In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...) the context they are embedded within—and hence by the web of relations they are part of. (shrink)

This article considers interventionist arguments for downward causation and non-fundamental level causal explanation from the point of view of inferring causation from experiments. Several authors have utilised the interventionist theory of causal explanation to argue that the causal exclusion argument is moot and that higher-level as well as downward causation is real. I show that this argument can be made when levels are understood as levels of grain, leaving us with a choice between causal explanations pitched at different levels. Causal (...) proportionality has been suggested as a principle for choosing the correct level of description for causal explanations, but this suggestion has serious problems. I offer an alternative principle, based on the idea that explanations should track actual difference-makers. I then consider claims about systems causally influencing their own parts. Such claims risk conceptual confusion for the same reason as the exclusion argument, by conflating causal and constitutive dependencies. The distinction between causation and constitution is used to give criteria for the correct use of the idea of downward causation. (shrink)

Defending Robert Rosen’s claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling’s demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive (...) tradition of anti-reductionist biomathematics. It is shown that the mathematicoephysico echemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this antireductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics. (shrink)

Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems “as a whole.” Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call “modular reductionism” and “bottom-up reductionism.” Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies (...) of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood “bottom-up.” Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. (shrink)

Which domains of biology do philosophers of biology primarily study? The fact that philosophy of biology has been dominated by an interest for evolutionary biology is widely admitted, but it has not been strictly demonstrated. Here I analyse the topics of all the papers published in Biology & Philosophy, just as the journal celebrates its thirtieth anniversary. I then compare the distribution of biological topics in Biology & Philosophy with that of the scientific journal Proceedings of the National Academy of (...) Science of the USA, focusing on the recent period 2003–2015. This comparison reveals a significant mismatch between the distributions of these topics. I examine plausible explanations for that mismatch. Finally, I argue that many biological topics underrepresented in philosophy of biology raise important philosophical issues and should therefore play a more central role in future philosophy of biology. (shrink)

Medicalization is frequently defined as a process by which some non-medical aspects of human life become to be considered as medical problems. Overdiagnosis, on the other hand, is most often defined as diagnosing a biomedical condition that in the absence of testing would not cause symptoms or death in the person’s lifetime. Medicalization and overdiagnosis are related concepts as both expand the extension of the concept of disease. They are both often used normatively to critique unwarranted or contested expansion of (...) medicine and to address health services that are considered to be unnecessary, futile, or even harmful. However, there are important differences between the concepts, as not all cases of overdiagnosis are medicalizations and not all cases of medicalizations are overdiagnosis. The objective of this article is to clarify the differences between medicalization and overdiagnosis. It will demonstrate how the subject matter of medicalization traditionally has been non-medical (social or cultural everyday life) phenomena, while the subject matter of overdiagnosis has been biological or biomolecular conditions or processes acknowledged being potentially harmful. They also refer to different types of uncertainty: medicalization is concerned with indeterminacy, while overdiagnosis is concerned with lack of prognostic knowledge. Medicalization is dealing with sickness (sick role) while overdiagnosis with disease. Despite these differences, medicalization and overdiagnosis are becoming more alike. Medicalization is expanding, encompassing the more “technical” aspects of overdiagnosis, while overdiagnosis is becoming more ideologized. Moreover, with new trends in modern medicine, such as P4 (preventive, predictive, personal, and participatory) medicine, medicalization will become all-encompassing, while overdiagnosis more or less may dissolve. In the end they may converge in some total “iatrogenization.” In doing so, the concepts may lose their precision and critical sting. (shrink)

The emerging concept of systems medicine (or ‘P4 medicine’—predictive, preventive, personalized and participatory) is at the vanguard of the post-genomic movement towards ‘precision medicine’. It is the medical application of systems biology, the biological study of wholes. Of particular interest, P4 systems medicine is currently promised as a revolutionary new biomedical approach that is holistic rather than reductionist. This article analyzes its concept of holism, both with regard to methods and conceptualization of health and disease. Rather than representing a medical (...) holism associated with basic humanistic ideas, we find a technoscientific holism resulting from altered technological and theoretical circumstances in biology. We argue that this holism, which is aimed at disease prevention and health optimization, points towards an expanded form of medicalization, which we call ‘holistic medicalization’: Each person’s whole life process is defined in biomedical, technoscientific terms as quantifiable and controllable and underlain a regime of medical control that is holistic in that it is all-encompassing. It is directed at all levels of functioning, from the molecular to the social, continual throughout life and aimed at managing the whole continuum from cure of disease to optimization of health. We argue that this medicalization is a very concrete materialization of a broader trend in medicine and society, which we call ‘the medicalization of health and life itself’. We explicate this holistic medicalization, discuss potential harms and conclude by calling for preventive measures aimed at avoiding eventual harmful effects of overmedicalization in systems medicine (quaternary prevention). (shrink)

Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. However, (...) I argue that this is only part of the epistemology of causal selection. Recent work on portable causes has implicitly assumed them to be portable within the same causal system at a later time. As a result, it has appeared that the objective content of causal selection includes only facts about the causal structure of that single system. In contrast, I present a case study from systems biology in which scientists are searching for causal factors that are portable across rather than within causal systems. By paying careful attention to how these biologists find portable causes, I show that the objective content of causal selection can extend beyond the immediate systems of interest. In particular, knowledge of the evolutionary history of gene networks is necessary for correctly identifying causal patterns in these networks that explain cellular behavior in a portable way. (shrink)

A number of areas of biology raise questions about what is of value in the natural environment and how we ought to behave towards it: conservation biology, environmental science, and ecology, to name a few. Based on my experience teaching students from these and similar majors, I argue that the field of environmental ethics has much to teach these students. They come to me with pent-up questions and a feeling that more is needed to fully engage in their subjects, and (...) I believe some exposure to environmental ethics can help focus their interests and goals. I identify three primary areas in which environmental ethics can con- tribute to their education. The first is an examination of who (or what) should be considered to be part of our moral community (i.e., the community to whom we owe direct duties). Is it humans only? Or does it include all sentient life? Or all life? Or ecosystems considered holistically? Often, readings implicitly assume one or more of these answers; the goal is to make the student more sensitive to these implicit claims and to get them to think about the different reasons that support them. The second area, related to the first, is the application of the different answers concerning the extent of the ethical community to real environmental issues and problems. Students need to be aware of how the different answers concerning the moral community can imply conflicting answers for how we should act in certain cases and to think about ways to move toward conflict resolution. The third area in which environmental ethics can contribute is a more conceptual one, focusing on central concepts such as biodiversity, sustainability, species, and ecosystems. Exploring and evaluating various meanings of these terms will make students more reflective and thoughtful citizens and biologists, sensitive to the implications that different conceptual choices make. (shrink)

Synthetic biology is an umbrella term that covers a range of aims, approaches, and techniques. They are all brought together by common practices of analogizing, synthesizing, mechanicizing, and kludging. With a focus on kludging as the connection point between biology, engineering, and evolution, I show how synthetic biology’s successes depend on custom-built kludges and a creative, “make-it-work” attitude to the construction of biological systems. Such practices do not fit neatly, however, into synthetic biology’s celebration of rational design. Nor do they (...) straightforwardly embody Richard Feynman’s “last blackboard” statement that without creating something it cannot be understood. Reflecting further on the relationship between synthetic construction and knowledge making gives philosophy of science new avenues of insight into scientific practice. (shrink)

According to conventional wisdom, local gauge symmetry is not a symmetry of nature, but an artifact of how our theories represent nature. But a study of the so-called theta-vacuum appears to refute this view. The ground state of a quantized non-Abelian Yang-Mills gauge theory is characterized by a real-valued, dimensionless parameter theta—a fundamental new constant of nature. The structure of this vacuum state is often said to arise from a degeneracy of the vacuum of the corresponding classical theory, which degeneracy (...) allegedly arises from the fact that “large” (but not “small”) local gauge transformations connect physically distinct states of zero field energy. If that is right, then some local gauge transformations do generate empirical symmetries. In defending conventional wisdom against this challenge I hope to clarify the meaning of empirical symmetry while deepening our understanding of gauge transformations. I distinguish empirical from theoretical symmetries. Using Galileo’s ship and Faraday’s cube as illustrations, I say when an empirical symmetry is implied by a theoretical symmetry. I explain how the theta-vacuum arises, and how “large” gauge transformations differ from “small” ones. I then present two analogies from elementary quantum mechanics. By applying my analysis of the relation between empirical and theoretical symmetries, I show which analogy faithfully portrays the character of the vacuum state of a classical non-Abelian Yang-Mills gauge theory. The upshot is that “large” as well as “small” gauge transformations are purely formal symmetries of non-Abelian Yang-Mills gauge theories, whether classical or quantized. It is still worth distinguishing between these kinds of symmetries. An analysis of gauge within the constrained-Hamiltonian formalism yields the result that “large” gauge transformations should not be classified as gauge transformations; indeed, nor should “global” gauge transformations. In a theory in which boundary conditions are modeled dynamically, “global” gauge transformations may be associated with physical symmetries, corresponding to translations of these extra dynamical variables. Such translations are symmetries if and only if charge is conserved. But it is hard to argue that these symmetries are empirical, and in any case they do not correspond to any constant phase change in a quantum state. (shrink)

