In a number of membrane-bound viruses, ion channels are formed by integral membrane proteins. These channel proteins include M2 from influenza A, NB from influenza B, and, possibly, Vpu from HIV-1. M2 is important in facilitating uncoating of the influenza A viral genome and is the target of amantadine, an anti-influenza drug. The biological roles of NB and Vpu are less certain. In all cases, the protein contains a single transmembrane α-helix close to its N-terminus. Channels can be formed by (...) homo-oligomerization of these proteins, yielding bundles of transmembrane helices that span the membrane and surround a central ion-permeable pore. Molecular modeling may be used to integrate and interpret available experimental data concerning the structure of such transmembrane pores. This has proved successful for the M2 channel domain, where two independently derived models are in agreement with one another, and with solid-state nuclear magnetic resonance (NMR) data. Simulations based on channel models may yield insights into possible ion conduction and selectivity mechanisms. BioEssays 20:992–1000, 1998. © 1998 John Wiley & Sons, Inc. (shrink)

In a number of membrane-bound viruses, ion channels are formed by integral membrane proteins. These channel proteins include M2 from influenza A, NB from influenza B, and, possibly, Vpu from HIV-1. M2 is important in facilitating uncoating of the influenza A viral genome and is the target of amantadine, an anti-influenza drug. The biological roles of NB and Vpu are less certain. In all cases, the protein contains a single transmembrane α-helix close to its N-terminus. Channels can be formed by (...) homo-oligomerization of these proteins, yielding bundles of transmembrane helices that span the membrane and surround a central ion-permeable pore. Molecular modeling may be used to integrate and interpret available experimental data concerning the structure of such transmembrane pores. This has proved successful for the M2 channel domain, where two independently derived models are in agreement with one another, and with solid-state nuclear magnetic resonance (NMR) data. Simulations based on channel models may yield insights into possible ion conduction and selectivity mechanisms. BioEssays 20:992–1000, 1998. © 1998 John Wiley & Sons, Inc. (shrink)

The English language has adopted the word Tardis for something that looks simple from the outside but is much more complicated when inspected from the inside. The word comes from a BBC science fiction series, in which the Tardis is a machine for traveling in time and space, that looks like a phone booth from the outside. This paper claims that simulation models are a Tardis in a way that calls into question their transferability. The argument is developed taking (...) class='Hi'>Molecular Modeling and Simulation as an example. There, simulation models are force fields that describe the molecular interactions and that look like simple and highly modular mathematical expressions. To make them work, they contain parameters that are adjusted to match certain data. The role of these parameters and the way they are obtained is seriously under-appreciated. It is constitutive for the model and central for its applicability and performance. Hence, the model is more than it seems so that working with adjustable parameters deeply affects the ontology of simulation models. This is particularly crucial for the transferability of the models: the information on how a model was trained is like luggage the model must carry on its voyage. (shrink)

Thanks to genetic and biochemical advances on the molecular mechanism of circadian rhythms in Drosophila, theoretical models closely related to experimental observations can be considered for the regulatory mechanism of the circadian clock in this organism. Modeling is based on the autoregulatory negative feedback exerted by a complex between PER and TIM proteins on the expression of per and tim genes. The model predicts the occurrence of sustained circadian oscillations in continuous darkness. When incorporating light‐induced TIM degradation, the (...) model accounts for damping of oscillations in constant light, entrainment of the rhythm by light‐dark cycles of varying period or photoperiod, and phase shifting by light pulses. The model further provides a molecular dynamical explanation for the permanent or transient suppression of circadian rhythmicity triggered in a variety of organisms by a critical pulse of light. Finally, the model shows that to produce a robust rhythm the various clock genes must be expressed at the appropriate levels since sustained oscillations only occur in a precise range of parameter values. BioEssays 22:84–93, 2000. ©2000 John Wiley & Sons, Inc. (shrink)

