The paper discusses how systemsbiology 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. Systemsbiology 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 (...) their qualitative interactions) have failed to address how a mathematical model could contribute to such explanations. I discuss how mathematical equations can be explanatorily relevant. Several cases from systemsbiology are discussed to illustrate the interplay between mechanistic research and mathematical modeling, and I point to questions about qualitative phenomena (rather than the explanation of quantitative details), where quantitative models are still indispensable to the explanation. Systemsbiology shows that a broader philosophical conception of mechanisms is needed, which takes into account functional-dynamical aspects, interaction in complex networks with feedback loops, system-wide functional properties such as distributed functionality and robustness, and a mechanism’s ability to respond to perturbations (beyond its actual operation). I offer general conclusions for philosophical accounts of explanation. (shrink)
Complex SystemsBiology 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 (...) treating diseases such as cancers, is pointed out. The roles played by multiple metastable states in the “continuous uphill flow of Life” supported through internal bioenergetic processes that are coupled to essential inflows are also discussed in relation to dynamic realizations of (M,R)-systems. Furthermore, the roles played by the underlying, many-valued, quantum logics and symbolic computations for ultra-complex biological systems are also briefly discussed. (shrink)
Mechanistic models in molecular systemsbiology 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. Systemsbiology 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 (...) and development of mechanistic models, identifying five constraints which guide the articulation of models in molecular systemsbiology. These constraints are not independent of one another, with the result that modeling becomes an iterative process. We illustrate the use of these constraints in the modeling of the mechanism for bistability in the lac operon. (shrink)
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, systemsbiology and genomics, with two earlier related life sciences, genetics and molecular biology. These four disciplines span the twentieth century, a period in (...) which the processes of disciplinary demarcation fundamentally changed from those characteristic of the nineteenth century. We outline how the establishment of each discipline relies upon an interplay of factors that include paradigmatic achievements, technological innovation, and social formations. Our focus, however, is the baptism stories that give the new discipline a founding narrative and articulate core problems, general approaches and constitutive methods. The highly plastic process of achieving disciplinary identity is further marked by the openness of disciplinary definition, tension between technological possibilities and the ways in which scientific issues are conceived and approached, synthesis of reductive and integrative strategies, and complex social interactions. The importance – albeit highly variable – of naming stories in these four cases indicates the scope for future studies that focus on failed disciplines or competing names. Further attention to disciplinary histories could, we suggest, give us richer insight into scientific development. (shrink)
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 systemsbiology brings together different experimental and methodological approaches in an integrative way, systems (...) bioethics integrates aspects of the history and philosophy of science, social and political theory, and normative analysis with the science in question. In this paper we outline how a careful analysis of the science of stem cell research can help to refocus the discussions related to the clinical applications of stem cells. We show how inaccurate or inadequate scientific assumptions help to create a set of unrealistic expectations and badly inform ethical deliberations and policy development. Systems bioethics offers resources for moving beyond the current impasse. (shrink)
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.
Stem cell biology and systemsbiology are two prominent new approaches to studying cell development. In stem cell biology, the predominant method is experimental manipulation of concrete cells and tissues. Systemsbiology, 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 (...)systems approaches. This simple abstract model represents development as an undulating surface of hills and valleys. Originally constructed by C. H. Waddington to visually explicate an integrated theory of genetics, development and evolution, the landscape model can play an updated unificatory role. I examine this model’s structure, representational assumptions, and uses in all three contexts, and argue that explanations of cell development require both mathematical models and concrete experiments. On this view, the two approaches are interdependent, with mathematical models playing a crucial but circumscribed role in explanations of cell development. (shrink)
The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systemsbiology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systemsbiology 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 (...) class='Hi'>biology ‘revolutionizes’ molecular biology and ‘transcends’ its assumed reductionism. The strength of this claim appears to depend on how molecular and systemsbiology 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 systemsbiology 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 systemsbiology’s use of modelling and bioinformatics, and by its scale enlargement. (shrink)
Systemsbiology 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 systemsbiology and its potential social consequences. We outline some of systemsbiology's most important socioethical (...) issues by contrasting the concept of systems as dynamic processes against the common static interpretation of genomes. New issues arise around systemsbiology's capacities for in silico testing, changing cultural understandings of life, synthetic biology, and commercialization. We advocate an interdisciplinary and interactive approach that integrates social and philosophical analysis and engages closely with the science. Overall, we argue that systemsbiology socioethics could stimulate new ways of thinking about socioethical studies of life sciences. (shrink)
Summary: Based on the book, the overall impression is that systemsbiology 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.