Twentieth-century theoretical efforts towards the articulation of general system properties came short of having the significant impact on biological practice that their proponents envisioned. Although the latter did arrive at preliminary mathematical formulations of such properties, they had little success in showing how these could be productively incorporated into the research agenda of biologists. Consequently, the gap that kept system-theoretic principles cut-off from biological experimentation persisted. More recently, however, simple theoretical tools have proved readily applicable within the context of systems (...) biology. In particular, examples reviewed in this paper suggest that rigorous mathematical expressions of design principles, imported primarily from engineering, could produce experimentally confirmable predictions of the regulatory properties of small biological networks. But this is not enough for contemporary systems biologists who adopt the holistic aspirations of early systemologists, seeking high-level organizing principles that could provide insights into problems of biological complexity at the whole-system level. While the presented evidence is not conclusive about whether this strategy could lead to the realization of the lofty goal of a comprehensive explanatory integration, it suggests that the ongoing quest for organizing principles is pragmatically advantageous for systems biologists. The formalisms postulated in the course of this process can serve as bridges between system-theoretic concepts and the results of molecular experimentation: they constitute theoretical tools for generalizing molecular data, thus producing increasingly accurate explanations of system-wide phenomena. (shrink)

Tema rada su dva tipa emergencije unutar razumevanja bioloških entiteta: a) epistemološka i b) ontološka emergencija. Iako postoji obimna literatura posvećena ovom pojmu (njegovim tipovima, čak i vrstama), tvrdimo da se pojam ontološke emergencije najčešće pogrešno primenjuje u naučnim i filozofskim objašnjenjima kompleksnih sistema, stoga ga formulišemo na drugačiji način. Da bismo istakli u čemu je distinktivno svojstvo jednog tipa u odnosu na drugi, i time dali doprinos boljem razumevanju kompleksnosti biosfere, za tip a) koristimo konvencionalno prihvaćen model za reprezentovanje (...) genetičkih regulatornih mreža, dok za tip b) obrazlažemo zašto treba da bude predstavljen egzaptacijama. Cilj naše analize je da ukaže, polazeći od osnovnih pretpostavki sistemske biologije, na koji način pojam emergencije ima značajno mesto u današnjoj filozofiji nauke i teorijskoj biologiji. (shrink)

In recent cancer research, strong and apparently conflicting epistemological stances have been advocated by different research teams in a mist of an ever-growing body of knowledge ignited by ever-more perplexing and non-conclusive experimental facts: in the past few years, an 'organicist' approach investigating cancer development at the tissue level has challenged the established and so-called 'reductionist' approach focusing on disentangling the genetic and molecular circuitry of carcinogenesis. This article reviews the ways in which 'organicism' and 'reductionism' are used and opposed (...) in this context, with an aim at clarifying the debate. Methodological, epistemological and ontological implications of both approaches are discussed. We argue that the 'organicist/reductionist' opposition in the present case of carcinogenesis is more a matter of diverging heuristics than a claim about theoretical or ontological (ir)reducibility. As a matter of fact, except for the downward causation claim, which we question, we argue that the organicist arguments are compatible with the reductionist approach. Moreover, we speculate that both approaches, which currently focus on specific entities i.e., genes versus tissues, will need to shift their conceptual frameworks to studying complex arrays of relationships potentially ranging over several levels of entities, as is the case with 'systems biology'. (shrink)

