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  1. added 2019-02-08
    Artificial and Natural Genetic Information Processing.Guenther Witzany - 2017 - In Mark Burgin & Wolfgang Hofkirchner (eds.), Information Studies and the Quest for Transdisciplinarity. Singapore: World Scientific. pp. 523-547.
    Conventional methods of genetic engineering and more recent genome editing techniques focus on identifying genetic target sequences for manipulation. This is a result of historical concept of the gene which was also the main assumption of the ENCODE project designed to identify all functional elements in the human genome sequence. However, the theoretical core concept changed dramatically. The old concept of genetic sequences which can be assembled and manipulated like molecular bricks has problems in explaining the natural genome-editing competences of (...)
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  2. added 2019-01-07
    Multiple Regression Is Not Multiple Regressions: The Meaning of Multiple Regression and the Non-Problem of Collinearity.Michael B. Morrissey & Graeme D. Ruxton - 2018 - Philosophy, Theory, and Practice in Biology 10 (3).
    Simple regression (regression analysis with a single explanatory variable), and multiple regression (regression models with multiple explanatory variables), typically correspond to very different biological questions. The former use regression lines to describe univariate associations. The latter describe the partial, or direct, effects of multiple variables, conditioned on one another. We suspect that the superficial similarity of simple and multiple regression leads to confusion in their interpretation. A clear understanding of these methods is essential, as they underlie a large range of (...)
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  3. added 2019-01-07
    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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  4. added 2018-10-13
    Why One Model is Never Enough: A Defense of Explanatory Holism.Hochstein Eric - 2017 - Biology and Philosophy 32 (6):1105-1125.
    Traditionally, a scientific model is thought to provide a good scientific explanation to the extent that it satisfies certain scientific goals that are thought to be constitutive of explanation. Problems arise when we realize that individual scientific models cannot simultaneously satisfy all the scientific goals typically associated with explanation. A given model’s ability to satisfy some goals must always come at the expense of satisfying others. This has resulted in philosophical disputes regarding which of these goals are in fact necessary (...)
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  5. added 2018-04-10
    The Mathematical Theory of Categories in Biology and the Concept of Natural Equivalence in Robert Rosen.Franck Varenne - 2013 - Revue d'Histoire des Sciences 66 (1):167-197.
    The aim of this paper is to describe and analyze the epistemological justification of a proposal initially made by the biomathematician Robert Rosen in 1958. In this theoretical proposal, Rosen suggests using the mathematical concept of “category” and the correlative concept of “natural equivalence” in mathematical modeling applied to living beings. Our questions are the following: According to Rosen, to what extent does the mathematical notion of category give access to more “natural” formalisms in the modeling of living beings? Is (...)
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  6. added 2018-02-17
    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 legitimately consider models while ignoring (...)
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  7. added 2018-02-17
    Field Equations, Quantum Mechanics and Geotropism.Han J. F. Geurdes - manuscript
    The biochemistry of geotropism in plants and gravisensing in e.g. cyanobacteria or paramacia is still not well understood today [1]. Perhaps there are more ways than one for organisms to sense gravity. The two best known relatively old explanations for gravity sensing are sensing through the redistribution of cellular starch statoliths and sensing through redistribution of auxin. The starch containing statoliths in a gravity field produce pressure on the endoplasmic reticulum of the cell. This enables the cell to sense direction. (...)
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  8. added 2017-11-02
    Representing Disease Courses: An Application of the Neurological Disease Ontology to Multiple Sclerosis Typology.Mark Jensen, Alexander P. Cox, Barry Smith & Alexander Diehl - 2013 - In Proceedings of the Fourth International Conference on Biomedical Ontology (ICBO), CEUR, vol. 1060.
    The Neurological Disease Ontology (ND) is being developed to provide a comprehensive framework for the representation of neurological diseases (Diehl et al., 2013). ND utilizes the model established by the Ontology for General Medical Science (OGMS) for the representation of entities in medicine and disease (Scheuermann et al., 2009). The goal of ND is to include information for each disease concerning its molecular, genetic, and environmental origins, the processes involved in its etiology and realization, as well as its clinical presentation (...)
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  9. added 2017-08-19
    The Sum of the Parts: Large-Scale Modeling in Systems Biology.Fridolin Gross & Sara Green - 2017 - Philosophy, Theory, and Practice in Biology 9 (10).
    Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems “as a whole.” Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call “modular reductionism” and “bottom-up reductionism.” Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies (...)
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  10. added 2017-08-01
    Thought Experiments in Biology.Guillaume Schlaepfer & Marcel Weber - 2018 - In Michael T. Stuart, Yiftach J. H. Fehige & James Robert Brown (eds.), The Routledge Companion to Thought Experiments. London: Routledge. pp. 243-256.
