Results for 'biological model'

975 found
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  1. Laws, Models, and Theories in Biology: A Unifying Interpretation.Pablo Lorenzano - 2020 - In Lorenzo Baravalle & Luciana Zaterka (eds.), Life and Evolution: Latin American Essays on the History and Philosophy of Biology. Springer. pp. 163-207.
    Three metascientific concepts that have been object of philosophical analysis are the concepts oflaw, model and theory. The aim ofthis article is to present the explication of these concepts, and of their relationships, made within the framework of Sneedean or Metatheoretical Structuralism (Balzer et al. 1987), and of their application to a case from the realm of biology: Population Dynamics. The analysis carried out will make it possible to support, contrary to what some philosophers of science in general and (...)
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  2. Review of Millikan, Ruth Garrett, Language: A Biological Model[REVIEW]Brian Epstein - 2006 - Notre Dame Philosophical Reviews 2006 (5).
    Ruth Mil­likan is one of the most inter­est­ing and influ­en­tial philoso­phers alive. Her work is also hard to pen­e­trate. In this review, I try to present and assess her work on the nature of lan­guage, which is col­lected in this anthol­ogy. I also crit­i­cize her analy­sis of “nat­ural con­ven­tion” as well as her dis­cus­sion of illo­cu­tion­ary acts.
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  3. Interactive Models in Synthetic Biology: Exploring Biological and Cognitive Inter-Identities.Leonardo Bich - 2020 - Frontiers in Psychology 11:510543.
    The aim of this article is to investigate the relevance and implications of synthetic models for the study of the interactive dimension of minimal life and cognition, by taking into consideration how the use of artificial systems may contribute to an understanding of the way in which interactions may affect or even contribute to shape biological identities. To do so, this article analyzes experimental work in synthetic biology on different types of interactions between artificial and natural systems, more specifically: (...)
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  4. How-Possibly Explanation in Biology: Lessons from Wilhelm His’s ‘Simple Experiments’ Models.Christopher Pearson - 2018 - Philosophy, Theory, and Practice in Biology 10 (4).
    A common view of how-possibly explanations in biology treats them as explanatorily incomplete. In addition to this interpretation of how-possibly explanation, I argue that there is another interpretation, one which features what I term “explanatory strategies.” This strategy-centered interpretation of how-possibly explanation centers on there being a different explanatory context within which how-possibly explanations are offered. I contend that, in conditions where this strategy context is recognized, how-possibly explanations can be understood as complete explanations. I defend this alternative interpretation by (...)
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  5. The Biosemiotic Approach in Biology : Theoretical Bases and Applied Models.Joao Queiroz, Claus Emmeche, Kalevi Kull & Charbel El-Hani - 2011 - In George Terzis & Robert Arp (eds.), Information and Living Systems: Philosophical and Scientific Perspectives. Bradford. pp. 91-130.
    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 (...)
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  6. Underdetermination and Models in Biology.Petr Jedlička - 2017 - Teorie Vědy / Theory of Science 39 (2):167-186.
    Since the early 20th century underdetermination has been one of the most contentious problems in the philosophy of science. In this article I relate the underdetermination problem to models in biology and defend two main lines of argument: First, the use of models in this discipline lends strong support to the underdetermination thesis. Second, models and theories in biology are not determined strictly by the logic of representation of the studied phenomena, but also by other constraints such as research traditions, (...)
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  7. Model Organisms are Not (Theoretical) Models.Arnon Levy & Adrian Currie - 2015 - British Journal for the Philosophy of Science 66 (2):327-348.
    Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown (...)
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  8. (2 other versions)From Silico to Vitro: Computational Models of Complex Biological Systems Reveal Real-World Emergent Phenomena.Orly Stettiner - 2016 - In Vincent C. Müller (ed.), Computing and philosophy: Selected papers from IACAP 2014. Cham: Springer. pp. 133-147.
    Computer simulations constitute a significant scientific tool for promoting scientific understanding of natural phenomena and dynamic processes. Substantial leaps in computational force and software engineering methodologies now allow the design and development of large-scale biological models, which – when combined with advanced graphics tools – may produce realistic biological scenarios, that reveal new scientific explanations and knowledge about real life phenomena. A state-of-the-art simulation system termed Reactive Animation (RA) will serve as a study case to examine the contemporary (...)
