In the natural and social sciences, it is common to use toy models—extremely simple and highly idealized representations—to understand complex phenomena. Some of the simple surrogate models used to understand opaque machine learning (ML) models, such as rule lists and sparse decision trees, bear some resemblance to scientific toy models. They allow non-experts to understand how an opaque ML model works globally via a much simpler model that highlights the most relevant features of the input space and their effect on (...) the output. The obvious difference is that the common target of a toy and a full-scale model in the sciences is some phenomenon in the world, while the target of a surrogate model is another model. This essential difference makes toy surrogate models (TSMs) a new object of study for theories of understanding, one that is not easily accommodated under current analyses. This paper provides an account of what it means to understand an opaque ML model globally with the aid of such simple models. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

A persistent criticism of radical embodied cognitive science is that it will be impossible to explain “real cognition” without invoking mental representations. This paper provides an account of explicit, real-time thinking of the kind we engage in when we imagine counter-factual situations, remember the past, and plan for the future. We first present a very general non-representational account of explicit thinking, based on pragmatist philosophy of science. We then present a more detailed instantiation of this general account drawing on nonlinear (...) dynamics and ecological psychology. (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)

The aim of this paper is to argue that logic can play an important role in the “toolbox” of molecular biology. We show how biochemical pathways, i.e., transitions from a molecular aggregate to another molecular aggregate, can be viewed as deductive processes. In particular, our logical approach to molecular biology — developed in the form of a natural deduction system — is centered on the notion of Curry-Howard isomorphism, a cornerstone in nineteenth-century proof-theory.

How are data science systems made to work? It may seem that whether a system works is a function of its technical design, but it is also accomplished through ongoing forms of discretionary work by many actors. Based on six months of ethnographic fieldwork with a corporate data science team, we describe how actors involved in a corporate project negotiated what work the system should do, how it should work, and how to assess whether it works. These negotiations laid the (...) foundation for how, why, and to what extent the system ultimately worked. We describe three main findings. First, how already-existing technologies are essential reference points to determine how and whether systems work. Second, how the situated resolution of development challenges continually reshapes the understanding of how and whether systems work. Third, how business goals, and especially their negotiated balance with data science imperatives, affect a system’s working. We conclude with takeaways for critical data studies, orienting researchers to focus on the organizational and cultural aspects of data science, the third-party platforms underlying data science systems, and ways to engage with practitioners’ imagination of how systems can and should work. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of contingency”. We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For illustrative (...) purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

Philosophers of science diverge on the question what drives the growth of scientific knowledge. Most of the twentieth century was dominated by the notion that theories propel that growth whereas experiments play secondary roles of operating within the theoretical framework or testing theoretical predictions. New experimentalism, a school of thought pioneered by Ian Hacking in the early 1980s, challenged this view by arguing that theory-free exploratory experimentation may in many cases effectively probe nature and potentially spawn higher evidence-based theories. Because (...) theories are often powerless to envisage workings of complex biological systems, theory-independent experimentation is common in the life sciences. Some such experiments are triggered by compelling observation, others are prompted by innovative techniques or instruments, whereas different investigations query big data to identify regularities and underlying organizing principles. A distinct fourth type of experiments is motivated by a major question. Here I describe two question-guided experimental discoveries in biochemistry: the cyclic adenosine monophosphate mediator of hormone action and the ubiquitin-mediated system of protein degradation. Lacking underlying theories, antecedent data bases, or new techniques, the sole guides of the two discoveries were respective substantial questions. Both research projects were similarly instigated by theory-free exploratory experimentation and continued in alternating phases of results-based interim working hypotheses, their examination by experiment, provisional hypotheses again, and so on. These two cases designate theory-free, question-guided, stepwise biochemical investigations as a distinct subtype of the new experimentalism mode of scientific enquiry. (shrink)

