WorldWideScience

Sample records for complex biological system

  1. Complexity, Analysis and Control of Singular Biological Systems

    CERN Document Server

    Zhang, Qingling; Zhang, Xue

    2012-01-01

    Complexity, Analysis and Control of Singular Biological Systems follows the control of real-world biological systems at both ecological and phyisological levels concentrating on the application of now-extensively-investigated singular system theory. Much effort has recently been dedicated to the modelling and analysis of developing bioeconomic systems and the text establishes singular examples of these, showing how proper control can help to maintain sustainable economic development of biological resources. The book begins from the essentials of singular systems theory and bifurcations before tackling  the use of various forms of control in singular biological systems using examples including predator-prey relationships and viral vaccination and quarantine control. Researchers and graduate students studying the control of complex biological systems are shown how a variety of methods can be brought to bear and practitioners working with the economics of biological systems and their control will also find the ...

  2. Predictive modelling of complex agronomic and biological systems.

    Science.gov (United States)

    Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

    2013-09-01

    Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

  3. Complex biological and bio-inspired systems

    Energy Technology Data Exchange (ETDEWEB)

    Ecke, Robert E [Los Alamos National Laboratory

    2009-01-01

    The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

  4. Network Analyses in Systems Biology: New Strategies for Dealing with Biological Complexity

    DEFF Research Database (Denmark)

    Green, Sara; Serban, Maria; Scholl, Raphael

    2018-01-01

    of biological networks using tools from graph theory to the application of dynamical systems theory to understand the behavior of complex biological systems. We show how network approaches support and extend traditional mechanistic strategies but also offer novel strategies for dealing with biological...... strategies? When and how can network and mechanistic approaches interact in productive ways? In this paper we address these questions by focusing on how biological networks are represented and analyzed in a diverse class of case studies. Our examples span from the investigation of organizational properties...

  5. Complex fluids in biological systems experiment, theory, and computation

    CERN Document Server

    2015-01-01

    This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

  6. EPR spectroscopy of complex biological iron-sulfur systems.

    Science.gov (United States)

    Hagen, Wilfred R

    2018-02-21

    From the very first discovery of biological iron-sulfur clusters with EPR, the spectroscopy has been used to study not only purified proteins but also complex systems such as respiratory complexes, membrane particles and, later, whole cells. In recent times, the emphasis of iron-sulfur biochemistry has moved from characterization of individual proteins to the systems biology of iron-sulfur biosynthesis, regulation, degradation, and implications for human health. Although this move would suggest a blossoming of System-EPR as a specific, non-invasive monitor of Fe/S (dys)homeostasis in whole cells, a review of the literature reveals limited success possibly due to technical difficulties in adherence to EPR spectroscopic and biochemical standards. In an attempt to boost application of System-EPR the required boundary conditions and their practical applications are explicitly and comprehensively formulated.

  7. Toxicity of silver nanoparticles in biological systems: Does the complexity of biological systems matter?

    Science.gov (United States)

    Vazquez-Muñoz, Roberto; Borrego, Belen; Juárez-Moreno, Karla; García-García, Maritza; Mota Morales, Josué D; Bogdanchikova, Nina; Huerta-Saquero, Alejandro

    2017-07-05

    Currently, nanomaterials are more frequently in our daily life, specifically in biomedicine, electronics, food, textiles and catalysis just to name a few. Although nanomaterials provide many benefits, recently their toxicity profiles have begun to be explored. In this work, the toxic effects of silver nanoparticles (35nm-average diameter and Polyvinyl-Pyrrolidone-coated) on biological systems of different levels of complexity was assessed in a comprehensive and comparatively way, through a variety of viability and toxicological assays. The studied organisms included viruses, bacteria, microalgae, fungi, animal and human cells (including cancer cell lines). It was found that biological systems of different taxonomical groups are inhibited at concentrations of silver nanoparticles within the same order of magnitude. Thus, the toxicity of nanomaterials on biological/living systems, constrained by their complexity, e.g. taxonomic groups, resulted contrary to the expected. The fact that cells and virus are inhibited with a concentration of silver nanoparticles within the same order of magnitude could be explained considering that silver nanoparticles affects very primitive cellular mechanisms by interacting with fundamental structures for cells and virus alike. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. How do precision medicine and system biology response to human body's complex adaptability?

    Science.gov (United States)

    Yuan, Bing

    2016-12-01

    In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

  9. From globally coupled maps to complex-systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Kaneko, Kunihiko, E-mail: kaneko@complex.c.u-tokyo.ac.jp [Research Center for Complex Systems Biology, Graduate School of Arts and Sciences, The University of Tokyo 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902 (Japan)

    2015-09-15

    Studies of globally coupled maps, introduced as a network of chaotic dynamics, are briefly reviewed with an emphasis on novel concepts therein, which are universal in high-dimensional dynamical systems. They include clustering of synchronized oscillations, hierarchical clustering, chimera of synchronization and desynchronization, partition complexity, prevalence of Milnor attractors, chaotic itinerancy, and collective chaos. The degrees of freedom necessary for high dimensionality are proposed to equal the number in which the combinatorial exceeds the exponential. Future analysis of high-dimensional dynamical systems with regard to complex-systems biology is briefly discussed.