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  9.  30
    Stepping Beyond the Newtonian Paradigm in Biology. Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science.Plamen L. Simeonov, Edwin Brezina, Ron Cottam, Andreé C. Ehresmann, Arran Gare, Ted Goranson, Jaime Gomez-­‐Ramirez, Brian D. Josephson, Bruno Marchal, Koichiro Matsuno, Robert S. Root-­Bernstein, Otto E. Rössler, Stanley N. Salthe, Marcin Schroeder, Bill Seaman & Pridi Siregar - 2012 - In Plamen L. Simeonov, Leslie S. Smith & Andrée C. Ehresmann (eds.), Integral Biomathics: Tracing the Road to Reality. Springer. pp. 328-427.
    The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...)
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  10. Non-linear Analysis of Models for Biological Pattern Formation: Application to Ocular Dominance Stripes.Michael Lyons & Lionel G. Harrison - 1992 - In Frank Eeckman (ed.), Neural Systems: Analysis and Modeling. Springer. pp. 39-46.
    We present a technique for the analysis of pattern formation by a class of models for the formation of ocular dominance stripes in the striate cortex of some mammals. The method, which employs the adiabatic approximation to derive a set of ordinary differential equations for patterning modes, has been successfully applied to reaction-diffusion models for striped patterns [1]. Models of ocular dominance stripes have been studied [2,3] by computation, or by linearization of the model equations. These techniques do not (...)
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  11. The challenges of purely mechanistic models in biology and the minimum need for a 'mechanism-plus-X' framework.Sepehr Ehsani - 2018 - Dissertation, University College London
    Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models such as (...)
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  12. From Biological Synapses to "Intelligent" Robots.Birgitta Dresp-Langley - 2022 - Electronics 11:1-28.
    This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought (...)
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  13. Synthetic Biology and Biofuels.Catherine Kendig - 2012 - In Paul B. Thompson & David M. Kaplan (eds.), Encyclopedia of Food and Agricultural Ethics. New York: Springer Verlag.
    Synthetic biology is a field of research that concentrates on the design, construction, and modification of new biomolecular parts and metabolic pathways using engineering techniques and computational models. By employing knowledge of operational pathways from engineering and mathematics such as circuits, oscillators, and digital logic gates, it uses these to understand, model, rewire, and reprogram biological networks and modules. Standard biological parts with known functions are catalogued in a number of registries (e.g. Massachusetts Institute of Technology Registry (...)
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  14. The Structure of Idealization in Biological Theories: The Case of the Wright-Fisher Model.Donato Rodriguez Xavier & Arroyo-Santos Alfonso - 2012 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 43 (1):11-27.
    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 (...)
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  15. Diagrams as locality aids for explanation and model construction in cell biology.Nicholaos Jones & Olaf Wolkenhauer - 2012 - Biology and Philosophy 27 (5):705-721.
    Using as case studies two early diagrams that represent mechanisms of the cell division cycle, we aim to extend prior philosophical analyses of the roles of diagrams in scientific reasoning, and specifically their role in biological reasoning. The diagrams we discuss are, in practice, integral and indispensible elements of reasoning from experimental data about the cell division cycle to mathematical models of the cycle’s molecular mechanisms. In accordance with prior analyses, the diagrams provide functional explanations of the cell cycle (...)
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  16. (8 other versions)Stepping Beyond the Newtonian Paradigm in Biology. Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science.Plamen L. Simeonov, Edwin Brezina, Ron Cottam, Andreé C. Ehresmann, Arran Gare, Ted Goranson, Jaime Gomez-­‐Ramirez, Brian D. Josephson, Bruno Marchal, Koichiro Matsuno, Robert S. Root-­Bernstein, Otto E. Rössler, Stanley N. Salthe, Marcin Schroeder, Bill Seaman & Pridi Siregar - 2012 - In Plamen L. Simeonov, Leslie S. Smith & Andrée C. Ehresmann (eds.), Integral Biomathics: Tracing the Road to Reality. Springer. pp. 328-427.
    The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...)
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  17. Standard Aberration: Cancer Biology and the Modeling Account of Normal Function.Seth Goldwasser - 2023 - Biology and Philosophy 38 (1):(4) 1-33.
    Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account of (...)
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  18. Biological Autonomy.Attila Grandpierre & Menas Kafatos - 2012 - Philosophy Study 2 (9):631-649.