Systemsbiology 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. Systemsbiology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. (...) The former are based on data about systems components, the latter on systems-level data. We trace back both modeling strategies (which are often used to delineate two branches of the field) to the modeling of metabolic and signaling pathways in the bottom-up case, and to biological cybernetics and systems theory in the top-down case. We then argue that three roots of systemsbiology must be discerned to account adequately for the structure of the field: pathway modeling, biological cybernetics, and “omics”. We regard systemsbiology as merging modeling strategies (supplemented by new mathematical procedures) from data-poor fields with data supply from a field that is quite deficient in explanatory modeling. After characterizing the structure of the field, we address some epistemological and ontological issues regarding concepts on which the top-down approach relies and that seem to us to require clarification. This includes the consequences of identifying modules in large networks without relying on functional considerations, the question of the “holism” of systemsbiology, and the epistemic value of the “systeome” project that aspires to become the cutting edge of the field. (shrink)
In this article, we provide a case study examining how integrative systems biologists build simulation models in the absence of a theoretical base. Lacking theoretical starting points, integrative systemsbiology researchers rely cognitively on the model-building process to disentangle and understand complex biochemical systems. They build simulations from the ground up in a nest-like fashion, by pulling together information and techniques from a variety of possible sources and experimenting with different structures in order to discover a (...) stable, robust result. Finally, we analyze the alternative role and meaning theory has in systemsbiology expressed as canonical template theories like Biochemical Systems Theory. (shrink)
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, (...) than the former. It argues that these findings are related; that computer simulations are considered to be undeserving of experimental status, by molecular biologists, precisely because of the idealizations and approximations that they involve. The complexity of biological systems is a key factor. The paper concludes by critically examining whether the new research programme of ‘systemsbiology’ offers a genuine alternative to the modelling strategies used by physicists. It argues that it does not. (shrink)
SystemsBiology 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 (...) purely internal processes that are based on mathematical principles and physical laws. At the molecular level, the basic mechanism of the Modern Synthesis is molecular copying, the process that leads in the short run to heredity and in the long run to natural selection. The basic mechanism of SystemsBiology, instead, is self-assembly, the process by which many supramolecular structures are formed by the spontaneous aggregation of their components. In addition to molecular copying and self-assembly, however, molecular biology has uncovered also a third great mechanism at the heart of life. The existence of the genetic code and of many other organic codes in Nature tells us that molecular coding is a biological reality and we need therefore a framework that accounts for it. This framework is Code biology, the study of the codes of life, a new field of research that brings to light an entirely new dimension of the living world and gives us a completely new understanding of the origin and the evolution of life. (shrink)
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 (...) is proposed to capture the ensuing circular causality. Its differences with standard mean-field self-consistent equations and slow-fast decompositions are discussed. As such, this scheme offers a way to unravel the multilevel architecture of living systems and their regulation. Two examples, genome functions and biofilms, are detailed. (shrink)
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 (...) relational approaches that could help to find recurrent patterns in the mass of data. Earlier conceptions of relational biology and cybernetics, once deemed too abstract and speculative, are now resurrected and applied by means of new computational and simulation tools. I think this receptivity should be extended to incorporate nets of semiotic relations as heuristic guides for discerning global patterns of interactions in living systems. In this article I review aspects of systemsbiology and new directions in evolutionary theory, focusing on the role of circular and downward causation in relational structures and dynamical networks. I also indicate promising avenues of integration of some ideas of biosemiotics with those emerging from these new currents in biology. Relational developments in biology bear a telling similarity to a parallel relational turn presently manifest in the philosophy of science, rooted in the philosophy of physics and mathematics and in different varieties of structural and informational realism. The recognition of the relational nature of reality within these disciplines entails a tacit repudiation of nominalistic biases in science that have hindered the reception of semitiotic conceptions in biology. In previous investigations I explored connections between two kinds of relational structures: the networks of self-referential circular loops that appear pervasively in living systems, and the triadic relational structures that Peircean semiotics places at the basis of all semiotic transactions. Current relational views in the sciences seem oblivious to the difference between dyadic and triadic relations. Incorporating this essential distinction from biosemiotics into other fields could be a first step in seizing the opportunities opened by the relational turn for a renewal of biology and of natural philosophy in general, across disciplinary boundaries. (shrink)