  10. Systems Biology and Health Systems Complexity in;

    NARCIS (Netherlands)

    Donald Combs, C.; Barham, S.R.; Sloot, P.M.A.

    2016-01-01

    Systems biology addresses interactions in biological systems at different scales of biological organization, from the molecular to the cellular, organ, organism, societal, and ecosystem levels. This chapter expands on the concept of systems biology, explores its implications for individual patients

  11. Life: An Introduction to Complex Systems Biology

    CERN Document Server

    Kaneko, Kunihiko

    2006-01-01

    What is life? Has molecular biology given us a satisfactory answer to this question? And if not, why, and how to carry on from there? This book examines life not from the reductionist point of view, but rather asks the question: what are the universal properties of living systems and how can one construct from there a phenomenological theory of life that leads naturally to complex processes such as reproductive cellular systems, evolution and differentiation? The presentation has been deliberately kept fairly non-technical so as to address a broad spectrum of students and researchers from the natural sciences and informatics.

  12. Network biology: Describing biological systems by complex networks. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

    Science.gov (United States)

    Jalili, Mahdi

    2018-03-01

    I enjoyed reading Gosak et al. review on analysing biological systems from network science perspective [1]. Network science, first started within Physics community, is now a mature multidisciplinary field of science with many applications ranging from Ecology to biology, medicine, social sciences, engineering and computer science. Gosak et al. discussed how biological systems can be modelled and described by complex network theory which is an important application of network science. Although there has been considerable progress in network biology over the past two decades, this is just the beginning and network science has a great deal to offer to biology and medical sciences.

  13. 7th Annual Systems Biology Symposium: Systems Biology and Engineering

    Energy Technology Data Exchange (ETDEWEB)

    Galitski, Timothy P.

    2008-04-01

    Systems biology recognizes the complex multi-scale organization of biological systems, from molecules to ecosystems. The International Symposium on Systems Biology has been hosted by the Institute for Systems Biology in Seattle, Washington, since 2002. The annual two-day event gathers the most influential researchers transforming biology into an integrative discipline investingating complex systems. Engineering and application of new technology is a central element of systems biology. Genome-scale, or very small-scale, biological questions drive the enigneering of new technologies, which enable new modes of experimentation and computational analysis, leading to new biological insights and questions. Concepts and analytical methods in engineering are now finding direct applications in biology. Therefore, the 2008 Symposium, funded in partnership with the Department of Energy, featured global leaders in "Systems Biology and Engineering."

  14. Reflecting on complexity of biological systems: Kant and beyond?

    Science.gov (United States)

    Van de Vijver, Gertrudis; Van Speybroeck, Linda; Vandevyvere, Windy

    2003-01-01

    Living organisms are currently most often seen as complex dynamical systems that develop and evolve in relation to complex environments. Reflections on the meaning of the complex dynamical nature of living systems show an overwhelming multiplicity in approaches, descriptions, definitions and methodologies. Instead of sustaining an epistemic pluralism, which often functions as a philosophical armistice in which tolerance and so-called neutrality discharge proponents of the burden to clarify the sources and conditions of agreement and disagreement, this paper aims at analysing: (i) what has been Kant's original conceptualisation of living organisms as natural purposes; (ii) how the current perspectives are to be related to Kant's viewpoint; (iii) what are the main trends in current complexity thinking. One of the basic ideas is that the attention for structure and its epistemological consequences witness to a great extent of Kant's viewpoint, and that the idea of organisational stratification today constitutes a different breeding ground within which complexity issues are raised. The various approaches of complexity in biological systems are captured in terms of two different styles, universalism and (weak and strong) constructivism, between which hybrid forms exist.

  15. Degeneracy: a link between evolvability, robustness and complexity in biological systems

    Directory of Open Access Journals (Sweden)

    Whitacre James M

    2010-02-01

    Full Text Available Abstract A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability and evidence of an intimate relationship between robustness and complexity in biology. This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability.