    We argue that genuine biological autonomy, or described at human level as free will, requires taking into account quantum vacuum processes in the context of biological teleology. One faces at least three basic problems of genuine biological autonomy: (1) if biological autonomy is not physical, where does it come from? (2) Is there a room for biological causes? And (3) how to obtain a workable model of biological teleology? It is shown here that (...)
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  19. Using blinking fractals for mathematical modelling of processes of growth in biological systems.Yaroslav Sergeyev - 2011 - Informatica 22 (4):559–576.
    Many biological processes and objects can be described by fractals. The paper uses a new type of objects – blinking fractals – that are not covered by traditional theories considering dynamics of self-similarity processes. It is shown that both traditional and blinking fractals can be successfully studied by a recent approach allowing one to work numerically with infinite and infinitesimal numbers. It is shown that blinking fractals can be applied for modeling complex processes of growth of biological systems (...)
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  20. Aristotle's Syllogistic Model of Knowledge and the Biological Sciences: Demonstrating Natural Processes.Mariska Leunissen - 2010 - Apeiron 43 (2-3):31-60.
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  21. Modeling the Biologically Possible: Evolvability as a Modal Concept.Marcel Weber - 2025 - In Tarja Knuuttila, Till Grüne-Yanoff, Rami Koskinen & Ylwa Wirling (eds.), Modeling the Possible. Perspectives from Philosophy of Science. London: Routledge.
    Biological modalities, i.e., biologically possible, impossible, or necessary states of affairs have not received much attention from philosophers. Yet, it is widely agreed that there are biological constraints on physically possible states of affairs, such that not everything that is physically possible is also biologically possible, even if everything that is biologically possible is also physically possible. Furthermore, biologists use concepts that appear to be modal in nature, such as the concept of evolvability in evolutionary developmental biology, or (...)
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  22. The phylogeography debate and the epistemology of model-based evolutionary biology.Alfonso Arroyo-Santos, Mark E. Olson & Francisco Vergara-Silva - 2014 - Biology and Philosophy 29 (6):833-850.
    Phylogeography, a relatively new subdicipline of evolutionary biology that attempts to unify the fields of phylogenetics and population biology in an explicit geographical context, has hosted in recent years a highly polarized debate related to the purported benefits and limitations that qualitative versus quantitative methods might contribute or impose on inferential processes in evolutionary biology. Here we present a friendly, non-technical introduction to the conflicting methods underlying the controversy, and exemplify it with a balanced selection of quotes from the primary (...)
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  23. Understanding Biology in the Age of Artificial Intelligence.Adham El Shazly, Elsa Lawerence, Srijit Seal, Chaitanya Joshi, Matthew Greening, Pietro Lio, Shantung Singh, Andreas Bender & Pietro Sormanni - manuscript
    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 (...)
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  24. Is it Really so Easy to Model Biological Evolution in Terms of Design-free Cumulative Selection?Peter Punin - manuscript
    Abstract: Without directly taking sides in the design/anti-design debate, this paper defends the following position: the assertion that biological evolution “is” design-free presupposes the possibility to model biological evolution in a design-free way. Certainly, there are design-free models of evolution based on cumulative selection. But “to model” is a verb denoting “modeling” as the process leading to a model. So any modeling – trivially – needs “previous human design.” Nevertheless, contrary to other scientific activities which (...)
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  25. (1 other version)Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis.Martin Vezer - 2016 - Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis MA Vezér Studies in History and Philosophy of Science 56:95-102.
    To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the (...)
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  26. From Models to Simulations.Franck Varenne - 2018 - London, UK: Routledge.
    This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. -/- Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows how (...)
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  27. What are biological sexes?Paul E. Griffiths - manuscript
    Biological sexes (male, female, hermaphrodite) are defined by different gametic strategies for reproduction. Sexes are regions of phenotypic space which implement those gametic reproductive strategies. Individual organisms pass in and out of these regions – sexes - one or more times during their lives. Importantly, sexes are life-history stages rather than applying to organisms over their entire lifespan. This fact has been obscured by concentrating on humans, and ignoring species which regularly change sex, as well as those with non-genetic (...)
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  28. A Biologically Informed Hylomorphism.Christopher J. Austin - 2017 - In William M. R. Simpson, Robert Charles Koons & Nicholas Teh (eds.), Neo-Aristotelian Perspectives on Contemporary Science. New York: Routledge. pp. 185-210.
    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 (...)