Synthetic biology is rather a new field of science and technology. Societal, regulatory, legal, ethical, safety and security aspects of this field have already been analysed in much detail and discussed very widely in recent years. There is, however, a dearth of empirical studies on the points of view of relevant stakeholders in countries where SB is still in the process of emergence. Slovenia is one of them, and accordingly, the article analyses the situation of SB in this small country, (...) focusing on the points of view of various stakeholder groups concerning three aspects of SB: the policy framework, the ethical-legal discourse and the issues of biosafety and biosecurity. It is argued that Slovenia has missed many opportunities to foster the domestic development of the field; in particular, considering that at an early stage, young Slovenian researchers participated very successfully in the International Genetically Engineered Machine competition. (shrink)

Integrative systems biology is among the most innovative fields of contemporary science, bringing together scientists from a range of diverse backgrounds and disciplines to tackle biological complexity through computational and mathematical modeling. The result is a plethora of problem-solving techniques, theoretical perspectives, lab-structures and organizations, and identity labels that have made it difficult for commentators to pin down precisely what systems biology is, philosophically or sociologically. In this paper, through the ethnographic investigation of two ISB laboratories, we explore the particular (...) structural features of ISB thinking and organization and its relations to other disciplines that necessitate cognitive innovation at all levels from lab PI’s to individual researchers. We find that systems biologists face numerous constraints that make the production of models far from straight-forward, while at the same time they inhabit largely unstructured task environments in comparison to other fields. We refer to these environments as adaptive problem spaces. These environments they handle by relying substantially on the flexibility and affordances of model-based reasoning to integrate these various constraints and find novel adaptive solutions. Ultimately what is driving this innovation is a determination to construct new cognitive niches in the form of functional model building frameworks that integrate systems biology within the biological sciences. The result is an industry of diverse and different innovative practices and solutions to the problem of modeling complex, large-scale biological systems. (shrink)

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific practices address the (...) challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must meet to achieve these objectives as predictive robustness—predictive reliability over large domains. Drawing on the results of an ethnographic investigation and various studies in the systems biology literature, I explore four current obstacles to (...) achieving predictive robustness; data constraints, parameter uncertainty, collaborative constraints and system-scale requirements. I use a case study and the commentary of systems biologists themselves to show that current practices in the field, rather than pursuing these goals, frequently use models heuristically to investigate and build understanding of biological systems that do not meet standards of predictive robustness but are nonetheless effective uses of computation. A more heuristic conception of modeling allows us to interpret current practices as ways that manage these obstacles more effectively, particularly collaborative constraints, such that modelers can in the long-run at least work towards prediction and control. (shrink)

The importation of computational methods into biology is generating novel methodological strategies for managing complexity which philosophers are only just starting to explore and elaborate. This paper aims to enrich our understanding of methodology in integrative systems biology, which is developing novel epistemic and cognitive strategies for managing complex problem-solving tasks. We illustrate this through developing a case study of a bimodal researcher from our ethnographic investigation of two systems biology research labs. The researcher constructed models of metabolic and cell-signaling (...) pathways by conducting her own wet-lab experimentation while building simulation models. We show how this coupling of experiment and simulation enabled her to build and validate her models and also triangulate and localize errors and uncertainties in them. This method can be contrasted with the unimodal modeling strategy in systems biology which relies more on mathematical or algorithmic methods to reduce complexity. We discuss the relative affordances and limitations of these strategies, which represent distinct opinions in the field about how to handle the investigation of complex biological systems. (shrink)

In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systems biology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a stable, robust result. Finally, (...) we analyze the alternative role and meaning theory has in systems biology expressed as canonical template theories like Biochemical Systems Theory. (shrink)

The systems view on life and its emergence from complex chemistry has remarkably increased the scientific attention on metabolism in the last two decades. However, during this time there has not been much theoretical discussion on what constitutes a metabolism and what role it actually played in biogenesis. A critical and updated review on the topic is here offered, including some references to classical models from last century, but focusing more on current and future research. Metabolism is considered as intrinsically (...) related to the living but not necessarily equivalent to it. More precisely, the idea of “minimal metabolism”, in contrast to previous, top‐down conceptions, is formulated as a heuristic construct, halfway between chemistry and biology. Thus, rather than providing a complete or final characterization of metabolism, our aim is to encourage further investigations on it, particularly in the context of life's origin, for which some concrete methodological suggestions are provided. Also see the video abstract here:https://youtu.be/DP7VMKk2qpA. (shrink)