  16. Development trend of radiation biology research-systems radiation biology

    International Nuclear Information System (INIS)

    Min Rui

    2010-01-01

    Radiation biology research has past 80 years. We have known much more about fundamentals, processes and results of biology effects induced by radiation and various factors that influence biology effects wide and deep, however many old and new scientific problems occurring in the field of radiation biology research remain to be illustrated. To explore and figure these scientific problems need systemic concept, methods and multi dimension view on the base of considerations of complexity of biology system, diversity of biology response, temporal and spatial process of biological effects during occurrence, and complex feed back network of biological regulations. (authors)

  17. Complex systems of biological interest stability under ionising radiations

    International Nuclear Information System (INIS)

    Maclot, Sylvain

    2014-01-01

    This PhD work presents the study of stability of molecular systems of biological interest in the gas phase after interaction with ionising radiations. The use of ionising radiation can probe the physical chemistry of complex systems at the molecular scale and thus consider their intrinsic properties. Beyond the fundamental aspect, this work is part of the overall understanding of radiation effects on living organisms and in particular the use of ionizing radiation in radiotherapy. Specifically, this study focused on the use of low-energy multiply charged ions (tens of keV) provided by the GANIL (Caen), which includes most of the experiments presented. In addition, experiments using VUV photons were also conducted at synchrotron ELETTRA (Trieste, Italy). The bio-molecular systems studied are amino acids and nucleic acid constituents. Using an experimental crossed beams device allows interaction between biomolecules and ionising radiation leads mainly to the ionization and fragmentation of the system. The study of its relaxation dynamics is by time-of-flight mass spectrometry coupled to a coincidences measurements method. It is shown that an approach combining experiment and theory allows a detailed study of the fragmentation dynamics of complex systems. The results indicate that fragmentation is generally governed by the Coulomb repulsion but the intramolecular rearrangements involve specific relaxation mechanisms. (author) [fr

  18. PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

    Science.gov (United States)

    Domijan, Mirela; Brown, Paul E; Shulgin, Boris V; Rand, David A

    2016-03-10

    Over the last decade sensitivity analysis techniques have been shown to be very useful to analyse complex and high dimensional Systems Biology models. However, many of the currently available toolboxes have either used parameter sampling, been focused on a restricted set of model observables of interest, studied optimisation of a objective function, or have not dealt with multiple simultaneous model parameter changes where the changes can be permanent or temporary. Here we introduce our new, freely downloadable toolbox, PeTTSy (Perturbation Theory Toolbox for Systems). PeTTSy is a package for MATLAB which implements a wide array of techniques for the perturbation theory and sensitivity analysis of large and complex ordinary differential equation (ODE) based models. PeTTSy is a comprehensive modelling framework that introduces a number of new approaches and that fully addresses analysis of oscillatory systems. It examines sensitivity analysis of the models to perturbations of parameters, where the perturbation timing, strength, length and overall shape can be controlled by the user. This can be done in a system-global setting, namely, the user can determine how many parameters to perturb, by how much and for how long. PeTTSy also offers the user the ability to explore the effect of the parameter perturbations on many different types of outputs: period, phase (timing of peak) and model solutions. PeTTSy can be employed on a wide range of mathematical models including free-running and forced oscillators and signalling systems. To enable experimental optimisation using the Fisher Information Matrix it efficiently allows one to combine multiple variants of a model (i.e. a model with multiple experimental conditions) in order to determine the value of new experiments. It is especially useful in the analysis of large and complex models involving many variables and parameters. PeTTSy is a comprehensive tool for analysing large and complex models of regulatory and

  19. Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

    Science.gov (United States)

    Dirnbeck, Matthew R.

    Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function

  20. Bridging Mechanistic and Phenomenological Models of Complex Biological Systems.

    Science.gov (United States)

    Transtrum, Mark K; Qiu, Peng

    2016-05-01

    The inherent complexity of biological systems gives rise to complicated mechanistic models with a large number of parameters. On the other hand, the collective behavior of these systems can often be characterized by a relatively small number of phenomenological parameters. We use the Manifold Boundary Approximation Method (MBAM) as a tool for deriving simple phenomenological models from complicated mechanistic models. The resulting models are not black boxes, but remain expressed in terms of the microscopic parameters. In this way, we explicitly connect the macroscopic and microscopic descriptions, characterize the equivalence class of distinct systems exhibiting the same range of collective behavior, and identify the combinations of components that function as tunable control knobs for the behavior. We demonstrate the procedure for adaptation behavior exhibited by the EGFR pathway. From a 48 parameter mechanistic model, the system can be effectively described by a single adaptation parameter τ characterizing the ratio of time scales for the initial response and recovery time of the system which can in turn be expressed as a combination of microscopic reaction rates, Michaelis-Menten constants, and biochemical concentrations. The situation is not unlike modeling in physics in which microscopically complex processes can often be renormalized into simple phenomenological models with only a few effective parameters. The proposed method additionally provides a mechanistic explanation for non-universal features of the behavior.

