Search results for 'systems biology' (try it on Scholar)

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  1. Ingo Brigandt (2013). Systems Biology and the Integration of Mechanistic Explanation and Mathematical Explanation. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.score: 182.0
    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 (as the analysis of a whole in terms of its structural parts and (...)
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  2. Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.) (2007). Systems Biology: Philosophical Foundations. Elsevier.score: 180.0
    Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecendented in its combination of biology with a ...
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  3. I. C. Baianu (2006). Robert Rosen's Work and Complex Systems Biology. Axiomathes 16 (1-2):25-34.score: 180.0
    Complex Systems Biology approaches are here considered from the viewpoint of Robert Rosen’s (M,R)-systems, Relational Biology and Quantum theory, as well as from the standpoint of computer modeling. Realizability and Entailment of (M,R)-systems are two key aspects that relate the abstract, mathematical world of organizational structure introduced by Rosen to the various physicochemical structures of complex biological systems. Their importance for understanding biological function and life itself, as well as for designing new strategies for (...)
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  4. Fred C. Boogerd, Frank J. Bruggeman & Robert C. Richardson (2013). Mechanistic Explanations and Models in Molecular Systems Biology. Foundations of Science 18 (4):725-744.score: 180.0
    Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation (...)
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  5. Alexander Powell, Maureen A. O'Malley, Staffan Mueller-Wille, Jane Calvert & John Dupré (2007). Disciplinary Baptisms: A Comparison of the Naming Stories of Genetics, Molecular Biology, Genomics and Systems Biology. History and Philosophy of the Life Sciences 29 (1):5-32.score: 180.0
    Understanding how scientific activities use naming stories to achieve disciplinary status is important not only for insight into the past, but for evaluating current claims that new disciplines are emerging. In order to gain a historical understanding of how new disciplines develop in relation to these baptismal narratives, we compare two recently formed disciplines, systems biology and genomics, with two earlier related life sciences, genetics and molecular biology. These four disciplines span the twentieth century, a period in (...)
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  6. Jason Scott Robert, Jane Maienschein & Manfred D. Laubichler (2006). Systems Bioethics and Stem Cell Biology. Journal of Bioethical Inquiry 3 (1-2):19-31.score: 162.0
    The complexities of modern science are not adequately reflected in many bioethical discussions. This is especially problematic in highly contested cases where there is significant pressure to generate clinical applications fast, as in stem cell research. In those cases a more integrated approach to bioethics, which we call systems bioethics, can provide a useful framework to address ethical and policy issues. Much as systems biology brings together different experimental and methodological approaches in an integrative way, systems (...)
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  7. Claudio Gutiérrez, Sebastián Jaramillo & Jorge Soto-Andrade (2011). Some Thoughts on A. H. Louie's “More Than Life Itself: A Reflection on Formal Systems and Biology”. [REVIEW] Axiomathes 21 (3):439-454.score: 156.0
    We review and discuss A. H. Louie’s book “More than Life Itself: A Reflexion on Formal Systems and Biology” from an interdisciplinary viewpoint, involving both biology and mathematics, taking into account new developments and related theories.
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  8. Jonathan Bard (2010). A Systems Biology View of Evolutionary Genetics. Bioessays 32 (7):559-563.score: 150.0
  9. Kurt Boonen, John W. Creemers & Liliane Schoofs (2009). Bioactive Peptides, Networks and Systems Biology. Bioessays 31 (3):300-314.score: 150.0
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  10. Marta Bertolaso, Alessandro Giuliani & Laura De Gara (2011). Systems Biology Reveals Biology of Systems. Complexity 16 (6):10-16.score: 150.0
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  11. Jeffrey C. Way & Pamela A. Silver (2007). Systems Engineering Without an Engineer: Why We Need Systems Biology. Complexity 13 (2):22-29.score: 150.0
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  12. Andrew Moore (2009). A Day of Systems and Synthetic Biology for Non‐Experts. Bioessays 31 (1):119-124.score: 132.0
  13. Melinda Fagan (2012). Waddington Redux: Models and Explanation in Stem Cell and Systems Biology. Biology and Philosophy 27 (2):179-213.score: 126.0
    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 (...)
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  14. Philippe De Backer, Danny De Waele & Linda Van Speybroeck (2010). Ins and Outs of Systems Biology Vis-à-Vis Molecular Biology: Continuation or Clear Cut? Acta Biotheoretica 58 (1).score: 120.0
    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 (...) ‘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)
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  15. Maureen O'Malley, Jane Calvert & John Dupré (2007). The Study of Socioethical Issues in Systems Biology. American Journal of Bioethics 7 (4):67-78.score: 120.0
    Systems biology is the rapidly growing and heavily funded successor science to genomics. Its mission is to integrate extensive bodies of molecular data into a detailed mathematical understanding of all life processes, with an ultimate view to their prediction and control. Despite its high profile and widespread practice, there has so far been almost no bioethical attention paid to systems biology and its potential social consequences. We outline some of systems biology's most important socioethical (...)