Based on genetic and biochemical advances on the molecular mechanism of circadian rhythms, a computational model for the mammalian circadian clock is used to examine the dynamical bases of circadian‐clock‐related physiological disorders in humans. Entrainment by the light–dark cycle with a phase advance or a phase delay is associated with the Familial advanced sleep phase syndrome (FASPS) or the Delayed sleep phase syndrome (DSPS), respectively. Lack of entrainment corresponding to the occurrence of quasiperiodic oscillations with or without phase jump (...) can be associated with the non‐24 h sleep–wake syndrome. In the close vicinity of the entrainment domain, the model uncovers the possibility of infradian oscillations of very long period. Perturbation in the form of chronic jet lag, as used in mice, prevents entrainment of the circadian clock and results in chaotic or quasiperiodic oscillations. It is important to clarify the conditions for entrainment and for its failure because dysfunctions of the circadian clock may lead to physiological disorders, which pertain not only to the sleep–wake cycle but also to mood and cancer. BioEssays 30:590–600, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

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)

Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology -- unlike historians and social scientists -- had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology (...) as a unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology -- described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details" -- and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism -- defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics. The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development. (shrink)

_Philosophy of Molecular Medicine: Foundational Issues in Theory and Practice_ aims at a systematic investigation of a number of foundational issues in the field of molecular medicine. The volume is organized around four broad modules focusing, respectively, on the following key aspects: What are the nature, scope, and limits of molecular medicine? How does it provide explanations? How does it represent and model phenomena of interest? How does it infer new knowledge from data and experiments? The essays (...) collected here, authored by prominent scientists and philosophers of science, focus on a handful of mainstream topics in the philosophical literature, such as _causation_, _explanation_, _modeling_, and _scientific inference_. These previously unpublished contributions shed new light on these traditional topics by integrating them with problems, methods, and results from three prominent areas of contemporary biomedical science: _basic research_, _translational_ and _clinical research_, and _clinical practice_. (shrink)

I propose that a sociological and historical examination of nanotechnologists can contribute more to an understanding of nanotechnology than an ontological definition. Nanotechnology emerged from the convergent evolution of numerous "technical knowledge communities"-networks of tightly-interconnected people who operate between disciplines and individual research groups. I demonstrate this proposition by sketching the co-evolution of computational chemistry and computational nanotechnology. Computational chemistry arose in the 1950s but eventually segregated into an ab initio, basic research, physics-oriented flavor and an industry-oriented, molecular (...) class='Hi'>modeling and visualization, biochemical flavor. Computational nanotechnology arose in the 1990s as a synthesis of these two subgroups, infused by people and practices from computational materials science, engineering, computer science, and elsewhere. I show that to understand the aims and outcomes of computational nanotechnology-and nanotechnology more generally-we need to understand relationships between different, but related, nano knowledge communities and their dependence on particular practices, artifacts, and theories. (shrink)

The practice of theoretical research in chemistry largely consists in the construction of models without which experimentation would be impossible. The best-known theoretical models in chemistry are those of the molecular structures of chemical compounds. What is the correspondence between these models and the unobservable entities that they are meant to explain? What is the ontological status of molecular models? The anti-realists question the basis of the realists’ belief in these entities and the truth claims regarding them. Ultimately, (...) the realist/anti-realist debate points to the question of the scope of scientific knowledge. In this paper, I shall show that the description of natural entities offered by the contemporary scientific worldview reveals that molecular modeling presupposes a realistic epistemology that recognizes the limits of scientific objectification. (shrink)

We apply molecular code theory to a rule-based model of the human inner kinetochore and study how complex formation in general can give rise to molecular codes. We analyze 105 reaction networks generated from the rule-based inner kinetochore model in two variants: with and without dissociation of complexes. Interestingly, we found codes only when some but not all complexes are allowed to dissociate. We show that this is due to the fact that in the kinetochore model proteins can (...) only bind at kinetochores by attaching to already attached proteins and cannot form complexes in free solution. Using a generalized linear mixed model we study which centromere protein can take which role in a molecular code . By this, associations between CENPs and code roles are found. We observed that CenpA is a major risk factor while CenpQ is a major protection factor . Finally we show, using an abstract model of copolymer formation, that molecular codes can also be realized solely by the formation of stable complexes, which do not dissociate. For example, with particular dimers as context a molecular code mapping from two different monomers to two particular trimers can be realized just by non-selective complex formation. We conclude that the formation of protein complexes can be utilized by the cell to implement molecular codes. Living cells thus facilitate a subsystem allowing for an enormous flexibility in the realization of mappings, which can be used for specific regulatory processes, e.g. via the context of a mapping. (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)