  1. Using multi-criteria analysis of simulation models to understand complex biological systems

    Science.gov (United States)

    Maureen C. Kennedy; E. David. Ford

    2011-01-01

    Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

  2. Emergence of biological complexity: Criticality, renewal and memory

    International Nuclear Information System (INIS)

    Grigolini, Paolo

    2015-01-01

    The key purpose of this article is to establish a connection between two emerging fields of research in theoretical biology. The former focuses on the concept of criticality borrowed from physics that is expected to be extensible to biology through a robust theoretical approach that although not yet available shall eventually shed light into the origin of cognition. The latter, largely based on the tracking of single molecules diffusing in biological cells, is bringing to the general attention the need to go beyond the ergodic assumption currently done in the traditional statistical physics. We show that replacing critical slowing down with temporal complexity explains why biological systems at criticality are resilient and why long-range correlations are compatible with the free-will condition necessary for the emergence of cognition. Temporal complexity generates ergodicity breakdown and requires new forms of response of complex systems to external stimuli. We concisely illustrate these new forms of information transport and we also address the challenging issue of combining temporal complexity with coherence and renewal with infinite memory.

  3. Modelling and Simulating Complex Systems in Biology: introducing NetBioDyn : A Pedagogical and Intuitive Agent-Based Software

    OpenAIRE

    Ballet, Pascal; Rivière, Jérémy; Pothet, Alain; Théron, Michaël; Pichavant, Karine; Abautret, Frank; Fronville, Alexandra; Rodin, Vincent

    2017-01-01

    International audience; Modelling and teaching complex biological systems is a difficult process. Multi-Agent Based Simulations (MABS) have proved to be an appropriate approach both in research and education when dealing with such systems including emergent, self-organizing phenomena. This chapter presents NetBioDyn, an original software aimed at biologists (students, teachers, researchers) to easily build and simulate complex biological mechanisms observed in multicellular and molecular syst...

  4. Entropy as a method to investigate complex biological systems. An alternative view on the biological transition from healthy aging to frailty

    Directory of Open Access Journals (Sweden)

    Roberto Siciliano

    2017-07-01

    Full Text Available Everyone is subject to a process of progressive deterioration of control mechanisms, which supervise the complex network of human physiological functions, reducing the individual ability to adapt to emerging situations of stress or change. In the light of results obtained during the last years, it appears that some of the tools of nonlinear dynamics, first developed for the physical sciences are well suited for studies of biological systems. We believe that, considering the level of order or complexity of the anatomical apparatus by measuring a physical quantity, which is the entropy, we can evaluate the health status or vice versa fragility of a biological system. In particular, a reduction in the entropy value, indicates modification of the structural order with a progressive reduction of functional reserve of the individual, which is associated with a failure to adapt to stress conditions, difficult to be analyzed and documented with a unique traditional biochemical or biomolecular vision. Therefore, in this paper, we present a method that, conceptually combines complexity, disease and aging, alloys Poisson statistics, predictive of the personal level of health, to the entropy value indicating the status of bio-dynamic and functional body, seen as a complex and open thermodynamic system.

  5. Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.

    Science.gov (United States)

    Vernon, Ian; Liu, Junli; Goldstein, Michael; Rowe, James; Topping, Jen; Lindsey, Keith

    2018-01-02

    Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology. Bayesian statistical methodology for the uncertainty analysis of complex models is introduced, which is designed to address the high dimensional global parameter search problem. Bayesian emulators that mimic the systems biology model but which are extremely fast to evaluate are embeded within an iterative history match: an efficient method to search high dimensional spaces within a more formal statistical setting, while incorporating major sources of uncertainty. The approach is demonstrated via application to a model of hormonal crosstalk in Arabidopsis root development, which has 32 rate parameters, for which we identify the sets of rate parameter values that lead to acceptable matches between model output and observed trend data. The multiple insights into the model's structure that this analysis provides are discussed. The methodology is applied to a second related model, and the biological consequences of the resulting comparison, including the evaluation of gene functions, are described. Bayesian uncertainty analysis for complex models using both emulators and history matching is shown to be a powerful technique that can greatly aid the study of a large class of systems biology models. It both provides insight into model behaviour

  6. Informing biological design by integration of systems and synthetic biology.

    Science.gov (United States)

    Smolke, Christina D; Silver, Pamela A

    2011-03-18

    Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Omics/systems biology and cancer cachexia.

    Science.gov (United States)

    Gallagher, Iain J; Jacobi, Carsten; Tardif, Nicolas; Rooyackers, Olav; Fearon, Kenneth

    2016-06-01

    Cancer cachexia is a complex syndrome generated by interaction between the host and tumour cells with a background of treatment effects and toxicity. The complexity of the physiological pathways likely involved in cancer cachexia necessitates a holistic view of the relevant biology. Emergent properties are characteristic of complex systems with the result that the end result is more than the sum of its parts. Recognition of the importance of emergent properties in biology led to the concept of systems biology wherein a holistic approach is taken to the biology at hand. Systems biology approaches will therefore play an important role in work to uncover key mechanisms with therapeutic potential in cancer cachexia. The 'omics' technologies provide a global view of biological systems. Genomics, transcriptomics, proteomics, lipidomics and metabolomics approaches all have application in the study of cancer cachexia to generate systems level models of the behaviour of this syndrome. The current work reviews recent applications of these technologies to muscle atrophy in general and cancer cachexia in particular with a view to progress towards integration of these approaches to better understand the pathology and potential treatment pathways in cancer cachexia. Copyright © 2016. Published by Elsevier Ltd.