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 (...) this background we outline how a range of scientific developments and conceptual considerations can be regarded as enabling and perhaps necessitating contemporary systems approaches. We suggest that philosophical ideas have a valuable part to play in making sense of complex scientific and disciplinary issues. (shrink)
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 (...) expression of this tendency, but they predict that, on average, we should see that lineages tend toward greater diversity and complexity, driven by fundamentally neutral processes. Their hypothesis can be summarised as “diversity is easy, stasis is hard”. Here, I consider evidence for this “zero force evolutionary law”. It provides a fair description of evolutionary change at the genomic level, but the predictions of the proposed law are not met for broad scale patterns in the evolution of the animal kingdom. (shrink)
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 (...) and molecular biology and genetics. Various paths of extension are invoked in these formal logics in order to express the information of biological apodicticism. Symbolizing the appropriate notations for invariant relations and for biological extensions of relations is fundamental to the exact generating functions of discrete algebraic biology. Aspects of philosophical perspectives of the relation scientific number systems are contrasted. The deep distinction between physical motion and biological motion is expressed in terms the roles of Aristotelian causes. The interior motion within perplex numbers is contrasted with the exterior motion of physical systems. The need for a new mathematics for biology is suggested. (shrink)
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.
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 (...) favor of his own methodological program are best construed as “pragmatic”. Fourth, I consider limitations of Levins’ arguments given contemporary population biology. (shrink)
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 (...) fail since Levins's thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)
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 (...) and Orzack`s arguments fail since Levins` thesis concerns the pragmatic features of model building not just the formal properties of models. (shrink)
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 (...)biology to moral issues in law, democracy and pursuit of the Good. In one interesting section that I will not be able to discuss here, Alexander provides an evolutionary hypothesis to explain each of Kohlberg's stages of moral development (pp. 131ff). The book ends with a discussion of some specific moral problems. (shrink)
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 (...) firm ground than when organismswith nervous systems, such as Schaffner''s C. elegans, areconsidered. (shrink)
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 (...) the vanguard of an emerging new complex dynamical systems paradigm now sweeping across science. (shrink)
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 (...) the construction of predictive models of transcription control in macrophages that identify the points of control (the major nodes of networks) and the ways in which they interact. (shrink)
Robert Rosen’s (M,R)-systems are a class of relational models that define organisms. The realization of relational models plays a central role in his study of life, itself. Biology becomes identified with the class of material realizations of a certain kind of relational organization, exhibited in (M,R)-systems. In this paper I describe several realizations of (M,R)-systems, and in particular alternate realizations of the replication component.
The genetic code has evolved from its initial non-degenerate wobble version until reaching its present state of degeneracy. By using the stereochemical hypothesis, we revisit the problem of codon assignations to the synonymy classes of amino-acids. We obtain these classes with a simple classifier based on physico-chemical properties of nucleic bases, like hydrophobicity and molecular weight. Then we propose simple RNA (or more generally XNA, with X for D, P or R) ring structures that present, overlap included, one and only (...) one codon by synonymy class as solutions of a combinatory variational problem. We compare these solutions to sequences of present RNAs considered as relics, with a high interspecific invariance, like invariant parts of tRNAs and micro-RNAs. We conclude by emphasizing some optimal properties of the genetic code. (shrink)