There is a trend within philosophy of biology to concentrate on questions that are strongly related to particular biological research programs rather than on the general scope of the field and its relation to other sciences. Projects of the latter kind, of course, are followed as well but will not be the topic of this review. Shifting the focus to particular research programs reflects philosophers’ increased interest in knowledge of, and contribution to, actual biological research, which is organized in such (...) programs. It is accompanied by the increasing enthusiasm of biologists to involve philosophers in the conceptual work of theoretical biology. I concentrate on the philosophies of four biological research programs, three of which are devoted to evolutionary biology, which is still the main field of interest among philosophers of biology: adaptationism, EvoDevo, and the developmental systems approach. In addition, a short sketch of the newly emerging philosophy of systems biology is given. Several lines of philosophical inquiry can be found in all of the fields considered here: philosophy contributes to the conceptual development of biological research programs, it analyzes structures and delineations of particular research programs, and sometimes it is involved in a comparative assessment of biological programs as well. Philosophical projects that start from the level of a particular research program may give rise to a bottom-up perspective on biology and allow for an integrative view of biological research. This may open up the opportunity to tackle “larger” questions again in an altered and fruitful manner. (shrink)

A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...) scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

Embryonic development and adult tissue homeostasis are controlled through activation of intracellular signal transduction pathways by extracellular growth factors. In the past, signal transduction has largely been regarded as a linear process. However, more recent data from large‐scale and high‐throughput experiments indicate that there is extensive cross‐talk between individual signaling cascades leading to the notion of a signaling network. The behavior of such complex networks cannot be predicted by simple intuitive approaches but requires sophisticated models and computational simulations. The purpose (...) of such models is to generate experimentally testable hypotheses and to find explanations for unexpected experimental results. Here, we discuss the need for, and the future impact of, mathematical models for exploring signal transduction in different biological contexts such as for example development. BioEssays 30:1110–1125, 2008. © 2008 Wiley Periodicals, Inc. (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 paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

This paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

Personalised medicine has been discussed as a medical paradigm shift that will improve health while reducing inefficiency and waste. At the same time, it raises new practical, regulatory, and ethical challenges. In this paper, we examine PM strategies epistemologically in order to develop capacities to address these challenges, focusing on a recently proposed strategy for developing patient-specific models from induced pluripotent stem cells so as to make individualised treatment predictions. We compare this strategy to two main PM strategies—stratified medicine and (...) computational models. Drawing on epistemological work in the philosophy of medicine, we explain why these two methods, while powerful, are neither truly personalised nor, epistemologically speaking, novel strategies. Both are forms of correlational black box. We then argue that the iPSC models would count as a new kind of black box. They would not rely entirely on mechanistic knowledge, and they would utilise correlational evidence in a different way from other strategies—a way that would enable personalised predictions. In arguing that the iPSC models would present a novel method of gaining evidence for clinical practice, we provide an epistemic analysis that can help to inform the practical, regulatory, and ethical challenges of developing an iPSC system. (shrink)

We address the question of whether and to what extent explanatory and modelling strategies in systems biology are mechanistic. After showing how dynamic mathematical models are actually required for mechanistic explanations of complex systems, we caution readers against expecting all systems biology to be about mechanistic explanations. Instead, the aim may be to generate topological explanations that are not standardly mechanistic, or to arrive at design principles that explain system organization and behaviour in general, but not specific mechanisms. These abstraction (...) strategies serve various aims, including prediction and control, that are central to understanding the epistemic diversity of systems biology. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and the (...) transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

With the emergence of systems biology the notion of organizing principles is being highlighted as a key research aim. Researchers attempt to ‘reverse engineer’ the functional organization of biological systems using methodologies from mathematics, engineering and computer science while taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-20th century. The aim of this paper is (...) to draw on this historical background in order to increase the understanding of the motivation behind the systems theoretic approach and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational and system-level properties, ii) the inherent critique of reductionism and fragmentation of knowledge resulting from overspecialization, and iii) the insight that the ideal of formulating abstract organizing principles is complementary to, rather than conflicting with, the aim of formulating detailed explanations of biological mechanisms. We argue that looking back not only helps us understand the current practice but also points to possible future directions for systems biology. (shrink)

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)

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 dependencyrelations 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 constraintbased 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)