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  16. Ulrich Krohs & Werner Callebaut (2007). Data Without Models Merging with Models Without Data. In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. 181--213.score: 120.0
    Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. (...)
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  17. H. Goorhuis (2007). Towards a Constructivist Systems Biology? Review Of: F. C. Boogerd Et Al. (Eds.) (2006) Systems Biology. Constructivist Foundations 3 (1):57-57.score: 120.0
    Summary: Based on the book, the overall impression is that systems biology struggles with the limits of first-order cybernetics and tries to overcome it by mixing bottom up and top down methods from classical approaches such as genetics, molecular biology and enzymology. However, the contributors avoid the step from first-order to second-order cybernetics.
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  18. Kenneth F. Schaffner (2007). Theories, Models, and Equations in Systems Biology. In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. 145--162.score: 120.0
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  19. Linda Van Speybroeck, Philippe De Backer, Joris Van Poucke & Danny De Waele (2005). The Conceptual Challenge of Systems Biology. Bioessays 27 (12):1305-1307.score: 120.0
    Report of the symposium 'Towards a Philosophy of Systems Biology' held at the Vrije Universiteit of Amsterdam (VUA), the Netherlands, from 2 to 3 June 2005.
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  20. Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (2007). Afterthoughts as Foundations for Systems Biology. In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier.score: 120.0
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  21. Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (2007). 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.score: 120.0
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  22. William C. Wimsatt (2007). On Building Reliable Pictures with Unreliable Data: An Evolutionary and Developmental Coda for the New Systems Biology. In Fred C. Boogerd, Frank J. Bruggeman, Jan-Hendrik S. Hofmeyr & Hans V. Westerhoff (eds.), Systems Biology: Philosophical Foundations. Elsevier. 103--20.score: 120.0
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  23. Darrell P. Rowbottom (2011). Approximations, Idealizations and 'Experiments' at the Physics-Biology Interface. Studies in History and Philosophy of Biological and Biomedical Sciences 42 (2):145-154.score: 110.0
    This paper, which is based on recent empirical research at the University of Leeds, the University of Edinburgh, and the University of Bristol, presents two difficulties which arise when condensed matter physicists interact with molecular biologists: (1) the former use models which appear to be too coarse-grained, approximate and/or idealized to serve a useful scientific purpose to the latter; and (2) the latter have a rather narrower view of what counts as an experiment, particularly when it comes to computer simulations, (...)
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  24. Marcello Barbieri (2012). Code Biology – A New Science of Life. Biosemiotics 5 (3):411-437.score: 108.0
    Systems Biology and the Modern Synthesis are recent versions of two classical biological paradigms that are known as structuralism and functionalism, or internalism and externalism. According to functionalism (or externalism), living matter is a fundamentally passive entity that owes its organization to external forces (functions that shape organs) or to an external organizing agent (natural selection). Structuralism (or internalism), is the view that living matter is an intrinsically active entity that is capable of organizing itself from within, with (...)
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  25. Eliseo Fernández (2010). Taking the Relational Turn: Biosemiotics and Some New Trends in Biology. [REVIEW] Biosemiotics 3 (2):147-156.score: 108.0
    A cluster of similar trends emerging in separate fields of science and philosophy points to new opportunities to apply biosemiotic ideas as tools for conceptual integration in theoretical biology. I characterize these developments as the outcome of a “relational turn” in these disciplines. They signal a shift of attention away from objects and things and towards relational structures and processes. Increasingly sophisticated research technologies of molecular biology have generated an enormous quantity of experimental data, sparking a need for (...)
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  26. Annick Lesne (forthcoming). Multiscale Analysis of Biological Systems. Acta Biotheoretica.score: 108.0
    It is argued that multiscale approaches are necessary for an explanatory modeling of biological systems. A first step, besides common to the multiscale modeling of physical and living systems, is a bottom-up integration based on the notions of effective parameters and minimal models. Top-down effects can be accounted for in terms of effective constraints and inputs. Biological systems are essentially characterized by an entanglement of bottom-up and top-down influences following from their evolutionary history. A self-consistent multiscale scheme (...)