The ways in which other animal species can be informative about human biology are not exhausted by the traditional picture of the animal model. In this paper, I propose to distinguish two roles which laboratory organisms can have in biomedical research. In the more traditional case, organisms act as surrogates for human beings, and as such are expected to be more manageable replicas of humans. However, animal models can inform us about human biology in a much less straightforward way, by (...) being used as measuring devices—what I call their instrumental role. I first characterize this role and provide criteria for it, before illustrating it with some examples from biomedical research, especially cancer research. In such an instrumental role, phenotypes are not expected to phenocopy human phenomena, but instead have the purely instrumental value of detecting or measuring differences. I argue that the instrumental role is more prevalent than might first be suspected, and that some characteristics of contemporary biomedical research are increasingly shifting the use of laboratory organisms to the instrumental role. Finally, in light of the distinction proposed, I discuss the meaning of the expression “animal model”. (shrink)

Early in his career Thomas Hunt Morgan was interested in embryology and dedicated his research to studying organisms that could regenerate. Widely regarded as a regeneration expert, Morgan was invited to deliver a series of lectures on the topic that he developed into a book, Regeneration. In addition to presenting experimental work that he had conducted and supervised, Morgan also synthesized and critiqued a great deal of work by his peers and predecessors. This essay probes into the history of regeneration (...) studies by looking in depth at Regeneration and evaluating Morgan’s contribution. Although famous for his work with fruit fly genetics, studying Regeneration illuminates Morgan’s earlier scientific approach which emphasized the importance of studying a diversity of organisms. Surveying a broad range of regenerative phenomena allowed Morgan to institute a standard scientific terminology that continues to inform regeneration studies today. Most importantly, Morgan argued that regeneration was a fundamental aspect of the growth process and therefore should be accounted for within developmental theory. Establishing important similarities between regeneration and development allowed Morgan to make the case that regeneration could act as a model of development. The nature of the relationship between embryogenesis and regeneration remains an active area of research. (shrink)

In a broad brush, biological models are often constructed in two general types: as a concrete model; as an abstract model. A concrete model is a material model such as model organisms, while an abstract model is a mathematical or computational model consists of equations or algorithms. Though there are types of biological models that cannot be strictly categorized as either concrete or abstract, they are falling somewhere in between this spectrum. In view of the fact that biological phenomena are (...) sui generis and distinct from physical phenomena in many respects, using the concepts in standard modeling fails to account for the differences between biological sciences and physical sciences. Drawing from the resources of a credible-world account of models in economic modeling, I propose to reinterpret abstract models and concrete models in the light of the credible world account of models. (shrink)

The inclusion of the practice of “developing and using models” in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according (...) to this account, can only be understood with respect to the aims and intentions of a cognitive agent, not solely in terms of how they represent phenomena in the world. We present this contrast as a heuristic—models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms. (shrink)

Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models—acknowledging their status as living beings and as epistemological tools—necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper (...) presents an account of how disease-specific animal models are established by drawing on the example of transgenic mice models for Alzheimer’s disease. We will introduce an account of validation that involves a three-fold process including from human being to experimental organism; from experimental organism to animal model; and from animal model to human patient. This process draws upon clinical relevance as much as scientific practices and results in disease-specific, yet incomplete, animal models. The second part of this paper argues that the incompleteness of models can be described in terms of multi-level abstractions. We qualify this notion by pointing to different experimental techniques and targets of modelling, which give rise to a plurality of models for a specific disease. (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 argues that the “long 1970s” (1969–1983) is an important though often overlooked period in the development of a rich landscape in the research of metabolism, development, and evolution. The period is marked by: shrinking public funding of basic science, shifting research agendas in molecular biology, the incorporation of new phenomena and experimental tools from previous biological research at the molecular level, and the development of recombinant DNA techniques. Research was reoriented towards eukaryotic cells and development, and in particular (...) towards “giant” RNA processing and transcription. We will here focus on three different models of developmental regulation published in that period: the two models of eukaryotic genetic regulation at the transcriptional level that were developed by Georgii P. Georgiev on the one hand, and by Roy Britten and Eric Davidson on the other; and the model of genetic sufficiency and evolution of regulatory genes proposed by Emile Zuckerkandl. These three cases illustrate the range of exploratory hypotheses that characterised the challenging landscape of gene regulation in the 1970s, a period that in hindsight can be labelled as transitional, between the biology at the laboratory bench of the preceding period, and the biology of genetic engineering and intensive data-driven research that followed. (shrink)