  8. Heuristic Strategies in Systems Biology

    Directory of Open Access Journals (Sweden)

    Fridolin Gross

    2016-06-01

    Full Text Available 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.

  9. Encyclopedia of Complexity and Systems Science

    CERN Document Server

    Meyers, Robert A

    2009-01-01

    Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

  10. Circulating immune complexes – reviewing the biological roles in ...

    African Journals Online (AJOL)

    Circulating immune complexes – reviewing the biological roles in human immune function and exercise. ... studies that have investigated CIC's following exercise and proposes that a comprehensive understanding and interpretation of immune system responses to exercise should take these complexes into consideration.

  11. Third International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems

    2006-01-01

    In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains over 35 papers selected from those presented at the conference on topics including: self-organization in biology, ecological systems, language, economic modeling, ecological systems, artificial life, robotics, and complexity and art. ALI MINAI is an Affiliate of the New England Complex Systems Institute and an Associate Professor in the Department of Electrical and Computer Engine...

  12. Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

    Science.gov (United States)

    De Domenico, Manlio

    2018-03-01

    Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

  13. Industrial systems biology and its impact on synthetic biology of yeast cell factories

    DEFF Research Database (Denmark)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-01-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools......, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex...... regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal...

  14. From Molecules to Life: Quantifying the Complexity of Chemical and Biological Systems in the Universe.

    Science.gov (United States)

    Böttcher, Thomas

    2018-01-01

    Life is a complex phenomenon and much research has been devoted to both understanding its origins from prebiotic chemistry and discovering life beyond Earth. Yet, it has remained elusive how to quantify this complexity and how to compare chemical and biological units on one common scale. Here, a mathematical description of molecular complexity was applied allowing to quantitatively assess complexity of chemical structures. This in combination with the orthogonal measure of information complexity resulted in a two-dimensional complexity space ranging over the entire spectrum from molecules to organisms. Entities with a certain level of information complexity directly require a functionally complex mechanism for their production or replication and are hence indicative for life-like systems. In order to describe entities combining molecular and information complexity, the term biogenic unit was introduced. Exemplified biogenic unit complexities were calculated for ribozymes, protein enzymes, multimeric protein complexes, and even an entire virus particle. Complexities of prokaryotic and eukaryotic cells, as well as multicellular organisms, were estimated. Thereby distinct evolutionary stages in complexity space were identified. The here developed approach to compare the complexity of biogenic units allows for the first time to address the gradual characteristics of prebiotic and life-like systems without the need for a definition of life. This operational concept may guide our search for life in the Universe, and it may direct the investigations of prebiotic trajectories that lead towards the evolution of complexity at the origins of life.

  15. Systems Biology — the Broader Perspective

    Directory of Open Access Journals (Sweden)

    Jonathan Bard

    2013-06-01

    Full Text Available Systems biology has two general aims: a narrow one, which is to discover how complex networks of proteins work, and a broader one, which is to integrate the molecular and network data with the generation and function of organism phenotypes. Doing all this involves complex methodologies, but underpinning the subject are more general conceptual problems about upwards and downwards causality, complexity and information storage, and their solutions provide the constraints within which these methodologies can be used. This essay considers these general aspects and the particular role of protein networks; their functional outputs are often the processes driving phenotypic change and physiological function—networks are, in a sense, the units of systems biology much as proteins are for molecular biology. It goes on to argue that the natural language for systems-biological descriptions of biological phenomena is the mathematical graph (a set of connected facts of the general form [process] (e.g., [activates] . Such graphs not only integrate events at different levels but emphasize the distributed nature of control as well as displaying a great deal of data. The implications and successes of these ideas for physiology, pharmacology, development and evolution are briefly considered. The paper concludes with some challenges for the future.

  16. Systems Biology, Systems Medicine, Systems Pharmacology: The What and The Why.

    Science.gov (United States)

    Stéphanou, Angélique; Fanchon, Eric; Innominato, Pasquale F; Ballesta, Annabelle

    2018-05-09

    Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences.

  17. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-06-01

    The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.