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  27. Alexander Powell & John Dupré (2009). From Molecules to Systems: The Importance of Looking Both Ways. Studies in History and Philosophy of Biological and Biomedical Sciences 40 (1):54-64.score: 104.0
    Although molecular biology has meant different things at different times, the term is often associated with a tendency to view cellular causation as conforming to simple linear schemas in which macro-scale effects are specified by micro-scale structures. The early achievements of molecular biologists were important for the formation of such an outlook, one to which the discovery of recombinant DNA techniques, and a number of other findings, gave new life even after the complexity of genotype–phenotype
    relations had become apparent. Against (...)
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  28. Lindell Bromham (2011). Wandering Drunks and General Lawlessness in Biology: Does Diversity and Complexity Tend to Increase in Evolutionary Systems? Biology and Philosophy 26 (6):915-933.score: 102.0
    Does biology have general laws that apply to all levels of biological organisation, across all evolutionary time? In their book “Biology’s first law: the tendency for diversity and complexity to increase in evolutionary systems” (2010), Daniel McShea and Robert Brandon propose that the most fundamental law of biology is that all levels of biological organisation have an underlying tendency to become more complex and diverse over time. A range of processes, most notably selection, can prevent the (...)
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  29. Jerry L. R. Chandler (2009). Algebraic Biology: Creating Invariant Binding Relations for Biochemical and Biological Categories. [REVIEW] Axiomathes 19 (3):297-320.score: 102.0
    The desire to understand the mathematics of living systems is increasing. The widely held presupposition that the mathematics developed for modeling of physical systems as continuous functions can be extended to the discrete chemical reactions of genetic systems is viewed with skepticism. The skepticism is grounded in the issue of scientific invariance and the role of the International System of Units in representing the realities of the apodictic sciences. Various formal logics contribute to the theories of biochemistry (...)
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  30. Paul E. Griffiths & Russell D. Gray (2005). Discussion: Three Ways to Misunderstand Developmental Systems Theory. [REVIEW] Biology and Philosophy 20 (2-3):417-425.score: 96.0
    Developmental systems theory (DST) is a general theoretical perspective on development, heredity and evolution. It is intended to facilitate the study of interactions between the many factors that influence development without reviving `dichotomous' debates over nature or nurture, gene or environment, biology or culture. Several recent papers have addressed the relationship between DST and the thriving new discipline of evolutionary developmental biology (EDB). The contributions to this literature by evolutionary developmental biologists contain three important misunderstandings of DST.
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  31. Jay Odenbaugh (2006). The Strategy of “the Strategy of Model Building in Population Biology”. Biology and Philosophy 21 (5):607-621.score: 96.0
    In this essay, I argue for four related claims. First, Richard Levins’ classic “The Strategy of Model Building in Population Biology” was a statement and defense of theoretical population biology growing out of collaborations between Robert MacArthur, Richard Lewontin, E. O. Wilson, and others. Second, I argue that the essay served as a response to the rise of systems ecology especially as pioneered by Kenneth Watt. Third, the arguments offered by Levins against systems ecology and in (...)
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  32. Jay Odenbaugh (2003). Complex Systems, Trade‐Offs, and Theoretical Population Biology: Richard Levin's “Strategy of Model Building in Population Biology” Revisited. Philosophy of Science 70 (5):1496-1507.score: 96.0
    Ecologist Richard Levins argues population biologists must trade‐off the generality, realism, and precision of their models since biological systems are complex and our limitations are severe. Steven Orzack and Elliott Sober argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins's thesis that there is a necessary trade‐off between generality, precision, and realism in mathematical models in biology is false. I argue that Orzack and Sober's arguments (...)
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  33. George Khushf (2008). Health as Intra-Systemic Integrity: Rethinking the Foundations of Systems Biology and Nanomedicine. Perspectives in Biology and Medicine 51 (3):432-449.score: 96.0
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  34. Jay Odenbaugh (2003). Complex Systems, Trade-Offs, and Theoretical Population Biology: Richard Levin's "Strategy of Model Building in Population Biology" Revisited. Philosophy of Science 70 (5):1496-1507.score: 96.0
    Ecologist Richard Levins (1966, 1968) argues population biologists must trade-off the generality, realism and precision of their models since biological systems are complex and our limitations are severe. Elliott Sober and Steven Orzack (1993) argue that there are cases where these model properties cannot be varied independently of one another. If this is correct, then Levins` thesis that there is a necessary trade-off between generality, precision, and realism in mathematical models in biology is false. I argue that Sober (...)
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  35. Athel Cornish-Bowden (2006). Putting the Systems Back Into Systems Biology. Perspectives in Biology and Medicine 49 (4):475-489.score: 96.0
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  36. John Collier, Critical Notice of Richard D. Alexander, The Biology of Moral Systems, New York: Aldine de Gruyter 1987. Pp. Xxi+301.score: 96.0
    Richard Alexander's second book on biology and morality is a continuation and amplification of the project he reported on in Darwinism and Human Affairs1. The Biology of Moral Systems is more abstract than the earlier book. It does not broach any new empirical ground, but puts Alexander's views into a broader context of philosophical and sociological discussions of morality. It discusses and criticizes alternative philosophical and biological views of morality, and presents his views on the significance of (...)