I argue that reconciling nature with human experience requires a new ontology in which nature is refigured as being in and of itself meaningful, thus reconfiguring traditional dualisms and the . But this refiguring of nature entails a method in which nature itself can exhibit its conceptual reconfiguration—otherwise we get caught in various conceptual and methodological problems that surreptitiously reduplicate the problem we are seeking to resolve. I first introduce phenomenology as a methodology fit to this task, then show how (...) life manifests a field in which nature in and of itself exhibits meaningfulness, such that this field can serve as a starting point for this phenomenological project. Finally, I take immunogenesis as an example in which living phenomena can guide insights into the ontology in virtue of which meaning arises in nature. (shrink)

This article traces the history of the Susceptible, Infected, Recovered (SIR) model in early 20th-century epidemiology (1904–27). The aim is to test the hypothesis that the active stance taken by Ross, Hudson, McKendrick, and Kermack represents a turn in the history of modern epidemiology, shifting the classical method of statistical epidemiology from a data-based model to a theory-based model. The article shows that epidemiological modeling is based on a mathematical simplification of epidemics at the time of the microbiological complexification of (...) epidemiology. What were the implications of the mathematical theory of epidemics for the development of modern epidemiology? How can epidemic dynamics be expressed mathematically without compromising the biological representation? This is exactly what is at stake here: from the work of Ross to the standardization of the SIR model by McKendrick and Kermack, modeling has been confronted with the problem of relating its equations to the facts. (shrink)

La variedad de metodologías científicas dedicadas a obtener conocimiento, generar creencias y motivarla acción es amplia. La filosofía de la ciencia y de la educación ha valorado críticamente las virtudes de los diversos métodos científicos, en especial de los inductivos y deductivos. Sin embargo, la aparición de nuevos procedimientos vinculados a ciencias no académicas ha promovido el desarrollo de nuevas perspectivas reflexivas que analicen dichas virtudes. Desde los métodos controlados aleatorios hasta los procedimientosepidemiológicos o clínicos, la filosofía ha examinado las (...) virtudes y también los defectos de su puesta en práctica. El presente artículo asume que la modelación basada en evidencias empíricas es una práctica de alto interés en linguistica. Con el fin de sustanciar tal asunción, se comparan dos enfoques filosóficos de la modelación científicadistinguidos por sus respectivas líneas de investigación en torno a la noción de representación: el representacionaly el pragmático. Los enfoques se ilustran posteriormente con un caso de la linguística denominado análisissintáctico del lenguaje, dirigido a examinar muestras particulares recogidas como evidencias en fases iniciales de la modelación experimental. Como conclusión, se enfatiza que ambos enfoques filosóficos aportan elementosanalíticos realmente pertinentes para el tipo de razonamiento científico que pivota en torno a modelos y cuyo alcance en la enseñanza de las ciencias puede resultar de gran interés práctico. (shrink)

Depuis le début de l’expérimentation en biologie, les animaux sont utilisés pour étudier des phénomènes inabordables chez l’homme. Le développement, depuis 1985, de procédures d’inactivation chez la souris de gènes suspects d’un rôle en pathologie humaine a produit des souris dites « modèles de maladies humaines » avec l’implicite d’une identité des processus physiopathologiques entre homme et souris. Le passage du modèle pour au modèle de est discuté dans cet article ainsi que le retour nécessaire à une forme d’expérimentation sur (...) l’homme pour tenir compte des spécificités de ce dernier.Since the beginning of experimentation in biology, animals have been used to study processes that cannot be approached on human beings. The development, since 1985, of techniques aimed at precisely inactivating mice genes suspected to be involved in human diseases has produced mice « model of human diseases », under the implicit assumption of an identity of physio-pathological processes in man and mice. The passage from model for to a model of is discussed in the present paper, along with the compulsory comeback of a kind of experimentation on man, so as to take into account human specificities. (shrink)

