Calculating life? Duelling discourses in interdisciplinary systems biology

A high profile context in which physics and biology meet today is in the new field of systems biology. Systems biology is a fascinating subject for sociological investigation because the demands of interdisciplinary collaboration have brought epistemological issues and debates front and centre in discussions amongst systems biologists in conference settings, in publications, and in laboratory coffee rooms. One could argue that systems biologists are conducting their own philosophy of science. This paper explores the epistemic aspirations of the field by drawing on interviews with scientists working in systems biology, attendance at systems biology conferences and workshops, and visits to systems biology laboratories. It examines the discourses of systems biologists, looking at how they position their work in relation to previous types of biological inquiry, particularly molecular biology. For example, they raise the issue of reductionism to distinguish systems biology from molecular biology. This comparison with molecular biology leads to discussions about the goals and aspirations of systems biology, including epistemic commitments to quantification, rigor and predictability. Some systems biologists aspire to make biology more similar to physics and engineering by making living systems calculable, modelable and ultimately predictable-a research programme that is perhaps taken to its most extreme form in systems biology's sister discipline: synthetic biology. Other systems biologists, however, do not think that the standards of the physical sciences are the standards by which we should measure the achievements of systems biology, and doubt whether such standards will ever be applicable to 'dirty, unruly living systems'. This paper explores these epistemic tensions and reflects on their sociological dimensions and their consequences for future work in the life sciences.     

Holism vs. Reductionism: Do Ecosystem Ecology and Landscape Ecology Clarify the Debate?

The holism-reductionism debate, one of the classic subjects of study in the philosopy of science, is currently at the heart of epistemological concerns in ecology. Yet the division between holism and reductionism does not always stand out clearly in this field. In particular, almost all work in ecosystem ecology and landscape ecology presents itself as holistic and emergentist. Nonetheless, the operational approaches used rely on conventional reductionist methodology.From an emergentist epistemological perspective, a set of general 'transactional' principles inspired by the work of J. Dewey and J.K. Feibleman are proposed in an effort to develop a coherent ontological and methodological semantics.     

Systems biology in animal sciences

Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes and animal traits are not yet frequently used. This paper aims to explain what systems biology is and which areas of animal sciences could benefit from systems biology approaches. Systems biology aims to understand whole biological systems working as a unit, rather than investigating their individual components. Therefore, systems biology can be considered a holistic approach, as opposed to reductionism. The recently developed 'omics' technologies enable biological sciences to characterize the molecular components of life with ever increasing speed, yielding vast amounts of data. However, biological functions do not follow from the simple addition of the properties of system components, but rather arise from the dynamic interactions of these components. Systems biology combines statistics, bioinformatics and mathematical modeling to integrate and analyze large amounts of data in order to extract a better understanding of the biology from these huge data sets and to predict the behavior of biological systems. A 'system' approach and mathematical modeling in biological sciences are not new in itself, as they were used in biochemistry, physiology and genetics long before the name systems biology was coined. However, the present combination of mass biological data and of computational and modeling tools is unprecedented and truly represents a major paradigm shift in biology. Significant advances have been made using systems biology approaches, especially in the field of bacterial and eukaryotic cells and in human medicine. Similarly, progress is being made with 'system approaches' in animal sciences, providing exciting opportunities to predict and modulate animal traits.     

奥德姆的生态思想是整体论吗?

奥德姆的生态思想是妥协的整体论,有还原论的一面。把生态系统看作是功能性整体、承认生态系统各层次的涌现属性属于整体论,把生态关系简化为能量关系、把生态系统看作是物理系统的分析方法则是还原论的。这种矛盾的生态思想决定了其方法论的先天不足:生态模型的内在逻辑关系没有理顺;较少考虑生态系统的进化;生态研究方法的排它性等。但是,它并不妨碍奥德姆的生态思想在夯实生态学的本体论基础、促进理论生态学和生态工程学的形成、协调生态整体论与还原论分歧、奠定生态系统服务功能研究基础等方面发挥重要作用。要超越生态整体论与还原论,繁荣发展生态复杂性理论也许是最好的选择。     

Ins and Outs of Systems Biology vis-à-vis Molecular Biology: Continuation or Clear Cut?

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 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.     

Chance between holism and reductionism: Tensions in the conceptualisation of Life

In debates between holism and reductionism in biology, from the early twentieth century to more recent re-enactments involving genetic reductionism, developmental systems theory or systems biology, the role of chance - the presence of theories invoking chance as a strong explanatory principle - is hardly ever acknowledged. Conversely, Darwinian models of chance and selection (Dennett, 1995; Kupiec, 1996, 2009) sit awkwardly with reductionist and holistic concepts, which they alternately challenge or approve of. I suggest that the juxtaposition of chance and the holism-reductionism pair (at multiple levels, ontological and methodological, pertaining to the vision of scientific practice as well as to the foundations of a vision of Nature, implicit or explicit) allows the theorist to shed some new light on these perennial tensions in the conceptualisation of Life.     

