Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems (...) at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially‐detailed and computationally‐efficient approaches. In this review, we summarize the capabilities of agent‐based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. (shrink)

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 and development of mechanistic models, identifying five constraints which guide the articulation of models in molecular systems biology. 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)

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 (...) class='Hi'>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. (shrink)

I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation (...) of chemotaxis in Escherichia coli—I argue that each strategy invokes a different combination of abstraction types and that each targets its abstractions to different mechanistic details. (shrink)

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 (...) class='Hi'>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. (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, systems biology 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)

As a result of the time‐ and context‐dependency of gene expression, gene regulatory and signaling pathways undergo dynamic changes during development. Creating a model of the dynamics of molecular interaction networks offers enormous potential for understanding how a genome orchestrates the developmental processes of an organism. The dynamic nature of pathway topology calls for new modeling strategies that can capture transient molecular links at the runtime. The aim of this paper is to present a brief and informative, but (...) not all‐inclusive, viewpoint on the computational aspects of modeling and simulation of a non‐static molecular network. BioEssays 26:68–72, 2004. © 2003 Wiley Periodicals, Inc. (shrink)

Occam’s razor refers to the idea that among competing explanations the simplest should be preferred. This principle has been understood and defended in different ways. Some systems biologists argue that traditional molecular biology is misguided because it relies on an unjustified application of Occam’s razor. I analyze which version of the principle is relevant in this context and ask whether the allegation stands up to scrutiny by looking at actual research. I defend the traditional approach by arguing (...) that its use of Occam’s razor is innocuous and by showing that systems biology heavily relies on considerations of simplicity as well. (shrink)

Evolutionary systems biology (ESB) is a rapidly growing integrative approach that has the core aim of generating mechanistic and evolutionary understanding of genotype‐phenotype relationships at multiple levels. ESB's more specific objectives include extending knowledge gained from model organisms to non‐model organisms, predicting the effects of mutations, and defining the core network structures and dynamics that have evolved to cause particular intracellular and intercellular responses. By combining mathematical, molecular, and cellular approaches to evolution, ESB adds new insights and (...) methods to the modern evolutionary synthesis, and offers ways in which to enhance its explanatory and predictive capacities. This combination of prediction and explanation marks ESB out as a research manifesto that goes further than its two contributing fields. Here, we summarize ESB via an analysis of characteristic research examples and exploratory questions, while also making a case for why these integrative efforts are worth pursuing. (shrink)

The progress of the molecular biosciences has been so enormous that a discipline studying how cellular functioning emerges out of the behaviors of their molecular constituents has become reality. Systems biology studies cells as spatiotemporal networks of interacting molecules using an integrative approach of theory , experimental biology , and quantitative network-wide analytical measurement . Its aim is to understand how molecules jointly bring about life. Systems biology is rapidly discovering principles governing the (...) functioning of molecular networks and methods to model and measure them. The application of the conceptual strength of systems sciences such as physics and engineering are opening up new ways of experimentally studying the design and functioning of molecular networks. Typically, in such studies models are used to highlight principles, design experiments, or to act in a predictive mode to specifically modify cellular behavior. In this trend article, theoretical approaches being applied in systems biology will be discussed. A number of books have recently appeared that deal with theoretical aspects of systems biology. In this article they are highlighted to facilitate the communication of systems biology to a broader audience. (shrink)

In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological (...) realm entities are defined primarily by the context they are embedded within—and hence by the web of relations they are part of. (shrink)

In the context of scientists' reflections on genomics, we examine some fundamental issues in the emerging postgenomic discipline of systems biology. Systems biology is best understood as consisting of two streams. One, which we shall call ‘pragmatic systems biology’, emphasises large‐scale molecular interactions; the other, which we shall refer to as ‘systems‐theoretic biology’, emphasises system principles. Both are committed to mathematical modelling, and both lack a clear account of what biological (...) class='Hi'>systems are. We discuss the underlying issues in identifying systems and how causality operates at different levels of organisation. We suggest that resolving such basic problems is a key task for successful systems biology, and that philosophers could contribute to its realisation. We conclude with an argument for more sociologically informed collaboration between scientists and philosophers. BioEssays 27:1270–1276, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