Emphatic claims of a “microbiome revolution” aside, the study of the gut microbiota and its role in organismal development and evolution is a central feature of so-called postgenomics; namely, a conceptual and/or practical turn in contemporary life sciences, which departs from genetic determinism and reductionism to explore holism, emergentism and complexity in biological knowledge-production. This paper analyses the making of postgenomic knowledge about developmental symbiosis in Drosophila melanogaster by a specific group of microbiome scientists. Drawing from both practical philosophy of (...) science and Science and Technology Studies, the paper documents epistemological questions of artefactuality and representativeness of model organisms as they emerge in the day-to-day labour producing and being produced by the “microbiome revolution." Specifically, the paper builds on all the written and editorial exchanges involved in the troubled publication of a research paper studying the symbiotic role of the microbiota in the flies’ development. These written materials permit us to delimit the network of justifications, evidence, standards of knowledge-production, trust in the tools and research designs that make up the conditions of possibility of a postgenomic fact. More than reframing the organism as a radically novel multiplicity of reactive genomes, we conclude, doing postgenomic research on the microbiota and symbiosis means producing a story that deviates from the scripts embedded into the sociotechnical experimental systems of post-Human Genome Project life sciences. (shrink)

In this essay I propose that what design principles in systems biology and systems neuroscience do is to present abstract characterizations of mechanisms, and thereby facilitate mechanistic explanation. To show this, one design principle in systems neuroscience, i.e., the multilayer perceptron, is examined. However, Braillard contends that design principles provide a sort of non-mechanistic explanation due to two related reasons: they are very general and describe non-causal dependence relationships. In response to this, I argue that, on the one hand, all (...) mechanisms are more or less general, and on the other, many design principles are causal systems. (shrink)

Stem cell biology and systems biology are two prominent new approaches to studying cell development. In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues. Systems biology, in contrast, emphasizes mathematical modeling of cellular systems. For scientists and philosophers interested in development, an important question arises: how should the two approaches relate? This essay proposes an answer, using the model of Waddington’s landscape to triangulate between stem cell and systems approaches. This simple abstract model represents (...) development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model can play an updated unificatory role. I examine this model’s structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments. On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development. (shrink)

This paper offers a contribution to debates around integrative aspects of systems biology and engages with issues related to the circumstances under which physicists look at biological problems. We use oral history as one of the methodological tools to gather the empirical material, conducting interviews with physicists working in systems biology. The interviews were conducted at several institutions in Brazil, Germany, Israel and the U.S. Biological research has been increasingly dependent on computational methods, high-throughput technologies, and multidisciplinary skills. Quantitative scientists (...) are joining biological departments and collaborations between physicists and biologists are particularly vigorous. This state of affairs raises a number of questions, such as: What are the circumstances under which physicists approach biological problems in systems biology? What kind of interdisciplinary challenges must be tackled? The paper suggests that, concerning physicists’ move to work on biological systems, there are common reasons to move, the transition must be understood in terms of degrees, physicists have a rationale for simplifying systems, and distinct conceptions of model and modeling strategies are recurrent. We identified problems regarding linguistic clarity and integration of epistemological aims. We conclude that cultural unconformities within the systems biology community have important consequences to the flow of scientific knowledge. (shrink)

A critical review of Frans de Waal's book on evolution of morality (Frans de Waal, Primates and Philosophers: How Morality Evolved, Princeton, NJ: Princeton University Press, 2006).

Metagenomics is an emerging microbial systems science that is based on the large-scale analysis of the DNA of microbial communities in their natural environments. Studies of metagenomes are revealing the vast scope of biodiversity in a wide range of environments, as well as new functional capacities of individual cells and communities, and the complex evolutionary relationships between them. Our examination of this science focuses on the ontological implications of these studies of metagenomes and metaorganisms, and what they mean for common (...) sense and philosophical understandings of multicellularity, individuality and organism. We show how metagenomics requires us to think in different ways about what human beings are and what their relation to the microbial world is. Metagenomics could also transform the way in which evolutionary processes are understood, with the most basic relationship between cells from both similar and different organisms being far more cooperative and less antagonistic than is widely assumed. In addition to raising fundamental questions about biological ontology, metagenomics generates possibilities for powerful technologies addressed to issues of climate, health and conservation. We conclude with reflections about process-oriented versus entity-oriented analysis in light of current trends towards systems approaches. (shrink)

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