Emergence,therefore antireductionism? A critique of emergent antireductionism

Emergent antireductionism in biological sciences states that even though all living cells and organisms are composed of molecules, molecular wholes are characterized by emergent properties that can only be understood from the perspective of cellular and organismal levels of composition. Thus, an emergence claim (molecular wholes are characterized by emergent properties) is thought to support a form of antireductionism (properties of higher-level molecular wholes can only be understood by taking into account concepts, theories and explanations dealing with higher-level entities). I argue that this argument is flawed: even if molecular wholes are characterized by emergent properties and even if many successful explanations in biology are not molecular, there is no entailment between the two claims.     

Toward computational systems biology

The development and successful application of high-throughput technologies are transforming biological research. The large quantities of data being generated by these technologies have led to the emergence of systems biology, which emphasizes large-scale, parallel characterization of biological systems and integration of fragmentary information into a coherent whole. Complementing the reductionist approach that has dominated biology for the last century, mathematical modeling is becoming a powerful tool to achieve an integrated understanding of complex biological systems and to guide experimental efforts of engineering biological systems for practical applications. Here I give an overview of current mainstream approaches in modeling biological systems, highlight specific applications of modeling in various settings, and point out future research opportunities and challenges.     

On emergence, agency, and organization

Ultimately we will only understand biological agency when we have developed a theory of the organization of biological processes, and science is still a long way from attaining that goal. It may be possible nonetheless to develop a list of necessary conditions for the emergence of minimal biological agency. The authors offer a model of molecular autonomous agents which meets the five minimal physical conditions that are necessary (and, we believe, conjointly sufficient) for applying agential language in biology: autocatalytic reproduction; work cycles; boundaries for reproducing individuals; self-propagating work and constraint construction; and choice and action that have evolved to respond to food or poison. When combined with the arguments from preadaptation and multiple realizability, the existence of these agents is sufficient to establish ontological emergence as against what one might call Weinbergian reductionism. Minimal biological agents are emphatically not conscious agents, and accepting their existence does not commit one to any robust theory of human agency. Nor is there anything mystical, dualistic, or non-empirical about the emergence of agency in the biosphere. Hence the emergence of molecular autonomous agents, and indeed ontological emergence in general, is not a negation of or limitation on careful biological study but simply one of its implications.     

Molecular systems biology at the crossroads: to know less about more,or to know more about less?

Systems biology is a rapidly evolving discipline that endeavours to understand the detailed coordinated workings of entire organisms, with the ultimate goal to detect differences between health and disease, or to understand how cells or entire organisms react to the environment. The editorial provides a critical evaluation of what molecular systems analysis can and cannot accomplish with existing methodologies, and how systems biology needs to merge with reductionism to yield a more comprehensive and mechanistically insightful model of a cell or organism.     

Rehabilitating Reductionism

SYNOPSIS: Reductionism has become the object of a great dealof criticism from a variety of quarters within evolutionarybiology in recent years. Many contemporary anti-reductionistsargue that reductionism is inappropriate in biological inquirygiven the prevalence of hierarchies, scales of complexity andlevels of organization in the organic world. They further contendthat a commitment to reductionism has led evolutionary theoriststo make a large number of methodological blunders and conceptualerrors in constructing explanations of biological evolution. The contemporary critics of reductionism have not made a persuasivecase for the ontological peculiarity of the organic world. Muchof their argument concerning hierarchy and levels appears torest on assertion rather than metaphysical necessity or ontologicalpeculiarity. Moreover, the interpretations of reductionism attackedby contemporary critics in biology are narrow and overly simplistic. The modern synthetic theory of evolution may well have explanatoryinadequacies that demand the attention of biologists workingin many fields. But attempts to motivate theoretical alternativesto this theory based solely on ontological grounds appear toplace the ontological cart before the theoretical horse. Theoriesdictate ontological commitments and, as a result, it is at thelevel of theoretical rather than ontological adequacy that theassessment of the modern synthetic theory ought to proceed.     

Building momentum for systems and synthetic biology in India

Biological systems are inherently noisy. Predicting the outcome of a perturbation is extremely challenging. Traditional reductionist approach of describing properties of parts, vis-a-vis higher level behaviour has led to enormous understanding of fundamental molecular level biology. This approach typically consists of converting genes into junk (knock-down) and garbage (knock-out) and observe how a system responds. To enable broader understanding of biological dynamics, an integrated computational and experimental strategy was formally proposed in mid 1990s leading to the re-emergence of Systems Biology. However, soon it became clear that natural systems were far more complex than expected. A new strategy to address biological complexity was proposed at MIT (Massachusetts Institute of Technology) in June 2004, when the first meeting of synthetic biology was held. Though the term ‘synthetic biology’ was proposed during 1970s (Szybalski in Control of gene expression, Plenum Press, New York, 1974), the usage of the original concept found an experimental proof in 2000 with the demonstration of a three-gene circuit called repressilator (Elowitz and Leibler in Nature, 403:335–338, 2000). This encouraged people to think of forward engineering biology from a set of well described parts.     