  18. Philosophy of Systems and Synthetic Biology

    DEFF Research Database (Denmark)

    Green, Sara

    2017-01-01

    This entry aims to clarify how systems and synthetic biology contribute to and extend discussions within philosophy of science. Unlike fields such as developmental biology or molecular biology, systems and synthetic biology are not easily demarcated by a focus on a specific subject area or level...... of organization. Rather, they are characterized by the development and application of mathematical, computational, and synthetic modeling strategies in response to complex problems and challenges within the life sciences. Proponents of systems and synthetic biology often stress the necessity of a perspective...... that goes beyond the scope of molecular biology and genetic engineering, respectively. With the emphasis on systems and interaction networks, the approaches explicitly engage in one of the oldest philosophical discussions on the relationship between parts and wholes, or between reductionism and holism...

  19. Systems Biology of Metabolism: Annual Review of Biochemistry

    DEFF Research Database (Denmark)

    Nielsen, Jens

    2017-01-01

    Metabolism is highly complex and involves thousands of different connected reactions; it is therefore necessary to use mathematical models for holistic studies. The use of mathematical models in biology is referred to as systems biology. In this review, the principles of systems biology are descr...

  20. The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

    Science.gov (United States)

    Pollard, Thomas D

    2014-12-02

    This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  1. Industrial systems biology and its impact on synthetic biology of yeast cell factories.

    Science.gov (United States)

    Fletcher, Eugene; Krivoruchko, Anastasia; Nielsen, Jens

    2016-06-01

    Engineering industrial cell factories to effectively yield a desired product while dealing with industrially relevant stresses is usually the most challenging step in the development of industrial production of chemicals using microbial fermentation processes. Using synthetic biology tools, microbial cell factories such as Saccharomyces cerevisiae can be engineered to express synthetic pathways for the production of fuels, biopharmaceuticals, fragrances, and food flavors. However, directing fluxes through these synthetic pathways towards the desired product can be demanding due to complex regulation or poor gene expression. Systems biology, which applies computational tools and mathematical modeling to understand complex biological networks, can be used to guide synthetic biology design. Here, we present our perspective on how systems biology can impact synthetic biology towards the goal of developing improved yeast cell factories. Biotechnol. Bioeng. 2016;113: 1164-1170. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  2. Top-down models in biology: explanation and control of complex living systems above the molecular level.

    Science.gov (United States)

    Pezzulo, Giovanni; Levin, Michael

    2016-11-01

    It is widely assumed in developmental biology and bioengineering that optimal understanding and control of complex living systems follows from models of molecular events. The success of reductionism has overshadowed attempts at top-down models and control policies in biological systems. However, other fields, including physics, engineering and neuroscience, have successfully used the explanations and models at higher levels of organization, including least-action principles in physics and control-theoretic models in computational neuroscience. Exploiting the dynamic regulation of pattern formation in embryogenesis and regeneration requires new approaches to understand how cells cooperate towards large-scale anatomical goal states. Here, we argue that top-down models of pattern homeostasis serve as proof of principle for extending the current paradigm beyond emergence and molecule-level rules. We define top-down control in a biological context, discuss the examples of how cognitive neuroscience and physics exploit these strategies, and illustrate areas in which they may offer significant advantages as complements to the mainstream paradigm. By targeting system controls at multiple levels of organization and demystifying goal-directed (cybernetic) processes, top-down strategies represent a roadmap for using the deep insights of other fields for transformative advances in regenerative medicine and systems bioengineering. © 2016 The Author(s).

  3. Quantitative computational models of molecular self-assembly in systems biology.

    Science.gov (United States)

    Thomas, Marcus; Schwartz, Russell

    2017-05-23

    Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

  4. Ins and outs of systems biology vis-à-vis molecular biology: continuation or clear cut?

    Science.gov (United States)

    De Backer, Philippe; De Waele, Danny; Van Speybroeck, Linda

    2010-03-01

    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.

  5. Seasonal allergic rhinitis and systems biology-oriented biomarker discovery

    NARCIS (Netherlands)

    Baars, E.W.; Nierop, A.F.M.; Savelkoul, H.F.J.

    2015-01-01

    There is an increasing interest in science and medicine in the systems approach. Instead of the reductionist approach that focuses on the physical and chemical properties of the individual components, systems biology aims to describe, understand, and explain from the complex biological systems

  6. Mammalian Synthetic Biology: Engineering Biological Systems.

    Science.gov (United States)

    Black, Joshua B; Perez-Pinera, Pablo; Gersbach, Charles A

    2017-06-21

    The programming of new functions into mammalian cells has tremendous application in research and medicine. Continued improvements in the capacity to sequence and synthesize DNA have rapidly increased our understanding of mechanisms of gene function and regulation on a genome-wide scale and have expanded the set of genetic components available for programming cell biology. The invention of new research tools, including targetable DNA-binding systems such as CRISPR/Cas9 and sensor-actuator devices that can recognize and respond to diverse chemical, mechanical, and optical inputs, has enabled precise control of complex cellular behaviors at unprecedented spatial and temporal resolution. These tools have been critical for the expansion of synthetic biology techniques from prokaryotic and lower eukaryotic hosts to mammalian systems. Recent progress in the development of genome and epigenome editing tools and in the engineering of designer cells with programmable genetic circuits is expanding approaches to prevent, diagnose, and treat disease and to establish personalized theranostic strategies for next-generation medicines. This review summarizes the development of these enabling technologies and their application to transforming mammalian synthetic biology into a distinct field in research and medicine.