The emergence of systems biology raises many fascinating questions: What does it mean to take a systems approach to problems in biology? To what extent is the use of mathematical and computational modelling changing the life sciences? How does the availability of big data influence research practices? What are the major challenges for biomedical research in the years to come? This book addresses such questions of relevance not only to philosophers and biologists but also to readers (...) interested in the broader implications of systems biology for science and society. The book features reflections and original work by experts from across the disciplines including systems biologists, philosophers, and interdisciplinary scholars investigating the social and educational aspects of systems biology. In response to the same set of questions, the experts develop and defend their personal perspectives on the distinctive character of systems biology and the challenges that lie ahead. Readers are invited to engage with different views on the questions addressed, and may explore numerous themes relating to the philosophy of systems biology. This edited work will appeal to scholars and all levels, from undergraduates to researchers, and to those interested in a variety of scholarly approaches such as systems biology, mathematical and computational modelling, cell and molecular biology, genomics, systems theory, and of course, philosophy of biology. (shrink)

The sense of touch informs us of the physical properties of our surroundings and is a critical aspect of communication. Before touches are perceived, mechanical signals are transmitted quickly and reliably from the skin's surface to mechano‐electrical transduction channels embedded within specialized sensory neurons. We are just beginning to understand how soft tissues participate in force transmission and how they are deformed. Here, we review empirical and theoretical studies of single molecules and molecular ensembles thought to be involved in (...) mechanotransmission and apply the concepts emerging from this work to the sense of touch. We focus on the nematode Caenorhabditis elegans as a well‐studied model for touch sensation in which mechanics can be studied on the molecular, cellular, and systems level. Finally, we conclude that force transmission is an emergent property of macromolecular cellular structures that mutually stabilize one another. (shrink)

Systems biology is sometimes presented as providing a superior approach to the problem of biological complexity. Its use of ‘unbiased’ methods and formal quantitative tools might lead to the impression that the human factor is effectively eliminated. However, a closer look reveals that this impression is misguided. Systems biologists cannot simply assemble molecular information and compute biological behavior. Instead, systems biology’s main contribution is to accelerate the discovery of mechanisms by applying models as heuristic (...) tools. These models rely on a variety of idealizing and simplifying assumptions in order to be efficient for this purpose. The strategies of systems biologists are similar to those of experimentalists in that they attempt to reduce the complexity of the discovery process. Analyzing and comparing these strategies, or ‘heuristics’, reveals the importance of the human factor in computational approaches and helps to situate systems biology within the epistemic landscape of the life sciences. (shrink)

Many lymphokine genes have now been cloned from activated T cells and their products have been expressed in mammalian cells. Use of these recombinant lymphokines has provided the opportunity to evaluate both the spectrum of their biological activities and the mechanisms of their action in promoting proliferation and differentiation of hemopoietic and lymphoid cells. Characterization of the structure of lymphokine genes will provide information about their regulated expression in T‐cell activation.

Our purpose in this essay is to introduce new concepts in a wide and recursive view of the systemic consequences of the following biological facts that I and we have presented that can be resumed as: that as living systems we human beings are molecular autopoietic system; that living systems live only as long as they find themselves in a medium that provides them with all the conditions that make the realization of their living possible, that is, (...) in the continuous conservation of their relation of adaptation to the circumstances in which they find themselves; that as a living system exists only in a relation of adaptation with the medium that operates as its ecological niche, its reproduction necessarily occurs as a process of systemic duplication or multiplication of the ecological organism-niche unity that it integrates; that the worlds of doings that we generate as languaging beings in our conversations, explanations, reflections and theories are part of our ecological niche; and that we human beings as living beings that exist in languaging, are biological–cultural beings in which our cultural and our biological manners of existences can be distinguished but cannot be separated. Of the systemic consequences of these biological facts that we consider in this essay, we wish to mention two as the principal: that the diversification of manners of living produced in biological evolution is the result of differential survival in a changing medium through the conservation of adaptation, and not through competitive survival of the best; and that we in our living as languaging human beings are the epistemological fundament of all that we do and know as such. (shrink)

The gap between Science and the Humanities becomes tangible when they both attempt to address the same problem. One such case is relationship between Life and biological molecules. Traditionally, molecular biology has attempted to explain biological processes in terms of physicochemical characteristics of individual macromolecules. The new science of systems biology largely ignores the molecular characteristics of specific molecules and endeavors to analyze biological processes through the relationship between thousands of molecules. On the face of (...) it, the difference between the molecular and the systems approach to biological research corresponds to the tension between the reductionist and the emergentist view in the philosophy of biology. However, a closer analysis reveals that experimental science and philosophy are concerned with different aspects of the problem and therefore search for different solutions. A main reason for this is the difference in their respective concepts of “question” and “answer”, which is essentially unbridgeable. (shrink)

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 of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood “bottom-up.” Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. (shrink)

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.

