and empirical critiques are dissected. These include: biological scientific, sociological, ontological, onto-epistemological, semantic, and teleological arguments. None are found to have any merit. Second, moral-based arguments are investigated in context to a general ethical frame and are counter-critiqued. Racial inequality, racial nepotism, and the “Racial Worldview" are discussed. What is dubbed the Anti-Racial Worldview is rejected on both empirical and moral grounds. Finally, an area of future investigation – the politics of the destruction of the race concept – is pointed to. (shrink)

Learning from contemporary natural, formal, and social sciences, especially from current biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (...) (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence. (shrink)

Terms loaded with informational connotations are often employed to refer to genes and their dynamics. Indeed, genes are usually perceived by biologists as basically ‘the carriers of hereditary information.’ Nevertheless, a number of researchers consider such talk as inadequate and ‘just metaphorical,’ thus expressing a skepticism about the use of the term ‘information’ and its derivatives in biology as a natural science. First, because the meaning of that term in biology is not as precise as it is, for (...) instance, in the mathematical theory of communication. Second, because it seems to refer to a purported semantic property of genes without theoretically clarifying if any genuinely intrinsic semantics is involved. Biosemiotics, a field that attempts to analyze biological systems as semiotic systems, makes it possible to advance in the understanding of the concept of information in biology. From the perspective of Peircean biosemiotics, we develop here an account of genes as signs, including a detailed analysis of two fundamental processes in the genetic information system (transcription and protein synthesis) that have not been made so far in this field of research. Furthermore, we propose here an account of information based on Peircean semiotics and apply it to our analysis of transcription and protein synthesis. (shrink)

Causal selection is the task of picking out, from a field of known causally relevant factors, some factors as elements of an explanation. The Causal Parity Thesis in the philosophy of biology challenges the usual ways of making such selections among different causes operating in a developing organism. The main target of this thesis is usually gene centrism, the doctrine that genes play some special role in ontogeny, which is often described in terms of information-bearing or programming. This paper (...) is concerned with the attempt of confronting the challenge coming from the Causal Parity Thesis by offering principles of causal selection that are spelled out in terms of an explicit philosophical account of causation, namely an interventionist account. I show that two such accounts that have been developed, although they contain important insights about causation in biology, nonetheless fail to provide an adequate reply to the Causal Parity challenge: Ken Waters's account of actual-difference making and Jim Woodward's account of causal specificity. A combination of the two also doesn't do the trick, nor does Laura Franklin-Hall's account of explanation (in this volume). We need additional conceptual resources. I argue that the resources we need consist in a special class of counterfactual conditionals, namely counterfactuals the antecedents of which describe biologically normal interventions. (shrink)

Schröedinger’s question “what is life?” was a real challenge for the scientific community and this still remains as an opened question, because in spite of the important advances in various scientific branches like philosophy, biology, chemistry and physics,, each of them assesses life from its particular point of view to explain the life’ characteristic features, so not a coherent and well structured general model of life was reported. In this paper life is approached from informational perspective, starting from earlier Draganeacu's (...) philosophic concepts, showing that actually life is structured by matter and information. Therefore, it is analyzed carbon-matter properties on the basis of which the living structures are composed, giving rise not only of a considerable number of carbon-based compounds, but serving now beside silicon, as an useful material for micro/nanostructure applications. Such specific properties refers to the high ability of carbon to associate/dissociate in chemical reactions regulated/facilitated by informational (Bit unit) YES/NO bistable mechanisms to form macro/small molecules with complementary properties, reactive info-functional pathways of transduction, relaying, amplification, integration, spreading, modulation, activation and positive/negative feedback reactions, like in the informational microelectronic/microsystems circuits. It is argued that the negentropy invoked earlier in Schrödinger's analysis is a consequence of informational-assisted structuration/organization of the cell and human organism. From the analysis of inter/intra-communication mechanisms in the cell and comparing with the outcomes described by the Informational Model of Human Body, it is deduced that, the living organisms operate on the basis of three main streaming circuits assuring the living functions: (1) the metabolic matter-related circuit; (2) the operative informational circuit; (3) the epigenetic informational circuit for the gradual integration of information in the central informational structure – DNA. It is founded on these bases the Informational Model of the Living Structures, and the Informational System of the Living Structures (ISLS), with similar functions on the entire living scale size, from unitary to multicellular living structures, composed by seven informational systems, namely [CASI (center of acquisition and storing of information), CDC (center of decision and command), IRSS (info-reactive sentient system), MIS (maintenance info-system), GTS (genetic transmission system), IGG (info-genetic generator) and IC (info-connection)]ISLS, and are identified the specific functions of each of them. The living structures operate thus like self-“polarized" bipolar info-matter informational devices by means of the stand-by metabolic matter-related circuit, and react/respond to the external/internal informational stimuli, which modulate their functionality, returning an external reaction signal (“attitude"), for adaptation and survival. (shrink)