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  29.  80
    Beyond Biological and Social Normativity: Varieties of Norm Deviation and the Justification for Intervention.Andrew Evans - forthcoming - Synthese.
    The most common theoretical approaches to defining mental disorder are naturalism, normativism, and hybridism. Naturalism and normativism are often portrayed as diametrically opposed, with naturalism grounded in objective science and normativism grounded in social convention and values. Hybridism is seen as a way of combining the two. However, all three approaches share a common feature in that they conceive of mental disorders as deviations from norms. Naturalism concerns biological norms; normativism concerns social norms; and hybridism, both biological and (...)
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  30. Mathematical biology and the existence of biological laws.Mauro Dorato - 2012 - In D. Dieks, S. Hartmann, T. Uebel & M. Weber (eds.), Probabilities, Laws and Structure. Springer.
    An influential position in the philosophy of biology claims that there are no biological laws, since any apparently biological generalization is either too accidental, fact-like or contingent to be named a law, or is simply reducible to physical laws that regulate electrical and chemical interactions taking place between merely physical systems. In the following I will stress a neglected aspect of the debate that emerges directly from the growing importance of mathematical models of biological phenomena. My main (...)
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  31. Models of Emotion.Sfetcu Nicolae - manuscript
    There are alternative models, which are based on the evaluation of certain properties, based on physiology or evolutionary psychology. Classical philosophers have addressed emotions as responses to certain types of events that are related to a subject, causing bodily and behavioral changes. In the last century emotions were neglected, being considered a disturbing factor. Lately, emotions have returned to the attention of philosophers and psychologists, corroborating them with other disciplines such as psychology, neurology, evolutionary biology and even economics. DOI: 10.13140/RG.2.2.28869.06881 (...)
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  32. Mathematical biology and the existence of biological laws.Mauro Dorato - 2012 - In D. Dieks, S. Hartmann, T. Uebel & M. Weber (eds.), Probabilities, Laws and Structure. Springer.
    An influential position in the philosophy of biology claims that there are no biological laws, since any apparently biological generalization is either too accidental, fact-like or contingent to be named a law, or is simply reducible to physical laws that regulate electrical and chemical interactions taking place between merely physical systems. In the following I will stress a neglected aspect of the debate that emerges directly from the growing importance of mathematical models of biological phenomena. My main (...)
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  33. Modelling as Indirect Representation? The Lotka–Volterra Model Revisited.Tarja Knuuttila & Andrea Loettgers - 2017 - British Journal for the Philosophy of Science 68 (4):1007-1036.
    ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely due (...)
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  34.  77
    An information processing model of psychopathy and anti-social personality disorders integrating neural and psychological accounts towards the assay of social implications of psychopathic agents.Jeffrey White - 2012 - In Angelo Fruili (ed.), Psychology of Morality. Hauppage: Nova. pp. 1-33.
    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 (...)
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  35. Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.
    The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use (...)
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  36. Multiple-Models Juxtaposition and Trade-Offs among Modeling Desiderata.Yoshinari Yoshida - 2021 - Philosophy of Science 88 (1):103-123.
    This article offers a characterization of what I call multiple-models juxtaposition, a strategy for managing trade-offs among modeling desiderata. MMJ displays models of distinct phenomena to...
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  37. Mechanist idealisation in systems biology.Dingmar van Eck & Cory Wright - 2020 - Synthese 199 (1-2):1555-1575.
    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 (...)
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  38. Models and Inferences in Science.Emiliano Ippoliti, Fabio Sterpetti & Thomas Nickles (eds.) - 1st ed. 2016 - Cham: Imprint: Springer.
    The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; (...)
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  39. The medical model, with a human face.Justis Koon - 2022 - Philosophical Studies 179 (12):3747-3770.
    In this paper, I defend a version of the medical model of disability, which defines disability as an enduring biological dysfunction that causes its bearer a significant degree of impairment. We should accept the medical model, I argue, because it succeeds in capturing our judgments about what conditions do and do not qualify as disabilities, because it offers a compelling explanation for what makes a condition count as a disability, and because it justifies why the federal government (...)
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  40. Model Organisms for Studying Decision-Making: A Phylogenetically Expanded Perspective.Linus Ta-Lun Huang, Leonardo Bich & William Bechtel - 2021 - Philosophy of Science 88 (5):1055-1066.