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 issues by contrasting the concept of systems as dynamic processes against the common static interpretation of genomes. New issues arise around systems biology'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 systems biology socioethics could stimulate new ways of thinking about socioethical studies of life sciences. (shrink)

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. (shrink)

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 issues by contrasting the concept of systems as dynamic processes against the common static interpretation of genomes. New issues arise around systems biology'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 systems biology socioethics could stimulate new ways of thinking about socioethical studies of life sciences. (shrink)

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 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)

The Neo‐Darwinian concept of natural selection is plausible when one assumes a straightforward causation of phenotype by genotype. However, such simple 1:1 mapping must now give place to the modern concepts of gene regulatory networks and gene expression noise. Both can, in the absence of genetic mutations, jointly generate a diversity of inheritable randomly occupied phenotypic states that could also serve as a substrate for natural selection. This form of epigenetic dynamics challenges Neo‐Darwinism. It needs to incorporate the non‐linear, stochastic (...) dynamics of gene networks. A first step is to consider the mathematical correspondence between gene regulatory networks and Waddington's metaphoric ‘epigenetic landscape’, which actually represents the quasi‐potential function of global network dynamics. It explains the coexistence of multiple stable phenotypes within one genotype. The landscape's topography with its attractors is shaped by evolution through mutational re‐wiring of regulatory interactions – offering a link between genetic mutation and sudden, broad evolutionary changes. (shrink)

Biology arises from the crowded molecular environment of the cell, rendering it a challenge to understand biological pathways based on the reductionist, low‐concentration in vitro conditions generally employed for mechanistic studies. Recent evidence suggests that low‐affinity interactions between cellular biopolymers abound, with still poorly defined effects on the complex interaction networks that lead to the emergent properties and plasticity of life. Mass‐action considerations are used here to underscore that the sheer number of weak interactions expected from the complex (...) mixture of cellular components significantly shapes biological pathway specificity. In particular, on‐pathway—i.e., “functional”—become those interactions thermodynamically and kinetically stable enough to survive the incessant onslaught of the many off‐pathway (“nonfunctional”) interactions. Consequently, to better understand the molecular biology of the cell a further paradigm shift is needed toward mechanistic experimental and computational approaches that probe intracellular diversity and complexity more directly. Also see the video abstract here https://youtu.be/T19X_zYaBzg. (shrink)

We provide an introduction to network theory, evidence to support a connection between molecular network structure and neuropsychiatric disease, and examples of how network approaches can expand our knowledge of the molecular bases of these diseases. Without systematic methods to derive their biological meanings and inter‐relatedness, the many molecular changes associated with neuropsychiatric disease, including genetic variants, gene expression changes, and protein differences, present an impenetrably complex set of findings. Network approaches can potentially help integrate and reconcile (...) these findings, as well as provide new insights into the molecular architecture of neuropsychiatric diseases. Network approaches to neuropsychiatric disease are still in their infancy, and we discuss what might be done to improve their prospects. (shrink)

We discuss foundational issues of quantum information biology —one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from “traditional quantum biophysics”. The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. We argue that the information (...) interpretation of quantum mechanics is the most natural interpretation of QIB. Biologically QIB is based on two principles: adaptivity; openness. These principles are mathematically represented in the framework of a novel formalism— quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems. (shrink)

I offer a defense, albeit a qualified one, of machine analogies in biology, focusing on molecular contexts. The defense is rooted in my prior work (Levy in Philosopher’s Imprint 14(6), 2014), which construes the machine machine-likeness of a system as a matter of the extent to which it exhibits an internal division of labor. A concrete aim is to shore up the notion of molecular biological machines, paying special attention to processive molecular motors, such as Kinesin. (...) But I will also try to show how the division of labor account gives us guidance more broadly, both about where and why machine analogies can be expected to prove helpful and about their limitations. (shrink)