This paper examines the role of mathematical idealization in describing and explaining various features of the world. It examines two cases: first, briefly, the modeling of shock formation using the idealization of the continuum. Second, and in more detail, the breaking of droplets from the points of view of both analytic fluid mechanics and molecular dynamical simulations at the nano-level. It argues that the continuum idealizations are explanatorily ineliminable and that a full understanding of certain physical phenomena cannot (...) be obtained through completely detailed, non-idealized representations. (shrink)

Model organisms are central to contemporary biology and studies of embryogenesis in particular. Biologists utilize only a small number of species to experimentally elucidate the phenomena and mechanisms of development. Critics have questioned whether these experimental models are good representatives of their targets because of the inherent biases involved in their selection (e.g., rapid development and short generation time). A standard response is that the manipulative molecular techniques available for experimental analysis mitigate, if not counterbalance, this concern. But the (...) most powerful investigative techniques and molecular methods are applicable to single-celled organisms (‘microbes’). Why not use unicellular rather than multicellular model organisms, which are the standard for developmental biology? To claim that microbes are not good representatives takes us back to the original criticism leveled against model organisms. Using empirical case studies of microbes modeling ontogeny, we break out of this circle of reasoning by showing: (a) that the criterion of representation is more complex than earlier discussions have emphasized; and, (b) that different aspects of manipulability are comparable in importance to representation when deciding if a model organism is a good model. These aspects of manipulability harbor the prospect of enhancing representation. The result is a better understanding of how developmental biologists conceptualize research using experimental models and suggestions for underappreciated avenues of inquiry using microbes. More generally, it demonstrates how the practical aspects of experimental biology must be scrutinized in order to understand the associated scientific reasoning. (shrink)

Biological forms are very complex, and mechanisms of pattern formation are not well understood. Although developmental biology deals with the mechanistic explanation of patterns, currently we do not know how to understand the mechanisms of pattern formation from huge amounts of molecular information. In this article, I present one useful tool, mathematical modeling, to obtain a mechanistic understanding of biological pattern formation, and show an actual example in lung branching morphogenesis. In this example, mathematical modeling plays an (...) indispensable role in understanding the biological phenomena. The model successfully reproduces the basic features of morphogenesis in vitro, but mechanism in vivo still remains to be elucidated. (shrink)

Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and (...) evolutionary biology believe that the use of many different experimental and mathematical models is necessary in order to do this. Many practitioners of both approaches misunderstand best practices of modeling, especially those related to model testing. We stress the need for biologists to better engage with best practices and for philosophers of biology providing normative guidance for biologists to better engage with current developments in biology. This is especially important as biology transitions from a “data-poor” to a “data-rich” discipline. If 21st century biology is going to capitalize on the unprecedented availability of ecological, evolutionary, and molecular data, of computational resources, and of mathematical and statistical tools, biologists will need a better understanding of what modeling is and can be. (shrink)

Neutrophil transepithelial migration is a central component of many inflammatory diseases of the gastrointestinal, respiratory and urinary tracts, and correlates with disease symptoms. In vitro modeling with polarized intestinal epithelial monolayers has shown that neutrophil transepithelial migration can influence crucial epithelial functions, ranging from barrier maintenance to electrolyte secretion. Studies have also demonstrated a dynamic involvement of the epithelium in modulating neutrophil transepithelial migration. Characterization of the molecular interactions between neutrophils and epithelial cells has revealed that transepithelial migration (...) is dependent on the neutrophil β2 integrin CD11b/CD18, and does not appear to involve adhesive interactions with the selectins or intercellular adhesion molecule‐1. Recent studies have implicated another transmembrane glycoprotein, CD47, as a crucial component of the transepithelial migration response. While the precise function of CD47 is not known, current evidence suggests that CD47‐dependent events occur after CD11b/CD18‐mediated neutrophil adhesion to the epithelium. This review will highlight key features of the current understanding of the molecular events important in neutrophil migration across epithelial surfaces. (shrink)