    Unlike in physics, the category of thought experiment is not very common in biology. At least there are no classic examples that are as important and as well-known as the most famous thought experiments in physics, such as Galileo’s, Maxwell’s or Einstein’s. The reasons for this are far from obvious; maybe it has to do with the fact that modern biology for the most part sees itself as a thoroughly empirical discipline that engages either in real natural history or in (...)
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  11. added 2017-03-10
    Is Defining Life Pointless? Operational Definitions at the Frontiers of Biology.Leonardo Bich & Sara Green - 2017 - Synthese:1-28.
    Despite numerous and increasing attempts to define what life is, there is no consensus on necessary and sufficient conditions for life. Accordingly, some scholars have questioned the value of definitions of life and encouraged scientists and philosophers alike to discard the project. As an alternative to this pessimistic conclusion, we argue that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices. This paper examines the possible (...)
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  12. added 2017-02-16
    Causal Graphs and Biological Mechanisms.Alexander Gebharter & Marie I. Kaiser - 2014 - In Marie I. Kaiser, Oliver Scholz, Daniel Plenge & Andreas Hüttemann (eds.), Explanation in the special sciences: The case of biology and history. Dordrecht: Springer. pp. 55-86.
    Modeling mechanisms is central to the biological sciences – for purposes of explanation, prediction, extrapolation, and manipulation. A closer look at the philosophical literature reveals that mechanisms are predominantly modeled in a purely qualitative way. That is, mechanistic models are conceived of as representing how certain entities and activities are spatially and temporally organized so that they bring about the behavior of the mechanism in question. Although this adequately characterizes how mechanisms are represented in biology textbooks, contemporary biological research practice (...)
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  13. added 2017-02-15
    On the Limits of Causal Modeling: Spatially-Structurally Complex Biological Phenomena.Marie I. Kaiser - 2016 - Philosophy of Science 83 (5):921-933.
    This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of these models is due (...)
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  14. added 2016-12-08
    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 all agree on (...)
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  15. added 2016-10-11
    From Silico to Vitro: Computational Models of Complex Biological Systems Reveal Real-World Emergent Phenomena.Orly Stettiner - 2014 - In Vincent C. Muller (ed.), Computing and Philosophy, Selected Papaers from IACAP 2014. 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 philosophical debate (...)
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  16. added 2016-08-30
    On the Incompatibility of Biological Dynamical Mechanisms and Causal Graphs.Marcel Weber - 2016 - Philosophy of Science 83 (5):959-971.
    I examine to what extent accounts of mechanisms based on formal interventionist theories of causality can adequately represent biological mechanisms with complex dynamics. Using a differential equation model for a circadian clock mechanism as an example, I first show that there exists an iterative solution that can be interpreted as a structural causal model. Thus, in principle it is possible to integrate causal difference-making information with dynamical information. However, the differential equation model itself lacks the right modularity properties for a (...)
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  17. added 2016-07-21
    Philosophy of Experimental Biology.Jacob Stegenga - 2009 - Erkenntnis 71 (3):431-436.
    Philosophers have committed sins while studying science, it is said – philosophy of science focused on physics to the detriment of biology, reconstructed idealizations of scientific episodes rather than attending to historical details, and focused on theories and concepts to the detriment of experiments. Recent generations of philosophers of science have tried to atone for these sins, and by the 1980s the exculpation was in full swing. Marcel Weber’s Philosophy of Experimental Biology is a zenith mea culpa for philosophy of (...)
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  18. added 2016-05-23
    A Framework for Philosophical Biology.Sepehr Ehsani - manuscript
    Advances in biology, at least over the past two centuries, have mostly relied on theories that were subsequently revised, expanded or eventually refuted using experimental and other means. The field of theoretical biology used to primarily provide a basis, similar to theoretical physics in the physical sciences, to rationally examine the frameworks within which biological experiments were carried out and to shed light on overlooked gaps in understanding. Today, however, theoretical biology has generally become synonymous with computational and mathematical biology. (...)
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  19. added 2016-01-12
    Defusing Ideological Defenses in Biology.Angela Potochnik - 2013 - BioScience 63 (2):118-123.
    Ideological language is widespread in theoretical biology. Evolutionary game theory has been defended as a worldview and a leap of faith, and sexual selection theory has been criticized for what it posits as basic to biological nature. Views such as these encourage the impression of ideological rifts in the field. I advocate an alternative interpretation, whereby many disagreements between different camps of biologists merely reflect methodological differences. This interpretation provides a more accurate and more optimistic account of the state of (...)
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  20. added 2015-12-21
    Categorizing the Mental.Eric Hochstein - 2016 - Philosophical Quarterly 66 (265):745-759.