We introduce the virtual special issue on content in signalling systems. The issue explores the uses and limits of ideas from evolutionary game theory and information theory for explaining the content of biological signals. We explain the basic idea of the Lewis-Skyrms sender-receiver framework, and we highlight three key themes of the issue: (i) the challenge of accounting for deception, misinformation and false content, (ii) the relevance of partial or total common interest to the evolution of meaningful signals, (...) and (iii) how the sender-receiver framework relates to teleosemantics. (shrink)

We undeniably live in an information age—as, indeed, did those who lived before us. After all, as the cultural historian Robert Darnton pointed out: ‘every age was an age of information, each in its own way’ (Darnton 2000: 1). Darnton was referring to the news media, but his insight surely also applies to the sciences. The practices of acquiring, storing, labeling, organizing, retrieving, mobilizing, and integrating data about the natural world has always been an enabling aspect of scientific (...) work. Natural history and its descendant discipline of biological taxonomy are prime examples of sciences dedicated to creating and managing systems of ordering data. In some sense, the idea of biological taxonomy as an information science is commonplace. Perhaps it is because of its self-evidence that the information science perspective on taxonomy has not been a major theme in the history and philosophy of science. The botanist Vernon Heywood once pointed out that historians of biology, in their ‘preoccupation with the development of the sciences of botany and zoology… [have] diverted attention from the role of taxonomy as an information science’ (Heywood 1985: 11). More specifically, he argued that historians had failed to appreciate how principles and practices that can be traced to Linnaeus constituted ‘a change in the nature of taxonomy from a local or limited folk communication system and later a codified folk taxonomy to a formal system of information science [that] marked a watershed in the history of biology’ (ibid.). A similar observation could be made about twentieth-century philosophy of biology, which mostly skipped over practical and epistemic questions about information management in taxonomy. The taxonomic themes that featured in the emerging philosophy of biology literature in the second half of the twentieth century were predominantly metaphysical in orientation. This is illustrated by what has become known as the ‘essentialism story’: an account about the essentialist nature of pre- Darwinian taxonomy that used to be accepted by many historians and philosophers, and which stimulated efforts to document and interpret shifts in the metaphysical understanding of species and (natural) classification (Richards 2010; Winsor 2003; Wilkins 2009). Although contemporary debates in the philosophy of taxonomy have moved on, much discussion continues to focus on conceptual and metaphysical issues surrounding the nature of species and the principles of classification. Discussions centring on whether species are individuals, classes, or kinds have sprung up as predictably as perennials. Raucous debates have arisen even with the aim of accommodating the diversity of views: is monism, pluralism, or eliminativism about the species category the best position to take? In addition to these, our disciplines continue to interrogate what is the nature of these different approaches to classification: are they representational or inferential roles of different approaches to classification (evolutionary taxonomy, phenetics, phylogenetic systematics)? While there is still much to learn from these discussions—in which we both actively participate—our aim with this topical collection has been to seek different entrypoints and address underexposed themes in the history and philosophy of taxonomy. We believe that approaching taxonomy as an information science prompts new questions and can open up new philosophical vistas worth exploring. A twenty-first century information science turn in the history and philosophy of taxonomy is already underway. In scientific practice and in daily life it is hard to escape the imaginaries of Big Data and the constant threats of being ‘flooded with data’. In the life sciences, these developments are often associated with the socalled bioinformatics crisis that can hopefully be contained by a new, interdisciplinary breed of bioinformaticians. These new concepts, narratives, and developments surrounding the centrality of data and information systems in the biological and biomedical sciences have raised important philosophical questions about their challenges and implications. But historical perspectives are just as necessary to judge what makes our information age different from those that preceded us. Indeed, as the British zoologist Charles Godfray has often pointed out, the piles of data that are being generated in contemporary systematic biology have led to a second bioinformatics crisis, the first being the one that confronted Linnaeus in the mid-18th century (Godfray 2007). Although our aim is to clear a path for new discussions of taxonomy from an information science-informed point of view, we continue where others in the history, philosophy, and sociology of science have already trod. We believe that an appreciation of biological taxonomy as an information science raises many questions about the philosophical, theoretical, material, and practical aspects of the use and revision of biological nomenclatures in different local and global communities of scientists and citizen scientists. In particular, conceiving of taxonomy as an information science directs attention to the temporalities of managing an accumulating data about classified entities that are themselves subject to revision, to the means by which revision is accomplished, and to the semantic, material, and collaborative contexts that mediate the execution of revisions. (shrink)