     
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  37. Gregory J. Morgan (2001). Bacteriophage Biology and Kenneth Schaffner's Rendition of Developmentalism. Biology and Philosophy 16 (1):85-92.score: 96.0
    In this paper I consider Kenneth Schaffner''s(1998) rendition of ''''developmentalism'''' from the point of viewof bacteriophage biology. I argue that the fact that a viablephage can be produced from purified DNA and host cellularcomponents lends some support to the anti-developmentalist, ifthey first show that one can draw a principled distinctionbetween genetic and environmental effects. The existence ofhost-controlled phage host range restriction supports thedevelopmentalist''s insistence on the parity of DNA andenvironment. However, in the case of bacteriophage, thedevelopmentalist stands on less (...)
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  38. Cliff Hooker, On Fundamental Implications of Systems and Synthetic Biology.score: 96.0
    Systems and synthetic biology promise to revolutionize our understanding of biology, blur the boundaries between the living and the engineered in a vital new bioengineering, and transform our daily relationship to the living world. Their emergence thus deserves to be understood in a wider intellectual perspective. Close attention to their relationship to the larger scientific intellectual frameworks within which they function reveals that systems and synthetic biology raise fundamental challenges to scientific orthodoxy, but stand in (...)
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  39. Jan Rivkin (1999). Reviews: Out of Control: The New Biology of Machines, Social Systems, and the Economic World, Kevin Kelly. [REVIEW] Emergence 1 (2):179-182.score: 96.0
    (1999). Reviews: Out of Control: The New Biology of Machines, Social Systems, and the Economic World, Kevin Kelly. Emergence: Vol. 1, No. 2, pp. 179-182.
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  40. Ivo F. Sbalzarini (2013). Modeling and Simulation of Biological Systems From Image Data. Bioessays 35 (5):482-490.score: 96.0
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  41. Timothy Ravasi, Christine A. Wells & David A. Hume (2007). Systems Biology of Transcription Control in Macrophages. Bioessays 29 (12):1215-1226.score: 96.0
    The study of the mammalian immune system offers many advantages to systems biologists. The cellular components of the mammalian immune system are experimentally tractable; they can be isolated or differentiated from in vivo and ex vivo sources and have an essential role in health and disease. For these reasons, the major effectors cells of the innate immune system, macrophages, have been a particular focus in international genome and transcriptome consortia. Genomescale analysis of the transcriptome, and transcription initiation has enabled (...)
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  42. Jason Scott Robert (2007). Molecular and Systems Biology and Bioethics. In David L. Hull & Michael Ruse (eds.), The Cambridge Companion to the Philosophy of Biology. Cambridge University Press.score: 96.0
  43. Orkun S. Soyer & Maureen A. O'Malley (2013). Evolutionary Systems Biology: What It is and Why It Matters. Bioessays 35 (8):696-705.score: 94.0
  44. Frank J. Bruggeman (2007). Systems Biology: At Last an Integrative Wet and Dry Biology. Biological Theory 2 (2):183-188.score: 92.0
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  45. Sara Green (2013). When One Model is Not Enough: Combining Epistemic Tools in Systems Biology. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):170-180.score: 92.0
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  46. Miles MacLeod & Nancy J. Nersessian (2013). Coupling Simulation and Experiment: The Bimodal Strategy in Integrative Systems Biology. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):572-584.score: 92.0
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  47. Jonathan F. Davies & Maureen A. O'Malley (2007). Toward a Philosophy of Systems Biology: Systems Biology: Philosophical Foundations, Fred C. Boogerd , Frank J. Bruggeman , Jan-Hendrik S. Hofmeyr , and Hans V. Westerhoff , Eds. Amsterdam: Elsevier, 2007, (360 Pp; €99.95 Hbk; ISBN 978-0-444-52085-2). [REVIEW] Biological Theory 2 (4):420-422.score: 92.0
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  48. Sara Green, Melinda Fagan & Johannes Jaeger (forthcoming). Explanatory Integration Challenges in Evolutionary Systems Biology. Biological Theory.score: 92.0
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  49. Mihajlo Mesarovic & Sree N. Sreenath (2006). Beyond the Flat Earth Perspective in Systems Biology. Biological Theory 1 (1):33-34.score: 92.0
  50. Beckett Sterner, The Epistemology of Causal Selection: Insights From Systems Biology.score: 90.0
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