Today, the lipid bilayer structure is nearly ubiquitous, taken for granted in even the most rudimentary introductions to cell biology. Yet the image of the lipid bilayer, built out of lipids with heads and tails, went from having obscure origins deep in colloid chemical theory in 1924 to being “obvious to any competent physical chemist” by 1935. This chapter examines how this schematic, strictly heuristic explanation of the idea of molecular orientation was developed within colloid physical chemistry, and how (...) the image was transformed into a reflection of the reality and agency of lipid molecules in the biological microworld. Whereas in physical and colloid chemistry these images considered secondary to instrumental measurement and mathematical modeling of surface phenomena, in biology the manipulable image of the lipid on paper became an essential tool for the molecularization of the cell. (shrink)

The use of physical models of molecular structures as research tools has been central to the development of biochemistry and molecular biology. Intriguingly, it has received little attention from scholars of science. In this paper, I argue that these physical models are not mere three-dimensional representations but that they are in fact very special research tools: they are cognitive augmentations. Despite the fact that they are external props, these models serve as cognitive tools that augment and extend the (...) modeler’s cognitive capacities and performance in molecular modeling tasks. This cognitive enhancement is obtained because of the way the modeler interacts with these models, the models’ materiality contributing to the solving of the molecule’s structure. Furthermore, I argue that these material models and their component parts were designed, built and used specifically to serve as cognitive facilitators and cognitive augmentations. (shrink)

One important aspect of biological explanation is detailed causal modeling of particular phenomena in limited experimental background conditions. Recognising this allows one to appreciate that a sufficient condition for a reduction in biology is a molecular model of (1) only the demonstrated causal parameters of a biological model and (2) only within a replicable experimental background. These identities—which are ubiquitous in biology and form the basis of ruthless reductions (Bickle, Philosophy and neuroscience: a ruthlessly reductive account, 2003)—are criticised (...) as merely “local” (Sullivan, Synthese 167:511–539, 2009) or “fragmentary” (Schaffner, Synthese, 151(3):377–402, 2006). However, in an instructive case, a biological model is preserved in molecular terms, demonstrating a complex phenomenon that has been successfully reduced. (shrink)

Philosophical discussions of systems biology have enriched the notion of mechanistic explanation by pointing to the role of mathematical modeling. However, such accounts still focus on explanation in terms of tracking a mechanism's operation across time (by means of mental or computational simulation). My contention is that there are explanations of molecular systems where the explanatory understanding does not consist in tracking a mechanism's operation and productive continuity. I make this case by a discussion of bifurcation analysis in (...) dynamical systems, articulating the distinctive way in which explanatory understanding is provided, especially about the reversibility or irreversibility of molecular processes. (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)

Herein is provided a brief overview of agent-based modeling , with a particular slant toward its potential as a tool for the theoretical biologist. Of course, its use for experimentalists is obvious; they are, as a group, already using agent-based models to examine contemporary biological questions ranging from molecular processes to evolving ecological landscapes . For the modeler-theoretician, ABMs offer a new tool for thinking about the structure of biological processes, thus creating a conduit for integrative perspective taking (...) between the experimentalist and the theoretician. (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)

Theory of networks serves as a mathematical foundation for the construction and modeling of chemical structures and complicated networks. In particular, chemical networking theory has a wide range of utilizations in the study of chemical structures, where examination and manipulation of chemical structural information are made feasible by utilizing the numerical graph invariants. A network invariant or a topological index is a numerical measure of a chemical compound which is capable to describe the chemical structural properties such as melting (...) point, freezing point, density, pressure, tension, and temperature of chemical compounds. Wiener initiated the first distance-based TI which is considered to be the most important TI to preserve the chemical and physical properties of chemical structures. Later on, degree-based TI was introduced to find the π -electron energy of molecules. Recently, connection number-based TIs are studied which are more efficient than degree and distance-based TIs. In this paper, we compute the connection number-based TIs of the structure of crystal cubic carbons which are one of the most significant and interesting composites in modern resources of science due to the involvement of carbon atoms. (shrink)

This article offers three contrasting cases of the use of neutrality and drift in molecular evolution. In the first, neutrality is assumed as a simplest case for modeling. In the second and third, concepts of drift and neutrality are developed within the context of population genetics testing and the development and application of the molecular clock.