The term “Complex Systems Biology” was introduced a few years ago [Kaneko, 2006] and, although not yet of widespread use, it seems particularly well suited to indicate an approach to biology which is well rooted in complex systems science. Although broad generalizations are always dangerous, it is safe to state that mainstream biology has been largely dominated by a gene-centric view in the last decades, due to the success of molecular biology. So the one gene - one trait approch, which (...) has often proved to be effective, has been extended to cover even complex traits. This simplifying view has been appropriately criticized, and the movement called systems biology has taken off. Systems biology [Noble, 2006] emphasizes the presence of several feedback loops in biological systems, which severely limit the range of validity of explanations based upon linear causal chains (e.g. gene → behaviour). Mathematical modelling is one the favourite tools of systems biologists to analyze the possible effects of competing negative and positive feedback loops which can be observed at several levels (from molecules to organelles, cells, tissues, organs, organisms, ecosystems). Systems biology is by now a well-established field, as it can be inferred by the rapid growth in number of conferences and journals devoted to it, as well as by the existence of several grants and funded projects.Systems biology is mainly focused upon the description of specific biological items, like for example specific organisms, or specific organs in a class of animals, or specific genetic-metabolic circuits. It therefore leaves open the issue of the search for general principles of biological organization, which apply to all living beings or to at least to broad classes. We know indeed that there are some principles of this kind, biological evolution being the most famous one. The theory of cellular organization also qualifies as a general principle. But the main focus of biological research has been that of studying specific cases, with some reluctance to accept (and perhaps a limited interest for) broad generalizations. This may however change, and this is indeed the challenge of complex systems biology: looking for general principles in biological systems, in the spirit of complex systems science which searches for similar features and behaviours in various kinds of systems. The hope to find such general principles appears well founded, and I will show in Section 2 that there are indeed data which provide support to this claim. Besides data, there are also general ideas and models concerning the way in which biological systems work. The strategy, in this case, is that of introducing simplified models of biological organisms or processes, and to look for their generic properties: this term, borrowed from statistical physics, is used for those properties which are shared by a wide class of systems. In order to model these properties, the most effective approach has been so far that of using ensembles of systems, where each member can be different from another one, and to look for those properties which are widespread. This approach was introduced many years ago [Kauffman, 1971] in modelling gene regulatory networks. At that time one had very few information about the way in which the expression of a given gene affects that of other genes, apart from the fact that this influence is real and can be studied in few selected cases (like e.g. the lactose metabolism in E. coli). Today, after many years of triumphs of molecular biology, much more has been discovered, however the possibility of describing a complete map of gene-gene interactions in a moderately complex organism is still out of reach. Therefore the goal of fully describing a network of interacting genes in a real organism could not be (and still cannot be) achieved. But a different approach has proven very fruitful, that of asking what are the typical properties of such a set of interacting genes. Making some plausible hypotheses and introducing some simplifying assumptions, Kauffman was able to address some important problems. In particular, he drew attention to the fact that a dynamical system of interacting genes displays selforganizing properties which explain some key aspects of life, most notably the existence of a limited number of cellular types in every multicellular organism (these numbers are of the order of a few hundreds, while the number of theoretically possible types, absent interactions, would be much much larger than the number of protons in the universe). In section 3 I will describe the ensemble based approach in the context of gene regulatory networks, and I will show that it can describe some important experimental data. Finally, in section 4 I will discuss some methodological aspects. (shrink)

There has recently been an explosion of formal models of signalling, which have been developed to learn about different aspects of meaning. This paper discusses whether that success can also be used to provide an original naturalistic theory of meaning in terms of information or some related notion. In particular, it argues that, although these models can teach us a lot about different aspects of content, at the moment they fail to support the idea that meaning just is some (...) kind of information. As an alternative, I suggest a more modest approach to the relationship between informational notions used in models and semantic properties in the natural world. (shrink)