    A common view in the philosophy of mind and philosophy of psychology is that there is an ideally correct way of categorizing the structures and operations of the mind, and that the goal of neuroscience and psychology is to find this correct categorizational scheme. Categories which cannot find a place within this correct framework ought to be eliminated from scientific practice. In this paper, I argue that this general idea runs counter to productive scientific practices. Such a view ignores the (...)
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  21. added 2015-06-18
    On Adjoint and Brain Functors.David Ellerman - 2016 - Axiomathes 26 (1):41-61.
    There is some consensus among orthodox category theorists that the concept of adjoint functors is the most important concept contributed to mathematics by category theory. We give a heterodox treatment of adjoints using heteromorphisms that parses an adjunction into two separate parts. Then these separate parts can be recombined in a new way to define a cognate concept, the brain functor, to abstractly model the functions of perception and action of a brain. The treatment uses relatively simple category theory and (...)
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  22. added 2015-02-07
    Practice Oriented Controversies and Borrowed Epistemic Support in Current Evolutionary Biology. The Case of Phylogeography.Alfonso Arroyo-Santos, Mark E. Olson & Francisco Vergara-Silva - 2015 - Perspectives on Science 23 (3):310-334.
    Philosophical treatments of scientific controversies usually focus on theory, excluding important practice related aspects. However, scientists in conflict often appeal to extra-theoretical and extra-empirical elements. To understand better the role that non-empirical elements play in scientific controversies, we introduce the notion of borrowed epistemic credibility, illustrating our proposal with a recent controversy in a field of evolutionary biology known as phylogeography. Our analysis shows how scientific controversies that spring from disagreements about methodological issues potentially involve deeperdebates regarding whatconstitutes good science, (...)
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  23. added 2014-03-23
    On the Dangers of Making Scientific Models Ontologically Independent: Taking Richard Levins' Warnings Seriously.Rasmus Grønfeldt Winther - 2006 - Biology and Philosophy 21 (5):703-724.
    Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these (...)
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  24. added 2014-02-22
    Reduktionismus und Rückübertragung.Patrick Grüneberg - 2012 - In Das modellierte Individuum. Biologische Modelle und ihre ethischen Implikationen. Transcript. pp. 227-244.
    »Welche [Zugangsweise] man wählt, hängt weitgehend von der Fragestellung ab und davon, was man eigentlich erreichen möchte. Jede Betrachtung, die sich nur auf den einen Zugang beschränkt, ist einseitig. Es gibt hier ein Spannungsfeld, das es auszuhalten gilt«, so Ulrich Freund in einer Diskussion über das Verhältnis reduktionistischer und holistischer Verfahrensweisen in der Medizin. Während seine Äußerung durchaus von einem gewissen Optimismus geprägt ist, dass die Gegensätze zwischen Reduktionismus und Holismus nicht überbetont werden sollten, verdeckt sie doch ein grundlegendes Problem. (...)
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  25. added 2013-12-14
    The Physics and Electronics Meaning of Vivartanam.Varanasi Ramabrahmam - manuscript
    A modern scientific awareness of the famous advaitic expression Brahma sat, jagat mithya, jivo brahmaiva na aparah is presented. The one ness of jiva and Brahman are explained from modern science point of view. The terms dristi, adhyasa, vivartanam, aham and idam are understood in modern scientific terms and a scientific analysis is given. -/- Further, the forward (purodhana) and reverse (tirodhana) transformation of maya as jiva, prapancham, jagat and viswam, undergoing vivartanam is understood and explained using concepts from physics (...)
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  26. added 2013-11-13
    The Altruism Paradox: A Consequence of Mistaken Genetic Modeling.Yussif Yakubu - 2013 - Biological Theory 8 (1):103-113.
    The theoretical heuristic of assuming distinct alleles (or genotypes) for alternative phenotypes is the foundation of the paradigm of evolutionary explanation we call the Modern Synthesis. In modeling the evolution of sociality, the heuristic has been to set altruism and selfishness as alternative phenotypes under distinct genotypes, which has been dubbed the “phenotypic gambit.” The prevalence of the altruistic genotype that is of lower evolutionary fitness relative to the alternative genotype for non-altruistic behavior in populations is the basis of the (...)
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  27. added 2012-03-08
    Object Spaces: An Organizing Strategy for Biological Theorizing.Beckett Sterner - 2009 - Biological Theory 4 (3):280-286.
    A classic analytic approach to biological phenomena seeks to refine definitions until classes are sufficiently homogenous to support prediction and explanation, but this approach founders on cases where a single process produces objects with similar forms but heterogeneous behaviors. I introduce object spaces as a tool to tackle this challenging diversity of biological objects in terms of causal processes with well-defined formal properties. Object spaces have three primary components: (1) a combinatorial biological process such as protein synthesis that generates objects (...)
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