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account (...) of Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

ArgumentThis paper examines the role of metaphors in science on the basis of a historical case study. The study explores how metaphors of “genetic information,” “genetic code,” and scripture representations of heredity entered molecular biology and reshaped experimentation during the 1950s and 1960s. Following the approach of the philosopher Hans Blumenberg, I will argue that metaphors are not merely a means of popularization or a specific kind of modeling but rather are representations that can unfold an operational force (...) of their own.While the influence of cybernetics and information theory on molecular biology is well documented in historical analysis throughout recent years, this paper offers new insights into the metaphysical and religious resonances of textual metaphors in the life sciences. The main focus will be on developments in Germany, in particular on the work of the German biochemist Gerhard Schramm. In this historical case study the interaction between metaphors and experimental practices will be discussed. The paper analyzes different phases in the use of metaphors during the 1950s and 1960s: it will explore how the metaphors of a “genetic alphabet” or of “genetic code” developed into a new research program and eventually attained ontological status in the early 1960s. At that time Schramm's use of textual metaphors was reminiscent of nineteenth-century German natural philosophy. In this case, the metaphorical shift shows how the metaphor of a “genetic text” or a “genetic code,” which were central for the emerging molecular biology, drew on older cultural traditions with all of their metaphysical and religious preoccupations. (shrink)

This paper examines the adequacy of causal graph theory as a tool for modeling biological phenomena and formalizing biological explanations. I point out that the causal graph approach reaches it limits when it comes to modeling biological phenomena that involve complex spatial and structural relations. Using a case study from molecular biology, DNA-binding and -recognition of proteins, I argue that causal graph models fail to adequately represent and explain causal phenomena in this field. The inadequacy of these (...) models is due to their failure to include relevant spatial and structural information in a way that does not render the model non-explanatory, unmanageable, or inconsistent with basic assumptions of causal graph theory. (shrink)

Sketching as a scientific practice goes beyond the simple act of inscribing diagrams onto paper. Scientists produce a wide range of representations through sketching, as it is tightly coupled to model-based reasoning. Chemists in particular make extensive use of sketches to reason about chemical phenomena and to communicate their ideas. However, the chemical sciences have a unique problem in that chemists deal with the unseen world of the atomic-molecular level. Using sketches, chemists strive to develop causal mechanisms that emerge (...) from the structure and behavior of molecular-level entities, to explain observations of the macroscopic visible world. Interpreting these representations and constructing sketches of molecular-level processes is a crucial component of student learning in the modern chemistry classroom. Sketches also serve as an important component of assessment in the chemistry classroom as student sketches give insight into developing mental models, which allows instructors to observe how students are thinking about a process. In this paper we discuss how sketching can be used to promote such model-based reasoning in chemistry and discuss two case studies of curricular projects, CLUE and The Connected Chemistry Curriculum, that have demonstrated a benefit of this approach. We show how sketching activities can be centrally integrated into classroom norms to promote model-based reasoning both with and without component visualizations. Importantly, each of these projects deploys sketching in support of other types of inquiry activities, such as making predictions or depicting models to support a claim; sketching is not an isolated activity but is used as a tool to support model-based reasoning in the discipline. (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)

Almost 40 years since the discovery of microtubule dynamic instability, the molecular mechanisms underlying microtubule dynamics remain an area of intense research interest. The “standard model” of microtubule dynamics implicates a “cap” of GTP‐bound tubulin dimers at the growing microtubule end as the main determinant of microtubule stability. Loss of the GTP‐cap leads to microtubule “catastrophe,” a switch‐like transition from microtubule growth to shrinkage. However, recent studies, using biochemical in vitro reconstitution, cryo‐EM, and computational modeling approaches, challenge the (...) simple GTP‐cap model. Instead, a new perspective on the mechanisms of microtubule dynamics is emerging. In this view, highly dynamic transitions between different structural conformations of the growing microtubule end – which may or may not be directly linked to the nucleotide content at the microtubule end – ultimately drive microtubule catastrophe. (shrink)