Do Organisms Exist?

What is the status of organisms in modern evolutionary biology?I argue that this is a question which centers on the questionof reduction, and towards a complete answer, I pursue issuesthrough three different senses of the term: ontological, methodological,and epistemological. The first sense refers to the ultimatestatus of the entities of the organic world, and in this senseI argue that organisms have no special status. The second senserefers to the question of organization, and I argue that inthe light of modern evolutionary biology organisms do have adistinctive "design-like" organization. The third sense refersto the relationship between theories, in particular to whetherthe theories of the biological sciences can be shown to be logicalconsequences of the theories of the physical sciences. I arguethat such reduction may be possible in principle but difficultin practice. However, from the perspective of the working scientist,this hardly matters. In conclusion, I argue that in some respectsorganisms are not distinctive and in other respects they are.Certainly biologists need not worry for the autonomy of theirsubject.     

传统中国医药与现代系统生物学研究理论的殊途同归

系统生物学是研究一个生物系统中所有组成成分(基因、mRNA、蛋白质等)的构成与组分之间相互关系的学科,近年来,系统生物学作为后基因组学时代研究的一个重要内容,已广泛深入到生命科学和医药学的各个领域。而作为中国传统医学而言,似乎与之相去甚远,然而当我们对这两个新老学科基础理论进行比较时,我们发现:传统中国医药与现代系统生物学研究理论的殊途同归。有鉴于此,本文论述了系统生物学和中医学的思想起源、相互联系,基于系统生物学的发展、研究思路和方法,阐述了生物学由还原论的研究方法过渡到系统论的研究方法,强调对生命现象从系统和整体的层次进行研究和把握,对传统中医学研究方法的变革起到了推动作用,最后对系统生物学在中医药学未来发展进行了评价。     

How to be an anti-reductionist about developmental biology: Response to Laubichler and Wagner

Alexander Rosenberg recently claimed (1997) that developmental biology is currently being reduced to molecular biology. cite several concrete biological examples that are intended to impugn Rosenberg's claim. I first argue that although Laubichler and Wagner's examples would refute a very strong reductionism, a more moderate reductionism would escape their attacks. Next, taking my cue from the antireductionist's perennial stress on the importance of spatial organization, I describe one form an empirical finding that refutes this moderate reductionism would take. Finally, I point out an actual example, anterior-posterior axis determination in the chick, that challenges the reductionist's belief that all developmental regularities can be explained by molecular biology. In short, I argue that Rosenberg's position can be saved from Laubichler and Wagner's criticisms and putative counter-examples, but it would not survive a different kind of counter-example.     

Can we build synthetic,multicellular systems by controlling developmental signaling in space and time?

Using biological machinery to make new, functional molecules is an exciting area in chemical biology. Complex molecules containing both 'natural' and 'unnatural' components are made by processes ranging from enzymatic catalysis to the combination of molecular biology with chemical tools. Here, we discuss applying this approach to the next level of biological complexity -- building synthetic, functional biotic systems by manipulating biological machinery responsible for development of multicellular organisms. We describe recent advances enabling this approach, including first, recent developmental biology progress unraveling the pathways and molecules involved in development and pattern formation; second, emergence of microfluidic tools for delivering stimuli to a developing organism with exceptional control in space and time; third, the development of molecular and synthetic biology toolsets for redesigning or de novo engineering of signaling networks; and fourth, biological systems that are especially amendable to this approach.     

Studying populations without molecular biology: Aster Models and a new argument against reductionism

During the past few decades, philosophers of biology have debated the issue of reductionism versus anti-reductionism, with both sides often claiming a 'pluralist' position. However, both sides also tend to focus on a single research paradigm, which analyzes living things in terms of certain macromolecular components. I offer a case study where biologists pursue other analytic pathways, in a tradition of quantitative genetics that originates with the initially purely mathematical theories of R. A. Fisher, J. B. S. Haldane, and Sewall Wright in the 1930s. Aster Models (developed by Ruth Shaw and Charles Geyer) offers a class of statistical models designed for studying the fitness of plant and animal populations, by integrating the measurements of separate, sequential, non-normally distributed fitness components in novel ways. Their work generates important theoretical and practical results that do not require elaboration by molecular biology, and thus serves as a counterexample to the claims of philosophers whose 'pluralism' still harbors reductionist assumptions.     

系统生物学对医学的影响

系统生物学是21世纪最前沿的科学之一,它是随着生命科学飞速发展而产生的一门新兴生物学分支[1],它综合数学、信息科学和生物学的各种工具来阐明和理解大量的数据所包含的生物医学意义,从而使人们能够从整体上理解生物医学系统并精确、量化地预测生物医学系统的行为。随着系统生物学的发展及其理论的突破,将在疾病诊治、新药开发、预防医学方面发挥重要的作用,有助于弥补传统医学缺陷并促进其发展。