Neutron Therapy: An Experimental System in Radiooncology. The history of the use of neutrons in radiotherapy will be revisited by focusing on the ideas, theories and experiments that led to first clinical studies. For addressing epistemological questions regarding biological effects of fast neutrons, the notion of an “experimental system” is employed and its evolution over time discussed. Taking up the analytical framework of Hans-Jörg Rheinberger, biological effects and the physical instrument “cyclotron” are conceptualized in terms of epistemic and technical objects. (...) It is shown that the epistemic object “biological effects of neutrons” could never reach the status of a technical object and – more strikingly – that the cyclotron itself returned to being an epistemic object in the context of medicine. So there is a misunderstanding of the different roles epistemic and technical objects have to play in the framework of an experimental system. This misunderstanding led to today's highly controversial discussions about the application of neutrons in radiotherapy. (shrink)

Part of the scientific enterprise is to measure the material world and to explain its dynamics by means of models. However, not only is measurability of the world limited, analyzability of models is so, too. Most often, computer simulations offer a way out of this epistemic bottleneck. They instantiate the model and may help to analyze it. In relation to the material world a simulation may be regarded as a kind of a “non-material scale model”. Like any other scale model, (...) it does not per se give any scientific explanation but is first in itself an object of scientific enquiry, a world. Since this world is numerical, it is a priori measurable. Its role in scientific explanation will be discussed. (shrink)

This article explores the development of a rat model of mother-infant relationships from its origins in the psychosomatic investigations of the mid-1960s to its elaboration into a theoretical system in neurobiology. I reconstruct the research trajectory of a group of neurobiologists in the United States, with a focus on the experimental practices they adopted while building this animal model. Providing a microhistory of this decade-long undertaking, I show that what drove the development of the model in practice was a serendipitous (...) finding about infants’ response to maternal separation. Detected inadvertently, the pup’s separation response acquired an epistemic significance of its own and reoriented the experimental system towards unanticipated paths. To explain this intriguing phenomenon, the neurobiologists kept on refining their material manipulations and stabilizing their experimental outcomes. They thus established a series of causal relationships that connected dysregulations of the infant’s physiological systems to disruptions in maternal care. As important as this interactive stabilization of technique and objects in the laboratory was how the researchers theorized the network of relationships derived from this technically constituted objectivity. Highlighting the practice-driven aspects of model-building, I demonstrate that what facilitated this theoretical process was an integrated design of complementary experiments. The outcome of each separate experiment of the research program came to bear upon the outcomes of other experiments, informing the development of future manipulations. It was this strategically driven integration process that allowed the experimenters to build expanding networks of causal relationships and consolidate them into a neurobiological theory. (shrink)

A model of a spatio-cultural sub-context (enfolded in a wider scope context) is presented in the form of a blue print of a Complex System with a two-stage decision engine at its core. The engine first attaches a meaning to analyzable datum, and then decides whether to keep or change it. It does not alter already stored meanings but is designed to search for data to be converted into additional stored meanings and improve the accuracy of correspondence of their spatial (...) and cultural range of relevance. Meaning is reduced to the choice of a strategy—a future continuum of events; a choice dependent on a unique Evolutionary Path, a past continuum of events specific enough to lead to the current temporarily stable state of a spatio-cultural category. It is a blue print for a program that can emulate decisions to initiate changes in the environment in which a collective of culture partners resides; changes consisting of movements from one location to another or in the layout of its current location. The model is proposed at a low cultural resolution and is applicable, after suitable modifications, to a majority of city/period pairs. However, any such model has to be city/period specific. It is illustrated with a design for analyzing changes in the Israeli city, in particular in Tel Aviv. (shrink)

The emerging area of network biology is seeking to provide insights into organizational principles of life. However, despite significant collaborative efforts, there is still typically a weak link between biological and computational scientists and a lack of understanding of the research issues across the disciplines. This results in the use of simple computational techniques of limited potential that are incapable of explaining these complex data. Hence, the danger is that the community might begin to view the topological properties of network (...) data as mere statistics, rather than rich sources of biological information. A further danger is that such views might result in the imposition of scientific doctrines, such as scale-free-centric (on the modeling side) and genome-centric (on the biological side) opinions onto this area. Here, we take a graph-theoretic perspective on protein-protein interaction networks and present a high-level overview of the area, commenting on possible challenges ahead. (shrink)

In 2013, Gail Davies and Helen Scalway launched Micespace.org, an interactive web-based art and research project that uses the platform of a mock mouse model repository to visualize the complex spa...