How eukaryotic genomes are packaged into compact cylindrical chromosomes in preparation for cell divisions has remained one of the major unsolved questions of cell biology. Novel approaches to study the topology of DNA helices inside the nuclei of intact cells, paired with computational modeling and precise biomechanical measurements of isolated chromosomes, have advanced our understanding of mitotic chromosome architecture. In this Review Essay, we discuss – in light of these recent insights – the role of chromatin architecture and the (...) functions and possible mechanisms of SMC protein complexes and other molecular machines in the formation of mitotic chromosomes. Based on the information available, we propose a stepwise model of mitotic chromosome condensation that envisions the sequential generation of intra‐chromosomal linkages by condensin complexes in the context of cohesin‐mediated inter‐chromosomal linkages, assisted by topoisomerase II. The described scenario results in rod‐shaped metaphase chromosomes ready for their segregation to the cell poles. (shrink)

Understanding what is distinctive about the role of models in science requires characterizing broad patterns in how these models evolve in the face of experimental results. That is, we must examine not just model statics—how the model relates to theory, or represents the world, at some point in time—but also model dynamics—how the model both generates new experimental results and is modified in response to them. Visual representations of structure play a central role in the theoretical reasoning of organic chemists. (...) Not surprisingly, these representations have changed in important ways–in response to experimental and theoretical developments– throughout the history of organic chemistry. In many cases it is appropriate to understand the visual representations used by organic chemists as models. The evolution of the structural representations of organic chemists therefore provides a clear example of the dynamics of scientific modeling. In this paper I use a conception of scientific modeling drawn from the work of Mary Hesse to examine how the concept of a molecular conformation was incorporated into the visual representations of structure used by organic chemists. (shrink)

This paper examines a looming reproducibility crisis in the core of the hard sciences. Namely, it concentrates on molecular modeling and simulation (MMS), a family of methods that predict properties of substances through computing interactions on a molecular level and that is widely popular in physics, chemistry, materials science, and engineering. The paper argues that in order to make quantitative predictions, sophisticated models are needed which have to be evaluated with complex simulation procedures that amalgamate theoretical, technological, (...) and social factors – leading to problems with reproducibility. Thus, for methodological reasons, the predictive success causes a reproducibility problem. (shrink)

The rapidly changing field of genetics affects society through advances in health-care and through implications of genetic research. This study addresses the impacts of new genetic discoveries and technologies on different segments of today's society. The book begins with a chapter on genetic complexity, and subsequent chapters discuss moral and ethical questions arising from today's genetics from the perspectives of health care professionals, the media, the general public, special interest groups and commercial interests.

The ability to convert human somatic cells into induced pluripotent stem cells (iPSCs) is allowing the production of custom‐tailored cells for drug discovery and for the study of disease phenotypes at the cellular and molecular level. IPSCs have been derived from patients suffering from a large variety of disorders with different severities. In many cases, disease related phenotypes have been observed in iPSCs or their lineage‐specific progeny. Several proof of concept studies have demonstrated that these phenotypes can be reversed (...) in vitro using approved drugs. However, several challenges must be overcome to take full advantage of this technology. Here, we highlight recent advances in the field and discuss the main challenges associated with this technology as it applies to disease modelling. (shrink)

Mazur & Booth (1998) (M&B) suggested that high testosterone (T) relates to status, dominance, and (anti-) social behaviour. However, low T also relates to status and to formal dominance. The General Trait Covariance (GTC) model predicts both relations under the assumption that high and low T modulates the genotype in ways that enforce the development of almost polar covariant patterns of body, brain, intellectual, and personality traits, irrespective of race. The precise modelling of these dose-dependent molecular body-intelligence-personality-behaviour relations requires (...) that causes, mechanisms, and effects enjoy equal operational standing. (shrink)