According to objective Bayesianism, an agent’s degrees of belief should be determined by a probability function, out of all those that satisfy constraints imposed by background knowledge, that maximises entropy. A Bayesian net offers a way of efficiently representing a probability function and efficiently drawing inferences from that function. An objective Bayesian net is a Bayesian net representation of the maximum entropy probability function. In this paper we apply the machinery of objective Bayesian nets to breast cancer prognosis. Background knowledge (...) is diverse and comes from several different sources: a database of clinical data, a database of molecular data, and quantitative data from the literature. We show how an objective Bayesian net can be constructed from this background knowledge and how it can be applied to yield prognoses and aid translation of clinical knowledge to genomics research. (shrink)

Complementary DNA clones corresponding to most of the proteins of a major amplification and effector of immune host defenses, the complement system, have been isolated and characterized. Availability of these molecular probes has substantially increased our information about and understanding of the structure of the complement proteins and regulation of complement gene expression. Information about the proteins has led to the generation of potential pharmacological agents for the selective control of inflammation. Understanding of the regulatory mechanism has provided insights (...) into the mechanisms accounting for the response to several cytokines including interferon‐gamma, interleukin‐1 and tumor necrosis factor. Finally, complement molecular genetics has been stimulated so that the basis for several complement deficiency disorders has been elucidated. (shrink)

After the discovery of the structure of DNA in 1953, scientists working in molecular biology embraced reductionism—the theory that all complex systems can be understood in terms of their components. Reductionism, however, has been widely resisted by both nonmolecular biologists and scientists working outside the field of biology. Many of these antireductionists, nevertheless, embrace the notion of physicalism—the idea that all biological processes are physical in nature. How, Alexander Rosenberg asks, can these self-proclaimed physicalists also be (...) antireductionists? With clarity and wit, Darwinian Reductionism navigates this difficult and seemingly intractable dualism with convincing analysis and timely evidence. In the spirit of the few distinguished biologists who accept reductionism—E. O. Wilson, Francis Crick, Jacques Monod, James Watson, and Richard Dawkins—Rosenberg provides a philosophically sophisticated defense of reductionism and applies it to molecular developmental biology and the theory of natural selection, ultimately proving that the physicalist must also be a reductionist. (shrink)

In recent decades the expression "molecular biology" has progressively disappeared from journals, and no longer designates new chairs or departments. This begs the question: does it mean that molecular biology is dead, and has been displaced by new emerging disciplines such as systems biology and synthetic biology? Maybe its reductionist approach to living phenomena has been substituted by one that is more holistic. The situation, undoubtedly, is far less simple. To appreciate better what (...) has happened it is necessary to acknowledge the following: the intial project of molecular biologists was not a reductionist one, but an attempt to naturalize the phenomena of life by using the epistemological principles of physics as a model; and, it is necessary to distinguish the early stages of molecular biology, and the later aggregating process which gave it its present characteristics. Only one of these characteristics, the importance of the informational vision, has been seriously challenged in recent years. But it is obvious that the ambition of most early molecular biologists to discover simple rules and principles explaining all of biological facts has vanished. The pendulum has now moved toward the study of the diversity generated by a long evolutionary history. (shrink)

Plasminogen activators are enzymes with multiple roles. They play vital parts in maintaining the functional integrity of the vascular system and they are also involved in processes of tissue reorganization. In this review, the molecular properties of these enzymes that make them ideal targets for genetic and biochemical engineering to satisfy a potential therapeutic role are described.

Molecular biologists use different kinds of reasoning strategies for different tasks, such as hypothesis formation, experimental design, and anomaly resolution. More specifically, the reasoning strategies discussed in this paper may be characterized as (1) abstraction-instantiation, in which an abstract skeletal model is instantiated to produce an experimental system; (2) the systematic scan, in which alternative hypotheses are systematically generated; and (3) modular anomaly resolution, in which components of a model are stated explicitly and methodically changed to generate alternative changes (...) to resolve an anomaly. This work grew out of close observation over a period of six months of an actively functioning molecular genetics laboratory. (shrink)

Systems thinking is an increasingly recognized paradigm in education in both natural and social sciences, a particular focus being, naturally, in biology. This article argues that plant biology, and in particular, plant hormonal signaling, provides highly illustrative models for learning and teaching in a systems paradigm, because it offers examples of highly complex networks, ranging from the molecular‐ to ecosystem‐scale, and in addition lends itself to the use of real‐life biological objects.