  7. Sixth International Conference on Complex Systems

    CERN Document Server

    Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems

    2008-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.

  8. On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

    Science.gov (United States)

    Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

    2017-12-05

    The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

  9. European Conference on Complex Systems 2012

    CERN Document Server

    Kirkilionis, Markus; Nicolis, Gregoire

    2013-01-01

    The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered:  1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.  

  10. On the interplay between mathematics and biology: hallmarks toward a new systems biology.

    Science.gov (United States)

    Bellomo, Nicola; Elaiw, Ahmed; Althiabi, Abdullah M; Alghamdi, Mohammed Ali

    2015-03-01

    This paper proposes a critical analysis of the existing literature on mathematical tools developed toward systems biology approaches and, out of this overview, develops a new approach whose main features can be briefly summarized as follows: derivation of mathematical structures suitable to capture the complexity of biological, hence living, systems, modeling, by appropriate mathematical tools, Darwinian type dynamics, namely mutations followed by selection and evolution. Moreover, multiscale methods to move from genes to cells, and from cells to tissue are analyzed in view of a new systems biology approach. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  12. Extending Life Concepts to Complex Systems

    Directory of Open Access Journals (Sweden)

    Jean Le Fur

    2013-01-01

    Full Text Available There is still no consensus definition of complex systems. This article explores, as a heuristic approach, the possibility of using notions associated with life as transversal concepts for defining complex systems. This approach is developed within a general classification of systems, with complex systems considered as a general ‘living things’ category and living organisms as a specialised class within this category. Concepts associated with life are first explored in the context of complex systems: birth, death and lifetime, adaptation, ontogeny and growth, reproduction. Thereafter, a refutation approach is used to test the proposed classification against a set of diverse systems, including a reference case, edge cases and immaterial complex systems. The summary of this analysis is then used to generate a definition of complex systems, based on the proposal, and within the background of cybernetics, complex adaptive systems and biology. Using notions such as ‘birth’ or ‘lifespan’ as transversal concepts may be of heuristic value for the generic characterization of complex systems, opening up new lines of research for improving their definition.

  13. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  14. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-01-01

    In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable

  15. Critical evaluation of the JDO API for the persistence and portability requirements of complex biological databases

    Directory of Open Access Journals (Sweden)

    Schwieger Michael

    2005-01-01

    Full Text Available Abstract Background Complex biological database systems have become key computational tools used daily by scientists and researchers. Many of these systems must be capable of executing on multiple different hardware and software configurations and are also often made available to users via the Internet. We have used the Java Data Object (JDO persistence technology to develop the database layer of such a system known as the SigPath information management system. SigPath is an example of a complex biological database that needs to store various types of information connected by many relationships. Results Using this system as an example, we perform a critical evaluation of current JDO technology; discuss the suitability of the JDO standard to achieve portability, scalability and performance. We show that JDO supports portability of the SigPath system from a relational database backend to an object database backend and achieves acceptable scalability. To answer the performance question, we have created the SigPath JDO application benchmark that we distribute under the Gnu General Public License. This benchmark can be used as an example of using JDO technology to create a complex biological database and makes it possible for vendors and users of the technology to evaluate the performance of other JDO implementations for similar applications. Conclusions The SigPath JDO benchmark and our discussion of JDO technology in the context of biological databases will be useful to bioinformaticians who design new complex biological databases and aim to create systems that can be ported easily to a variety of database backends.

  16. Morphogenetic Engineering Toward Programmable Complex Systems

    CERN Document Server

    Sayama, Hiroki; Michel, Olivier

    2012-01-01

    Generally, spontaneous pattern formation phenomena are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both self-organized and architectural.   This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is placed on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.   Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as   > How do biological organisms carry out morphog...

  17. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  18. Graphics processing units in bioinformatics, computational biology and systems biology.

    Science.gov (United States)

    Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

    2017-09-01

    Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

  19. Systems Biology of the Fluxome

    Directory of Open Access Journals (Sweden)

    Miguel A. Aon

    2015-07-01

    Full Text Available The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms.

  20. Systems biology approach to bioremediation

    Energy Technology Data Exchange (ETDEWEB)

    Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

    2012-06-01

    Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potential for making bioremediation breakthroughs and illuminating the ‘black box’.

  1. Complexity: the organizing principle at the interface of biological (dis ...

    Indian Academy of Sciences (India)

    RAMRAY BHAT

    2017-07-05

    Jul 5, 2017 ... opment of complexity theory in the context of biological systems. ... (DST), a mathematical enterprise that deals with the behaviour of ... and application of programming to trace the dynamical .... with the resultant organization being regulated by the ... more regular the pattern, the smaller the program needed.