Computational reproducibility possesses its own dynamics and narratives of crisis. Alongside the difficulties of computing as an ubiquitous yet complex scientific activity, computational reproducibility suffers from a naive expectancy of total reproducibility and a moral imperative to embrace the principles of free software as a non-negotiable epistemic virtue. We argue that the epistemic issues at stake in actual practices of computational reproducibility are best unveiled by focusing on software as a pivotal concept, one that is surprisingly often overlooked in accounts (...) of reproducibility issues. Software is not only about designing and coding but also about maintaining, supporting, distributing, licensing, and governance; it is not only about developers but also about users. We focus on openness debates among computational chemists involved in molecular modeling software packages as empirical grounding for our argument. We then identify and analyse four epistemic characteristics as key to the role of software in computational reproducibility. (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 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)

The theory of nonlinear complex systems has become a successful and widely used problem-solving approach in the natural sciences - from laser physics, quantum chaos and meteorology to molecular modeling in chemistry and computer simulations of cell growth in biology. In recent times it has been recognized that many of the social, ecological and political problems of mankind are also of a global, complex and nonlinear nature. And one of the most exciting topics of present scientific and public (...) interest is the idea that even the human mind is governed largely by the nonlinear dynamics of complex systems. In this wide-ranging but concise treatment Prof. Mainzer discusses, in nontechnical language, the common framework behind these endeavours. Special emphasis is given to the evolution of new structures in natural and cultural systems and it is seen clearly how the new integrative approach of complexity theory can give new insights that were not available using traditional reductionistic methods. (shrink)

We propose to study the wound healing in Zebrafish by using firstly a differential approach for modelling morphogens diffusion and cell chemotactic motion, and secondly a hybrid model of tissue regeneration, where cells are considered as individual objects and molecular concentrations are described by partial differential equations.

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. (shrink)

In this paper we address the question of minimal cognition by investigating the origin of some crucial cognitive properties from the very basic organisation of biological systems. More specifically, we propose a theoretical model of how a system can distinguish between specific features of its interaction with the environment, which is a fundamental requirement for the emergence of minimal forms of cognition. We argue that the appearance of this capacity is grounded in the molecular domain, and originates from basic (...) mechanisms of biological regulation. In doing so, our aim is to provide a theoretical account that can also work as a possible conceptual bridge between Synthetic Biology and Artificial Intelligence. In fact, we argue, Synthetic Biology can contribute to the study of minimal cognition, by providing a privileged approach to the study of these mechanisms by means of artificial systems. (shrink)

Ets proteins are a family of transcription factors that regulate the expression of a myriad of genes in a variety of tissues and cell types. This functional versatility emerges from their interactions with other structurally unrelated transcription factors. Indeed, combinatorial control is a characteristic property of Ets family members, involving interactions between Ets and other key transcriptional factors such as AP1, SRF, and Pax family members. Intriguingly, recent molecular modeling and crystallographic data suggest that not only the ETS (...) DNA-binding domain, but also the DNA recognition helix α3, are often directly required for Ets partner's selection. Indeed, while most DNA-binding proteins appear to exploit differences within their DNA recognition helices for sites selection, the Ets proteins exploit differences in their surfaces that interact with other transcription factors, which in turn may modify their DNA-binding properties in a promoter-specific fashion. Taken together, the gene-specific architecture of these unique complexes can mediate the selective control of transcriptional activity. BioEssays 24:362–370, 2002. ©2002 Wiley Periodicals, Inc. (shrink)

Philosophy of Molecular Medicine: Foundational Issues in Theory and Practice aims at a systematic investigation of a number of foundational issues in the field of molecular medicine. The volume is organized around four broad modules focusing, respectively, on the following key aspects: What are the nature, scope, and limits of molecular medicine? How does it provide explanations? How does it represent and model phenomena of interest? How does it infer new knowledge from data and experiments? The essays (...) collected here, authored by prominent scientists and philosophers of science, focus on a handful of mainstream topics in the philosophical literature, such as causation, explanation, modeling, and scientific inference. These previously unpublished contributions shed new light on these traditional topics by integrating them with problems, methods, and results from three prominent areas of contemporary biomedical science: basic research, translational and clinical research, and clinical practice. (shrink)