    This article explores the use of model organisms in studying the cognitive phenomenon of decision-making. Drawing on the framework of biological control to develop a skeletal conception of decision-making, we show that two core features of decision-making mechanisms can be identified by studying model organisms, such as E. coli, jellyfish, C. elegans, lamprey, and so on. First, decision mechanisms are distributed and heterarchically structured. Second, they depend heavily on chemical information processing, such as that involving neuromodulators. We (...)
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  41. Biological Explanation.Angela Potochnik - 2013 - In Kostas Kampourakis (ed.), The Philosophy of Biology: a Companion for Educators. Dordrecht: Springer. pp. 49-65.
    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 (...)
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  42. Evaluating Artificial Models of Cognition.Marcin Miłkowski - 2015 - Studies in Logic, Grammar and Rhetoric 40 (1):43-62.
    Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation (...)
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  43. Alife models as epistemic artefacts.Xabier Barandiaran & Alvaro Moreno - 2006 - In L. M. Rocha, L. S. Yaeger, M. A. Bedeau, D. Floreano, R. L. Goldstone & Alessandro Vespignani (eds.), Artificial Life X. Mit Press (Cambridge). pp. 513-519.
    Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories (...)
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  44. Biological Control Variously Materialized: Modeling, Experimentation and Exploration in Multiple Media.Tarja Knuuttila & Andrea Loettgers - 2021 - Perspectives on Science 29 (4):468-492.
    This paper examines two parallel discussions of scientific modeling which have invoked experimentation in addressing the role of models in scientific inquiry. One side discusses the experimental character of models, whereas the other focuses on their exploratory uses. Although both relate modeling to experimentation, they do so differently. The former has considered the similarities and differences between models and experiments, addressing, in particular, the epistemic value of materiality. By contrast, the focus on exploratory modeling has highlighted the various kinds of (...)
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  45. Complexity Biology-based Information Structures can explain Subjectivity, Objective Reduction of Wave Packets, and Non-Computability.Alex Hankey - 2014 - Cosmos and History 10 (1):237-250.
    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 (...)
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  46. Mathematical Modeling of Biological and Social Evolutionary Macrotrends.Leonid Grinin, Alexander V. Markov & Andrey V. Korotayev - 2014 - In Leonid Grinin & Andrey Korotayev (eds.), History & Mathematics: Trends and Cycles. Volgograd: "Uchitel" Publishing House. pp. 9-48.
    In the first part of this article we survey general similarities and differences between biological and social macroevolution. In the second (and main) part, we consider a concrete mathematical model capable of describing important features of both biological and social macroevolution. In mathematical models of historical macrodynamics, a hyperbolic pattern of world population growth arises from non-linear, second-order positive feedback between demographic growth and technological development. Based on diverse paleontological data and an analogy with macrosociological models, we (...)
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  47. Modeling of Biological and Social Phases of Big History.Leonid Grinin, Andrey V. Korotayev & Alexander V. Markov - 2015 - In Leonid Grinin & Andrey Korotayev (eds.), Evolution: From Big Bang to Nanorobots. Uchitel Publishing House. pp. 111-150.
    In the first part of this article we survey general similarities and differences between biological and social macroevolution. In the second (and main) part, we consider a concrete mathematical model capable of describing important features of both biological and social macroevolution. In mathematical models of historical macrodynamics, a hyperbolic pattern of world population growth arises from non-linear, second-order positive feedback between demographic growth and technological development. Based on diverse paleontological data and an analogy with macrosociological models, we (...)
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  48. Human stem-cell-derived embryo models: When bioethical normativity meets biological ontology.Adrian Villalba - 2024 - Developmental Biology 508.
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  49. Embryological models in ancient philosophy.Devin Henry - 2005 - Phronesis 50 (1):1 - 42.
    Historically embryogenesis has been among the most philosophically intriguing phenomena. In this paper I focus on one aspect of biological development that was particularly perplexing to the ancients: self-organisation. For many ancients, the fact that an organism determines the important features of its own development required a special model for understanding how this was possible. This was especially true for Aristotle, Alexander, and Simplicius, who all looked to contemporary technology to supply that model. However, they did not (...)
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  50. The Environment Ontology: Contextualising biological and biomedical entities.Pier Luigi Buttigieg, Norman Morrison, Barry Smith, Christopher J. Mungall & Suzanna E. Lewis - 2013 - Journal of Biomedical Semantics 4 (43):1-9.
    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 (...)
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