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Towards philosophical foundations of Systems Biology: introduction

In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier (2007)

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  1. Multiple Realization in Systems Biology.Wei Fang - forthcoming - Philosophy of Science.
    Polger and Shapiro claim that unlike human-made artifacts cases of multiple realization in naturally occurring systems are uncommon. Drawing on cases from systems biology, I argue that multiple realization in naturally occurring systems is not as uncommon as Polger and Shapiro initially thought. The relevant cases, which I draw from systems biology, involve generalizable design principles called network motifs which recur in different organisms and species and perform specific functions. I show that network motifs with entirely different underlying causal structures (...)
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  • Scientific Knowledge in the Age of Computation: Explicated, Computable and Manageable?Sophia Efstathiou, Rune Nydal, Astrid Laegreid & Martin Kuiper - 2019 - Theoria. An International Journal for Theory, History and Foundations of Science 34 (2):213.
    We have two theses about scientific knowledge in the age of computation. Our general claim is that scientific Knowledge Management practices emerge as second-order practices whose aim is to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data. Our specific thesis is that knowledge management practices are transforming biological research in at least three ways. We argue that scientific Knowledge Management a. operates with founded concepts of biological knowledge as explicated and computable, b. enables new outputs and (...)
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  • The Return of the Organism as a Fundamental Explanatory Concept in Biology.Daniel J. Nicholson - 2014 - Philosophy Compass 9 (5):347-359.
    Although it may seem like a truism to assert that biology is the science that studies organisms, during the second half of the twentieth century the organism category disappeared from biological theory. Over the past decade, however, biology has begun to witness the return of the organism as a fundamental explanatory concept. There are three major causes: (a) the realization that the Modern Synthesis does not provide a fully satisfactory understanding of evolution; (b) the growing awareness of the limits of (...)
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  • The Practical Value of Biological Information for Research.Beckett Sterner - 2014 - Philosophy of Science 81 (2):175-194,.
    Many philosophers are skeptical about the scientific value of the concept of biological information. However, several have recently proposed a more positive view of ascribing information as an exercise in scientific modeling. I argue for an alternative role: guiding empirical data collection for the sake of theorizing about the evolution of semantics. I clarify and expand on Bergstrom and Rosvall’s suggestion of taking a “diagnostic” approach that defines biological information operationally as a procedure for collecting empirical cases. The more recent (...)
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  • Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation.Ingo Brigandt - 2015 - In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer. pp. 135–173.
    Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...)
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  • The Role of Philosophy of Science in Responsible Research and Innovation : The Case of Nanomedicine.Gry Oftedal - 2014 - Life Sciences, Society and Policy 10 (1):1-12.
    Research on ethical, legal and social aspects of life sciences and new technologies has mainly been focused on impacts and consequences, while the emerging framework of Responsible Research and Innovation focuses rather on increased involvement and reflexivity in research processes to foster science and technology that better answers the needs of society. I argue that philosophy of science should be a central feature of RRI and demonstrate how the philosophy of science can contribute in this sense. I show how investigating (...)
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  • A Philosophical Perspective on Evolutionary Systems Biology.Maureen A. O’Malley, Orkun S. Soyer & Mark L. Siegal - 2015 - Biological Theory 10 (1):6-17.
    Evolutionary systems biology is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context (...)
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  • Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2018 - History and Philosophy of the Life Sciences 40 (1):17.
    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...)
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  • Mechanistic Explanation in Systems Biology: Cellular Networks.Dana Matthiessen - 2017 - British Journal for the Philosophy of Science 68 (1):1-25.
    It is argued that once biological systems reach a certain level of complexity, mechanistic explanations provide an inadequate account of many relevant phenomena. In this article, I evaluate such claims with respect to a representative programme in systems biological research: the study of regulatory networks within single-celled organisms. I argue that these networks are amenable to mechanistic philosophy without need to appeal to some alternate form of explanation. In particular, I claim that we can understand the mathematical modelling techniques of (...)
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  • Models in Systems Medicine.Jon Williamson - unknown
    Systems medicine is a promising new paradigm for discovering associations, causal relationships and mechanisms in medicine. But it faces some tough challenges that arise from the use of big data: in particular, the problem of how to integrate evidence and the problem of how to structure the development of models. I argue that objective Bayesian models offer one way of tackling the evidence integration problem. I also offer a general methodology for structuring the development of models, within which the objective (...)
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  • Multilevel Research Strategies and Biological Systems.Maureen A. O'Malley, Ingo Brigandt, Alan C. Love, John W. Crawford, Jack A. Gilbert, Rob Knight, Sandra D. Mitchell & Forest Rohwer - 2014 - Philosophy of Science 81 (5):811-828.
    Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.
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  • Systems Biology and the Integration of Mechanistic Explanation and Mathematical Explanation.Ingo Brigandt - 2013 - Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
    The paper discusses how systems biology is working toward complex accounts that integrate explanation in terms of mechanisms and explanation by mathematical models—which some philosophers have viewed as rival models of explanation. Systems biology is an integrative approach, and it strongly relies on mathematical modeling. Philosophical accounts of mechanisms capture integrative in the sense of multilevel and multifield explanations, yet accounts of mechanistic explanation have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical (...)
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  • Pluralization through epistemic competition: scientific change in times of data-intensive biology.Fridolin Gross, Nina Kranke & Robert Meunier - 2019 - History and Philosophy of the Life Sciences 41 (1):1.
    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 (...)
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  • Ins and Outs of Systems Biology Vis-À-Vis Molecular Biology: Continuation or Clear Cut?Philippe De Backer, Danny De Waele & Linda Van Speybroeck - 2010 - Acta Biotheoretica 58 (1):15-49.
    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 (...)
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  • Interdisciplinary Problem- Solving: Emerging Modes in Integrative Systems Biology.Miles MacLeod & Nancy J. Nersessian - 2016 - European Journal for Philosophy of Science 6 (3):401-418.
    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 (...)
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  • Modelling Molecular Mechanisms: A Framework of Scientific Reasoning to Construct Molecular-Level Explanations for Cellular Behaviour.Marc H. W. van Mil, Dirk Jan Boerwinkel & Arend Jan Waarlo - 2013 - Science & Education 22 (1):93-118.
  • Model-Based Inferences in Modeling of Complex Systems.Miles MacLeod - forthcoming - Topoi:1-11.
    Modelers are tackling ever more complex systems with the aid of computation. Model-based inferences can play a key role in their ability to handle complexity and produce reliable or informative models. We study here the role of model-based inference in the modern field of computational systems biology. We illustrate how these inferences operate and analyze the material and theoretical bases or conditions underlying their effectiveness. Our investigation reiterates the significance and centrality of model-based reasoning in day-to-day problem-solving practices, and the (...)
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  • Model and movement: studying cell movement in early morphogenesis, 1900 to the present.Janina Wellmann - 2018 - History and Philosophy of the Life Sciences 40 (3):59.
    Morphogenesis is one of the fundamental processes of developing life. Gastrulation, especially, marks a period of major translocations and bustling rearrangements of cells that give rise to the three germ layers. It was also one of the earliest fields in biology where cell movement and behaviour in living specimens were investigated. This article examines scientific attempts to understand gastrulation from the point of view of cells in motion. It argues that the study of morphogenesis in the twentieth century faced a (...)
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  • Heuristic Approaches to Models and Modeling in Systems Biology.Miles MacLeod - 2016 - Biology and Philosophy 31 (3):353-372.
    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 (...)
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  • Revisiting Generality in Biology: Systems Biology and the Quest for Design Principles.Sara Green - 2015 - Biology and Philosophy 30 (5):629-652.
    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 (...)
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