In 1937, a group of researchers in Nazi Germany began investigating tobacco mosaic virus with the hope of using the virus as a model system for understanding gene behavior in higher organisms. They soon developed a creative and interdisciplinary work style and were able to continue their research in the postwar era, when they made significant contributions to the history of molecular biology. This group is significant for two major reasons. First, it provides an example of how researchers (...) were able to produce excellent scientific research in the midst of dictatorship and war. Coupled with the group's ongoing success in postwar Germany, the German TMV investigators provide a dramatic example of how scientific communities deal with adversity as well as rapid political and social change. Second, since the researchers focused heavily on TMV, their story allows us to analyze how an experimental system other than phage contributed to the emergence of molecular biology. (shrink)

The Medical Research Council Laboratory of Molecular Biology (formerly the Medical Research Council Unit for the Study of Molecular Structure of Biological Systems) in Cambridge (England) played a key role in the postwar history of molecular biology. The paper, focussing on the early history of the institution, aims to show that the creation of the laboratory and the making of molecular biology were part of a new scientific culture set in place after (...) World War II. In five interlinked parts it deals with the institutional creation of the MRC unit dedicated to the crystallographic analysis of biological molecules; the attraction of postwar biophysics, the heading under which the work of the unit initially fell; the people who joined the laboratory and their appropriation of new technologies, in particular the electronic computer for protein crystal structure determination; the cultural appeal of postwar crystallography, as exemplified in the use of crystal structure diagrams for a wide series of consumer goods at the Festival of Britain in 1951 and the display of molecular models at the Brussels World's Fair in 1958, a key site for the presentation of science and its role in the postwar world. (shrink)

The heme‐containing cytochromes P‐450 are a ubiquitous family of monooxygenase isozymes responsible for the oxidative metabolism of a wide variety of endogenous as well as exogenous compounds. Many of the compounds metabolized by this enzyme system are effectively detoxified and converted to derivatives more easily eliminated from the organism. However, some compounds can be activated to reactive species capable of eliciting a cascade of toxic lesions, including cancer. Since its discovery nearly 30 years ago, the cytochrome P‐450 enzyme system has (...) received a great deal of attention, particularly in the areas of their mechanisms of metabolism, range of substrate specificity, the purification and characterization of the multiple isozymes and, more recently, the regulation of expression of specific forms. This review will discuss current notions concerning the expression of at least one cytochrome P‐450 isozyme and future directions that should lead to a more complete understanding of cytochrome P‐450 gene expression in general, particularly as it impacts upon biochemical pharmacology. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. (...) This is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

Multilevel research strategies characterize contemporary molecular inquiry into biological systems. We outline conceptual, methodological, and explanatory dimensions of these multilevel strategies in microbial ecology, systems biology, protein research, and developmental biology. This review of emerging lines of inquiry in these fields suggests that multilevel research in molecular life sciences has significant implications for philosophical understandings of explanation, modeling, and representation.

The process of condensation of an amorphous solid into a rigid matrix can often trap molecules in reversible binding sites. Exchange of the same molecular species with such sites is known to be sensitive to small chemical differences and to distinguish between enantiomers. In addition to their usefulness in chromatographic processes, such materials can separate, by solid phase extraction, specific compounds from complex mixtures. Furthermore, the trapped molecules can have their reactions guided and catalytically changed. The combination of this (...) spontaneously formed system of templates and catalytic sites may support a type of replication cycle, and suggests some pathways from simple chemistry toward the complexities of biology. © 2005 Wiley Periodicals, Inc. Complexity 11: 30–35, 2005 -/- . (shrink)

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 (...) 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 Systems Biology, 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)

The increasing place of evolutionary scenarios in functional biology is one of the major indicators of the present encounter between evolutionary biology and functional biology (such as physiology, biochemistry and molecular biology), the two branches of biology which remained separated throughout the twentieth century. Evolutionary scenarios were not absent from functional biology, but their places were limited, and they did not generate research programs. I compare two examples of these past scenarios with two (...) present-day ones. At least three characteristics distinguish present and past efforts: An excellent description of the systems under study, a rigorous use of the evolutionary models, and the possibility to experimentally test the evolutionary scenarios. These three criteria allow us to distinguish the domains in which the encounter is likely to be fruitful, and those where the obstacles to be overcome are high and in which the proposed scenarios have to be considered with considerable circumspection. (shrink)

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the framework (...) of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. (shrink)