En los inicios del siglo XXI está desarrollándose una e-ciencia, una ciencia electrónica y altamente computarizada que exige un replanteamiento sobre la epistemología científica. A través del ejemplo de la Bioinformática y las Biotecnologías, el autor muestra algunas características de esta nueva e-ciencia e indica algunos de los problemas con los que deben enfrentarse los filósofos de la ciencia contemporáneos. Right at the beginning of the 21st century an e-Science is emerging, a highly computerized electronic science which demands a new (...) way of understanding scientific epistemology. Through Bioinformatics and Biotechnologies, the author analyzes some of the characteristics of this new e-Science and shows several problems which contemporary philosophers of science must face. (shrink)

This discussion paper proposes that a meaningful distinction between science and technoscience can be found at the level of the objects of research. Both notions intermingle in the attitudes, intentions, programs and projects of researchers and research institutions—that is, on the side of the subjects of research. But the difference between science and technoscience becomes more explicit when research results are presented in particular settings and when the objects of research are exhibited for the specific interest they hold. When an (...) experiment is presented as scientific evidence which confirms or disconfirms a hypothesis, this agrees with traditional conceptions of science. When organic molecules are presented for their capacity to serve individually as electric wires that carry surprisingly large currents, this would be a hallmark of technoscience. Accordingly, we propose research on the ontology of research objects. The focus on the character and significance of research objects makes this a specifically philosophical project. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different “degrees of contingency”. We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For illustrative (...) purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

A view of evolution is presented in this paper (a two paper series), intended as a methodological infrastructure for modeling spatio-cultural systems (the design outline of such a model is presented in paper II). A motivation for the re-articulation of evolution as information dynamics is the phenomenologically discovered prerequisite of embedding a meaning-attributing apparatus in any and all models of spatio-cultural systems. An evolution is construed as the dynamics of a complex system comprised of memory devices, connected in an ordered (...) fashion (not randomly) by information-exchanges. An information-exchange transpires when the recipient system adopts a strategy (a continuum of events) that eventually changes its structure; namely, after the exchange, it contains and conveys different information. These memory devices—sub-systems—are also similarly constructed complex system. Only a part of the information is retained by a system in its physical-memory storage, which eventually loses this function too, when the ability to retrieve a common enough structure is lost. The entire amount of information is a system’s structure of connections (information exchanges); it is contained (apparently stored) dynamically when a system is observed in a temporarily stable state. This temporary permanence—robustness and resilience—is attained dynamically; namely, enabled by changes taking place in its sub-systems and in each of their sub-systems. Therefore, for modeling such a system a multi-layer/multi-scale approach is preferable. It enables the addition and subtraction of an interim scale and the consideration of such a scale as a micro or a macro (thus initiating a maneuver up or down scale) according to an ad-hoc requirement of the model, which imitates an envisaged sub system (called an ‘Inner World’), to which a certain range of decisions is relegated. This dynamics is driven (in time) by dynamically originated information growth, as defined by Shannon; i.e. by the fact that each of certain state transitions have occurred sometime in the past of the system just so and not otherwise, and by the fact that they have occurred in a certain order. Therefore, each ‘history’ and memory retrieval availability of information is unique, and thus can be used to differentiate meanings. Hence, there cannot be a comprehensive solution to the meaning attribution model-design challenge. However, the observation that at the core of each envisaged complex system, moving in time according to a rounded logic, there is an information manipulating device, operating necessarily according to a Boolean logic, can be copied into the design of a model. This observation enables, therefore, the embedding of a specific, locally fitted, meaning attributing device, which is an information manipulating mechanism (it splices/attaches one segment of information to another—its meaning). However, this is just a framework; the actual solution has still to be found locally—for each subject system. Such a solution is demonstrated for the change in location or layout in the Israeli city in paper II. (shrink)