  2. Plant Systems Biology at the Single-Cell Level.

    Science.gov (United States)

    Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

    2017-11-01

    Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Genomewide effects of peroxisome proliferator-activated receptor gamma in macrophages and dendritic cells--revealing complexity through systems biology.

    Science.gov (United States)

    Cuaranta-Monroy, Ixchelt; Kiss, Mate; Simandi, Zoltan; Nagy, Laszlo

    2015-09-01

    Systems biology approaches have become indispensable tools in biomedical and basic research. These data integrating bioinformatic methods gained prominence after high-throughput technologies became available to investigate complex cellular processes, such as transcriptional regulation and protein-protein interactions, on a scale that had not been studied before. Immunology is one of the medical fields that systems biology impacted profoundly due to the plasticity of cell types involved and the accessibility of a wide range of experimental models. In this review, we summarize the most important recent genomewide studies exploring the function of peroxisome proliferator-activated receptor γ in macrophages and dendritic cells. PPARγ ChIP-seq experiments were performed in adipocytes derived from embryonic stem cells to complement the existing data sets and to provide comparators to macrophage data. Finally, lists of regulated genes generated from such experiments were analysed with bioinformatics and system biology approaches. We show that genomewide studies utilizing high-throughput data acquisition methods made it possible to gain deeper insights into the role of PPARγ in these immune cell types. We also demonstrate that analysis and visualization of data using network-based approaches can be used to identify novel genes and functions regulated by the receptor. The example of PPARγ in macrophages and dendritic cells highlights the crucial importance of systems biology approaches in establishing novel cellular functions for long-known signaling pathways. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

  4. Fourth International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems IV

    2008-01-01

    In June of 2002, over 500 professors, students and researchers met in Boston, Massachusetts for the Fourth International Conference on Complex Systems. The attendees represented a remarkably diverse collection of fields: biology, ecology, physics, engineering, computer science, economics, psychology and sociology, The goal of the conference was to encourage cross-fertilization between the many disciplines represented and to deepen understanding of the properties common to all complex systems. This volume contains 43 papers selected from the more than 200 presented at the conference. Topics include: cellular automata, neurology, evolution, computer science, network dynamics, and urban planning. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex sys...

  5. Systems Biology and Stem Cell Pluripotency

    DEFF Research Database (Denmark)

    Mashayekhi, Kaveh; Hall, Vanessa Jane; Freude, Kristine

    2016-01-01

    Recent breakthroughs in stem cell biology have accelerated research in the area of regenerative medicine. Over the past years, it has become possible to derive patient-specific stem cells which can be used to generate different cell populations for potential cell therapy. Systems biological...... modeling of stem cell pluripotency and differentiation have largely been based on prior knowledge of signaling pathways, gene regulatory networks, and epigenetic factors. However, there is a great need to extend the complexity of the modeling and to integrate different types of data, which would further...... improve systems biology and its uses in the field. In this chapter, we first give a general background on stem cell biology and regenerative medicine. Stem cell potency is introduced together with the hierarchy of stem cells ranging from pluripotent embryonic stem cells (ESCs) and induced pluripotent stem...

  6. Distributed redundancy and robustness in complex systems

    KAUST Repository

    Randles, Martin; Lamb, David J.; Odat, Enas M.; Taleb-Bendiab, Azzelarabe

    2011-01-01

    that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed

  7. Finding optimal interaction interface alignments between biological complexes

    KAUST Repository

    Cui, Xuefeng; Naveed, Hammad; Gao, Xin

    2015-01-01

    Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which

  8. Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

    Science.gov (United States)

    Sorokin, Anatoly; Le Novère, Nicolas; Luna, Augustin; Czauderna, Tobias; Demir, Emek; Haw, Robin; Mi, Huaiyu; Moodie, Stuart; Schreiber, Falk; Villéger, Alice

    2015-09-04

    The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

  9. Using Simple Manipulatives to Improve Student Comprehension of a Complex Biological Process: Protein Synthesis

    Science.gov (United States)

    Guzman, Karen; Bartlett, John

    2012-01-01

    Biological systems and living processes involve a complex interplay of biochemicals and macromolecular structures that can be challenging for undergraduate students to comprehend and, thus, misconceptions abound. Protein synthesis, or translation, is an example of a biological process for which students often hold many misconceptions. This article…

  10. Yeast systems biology to unravel the network of life

    DEFF Research Database (Denmark)

    Mustacchi, Roberta; Hohmann, S; Nielsen, Jens

    2006-01-01

    Systems biology focuses on obtaining a quantitative description of complete biological systems, even complete cellular function. In this way, it will be possible to perform computer-guided design of novel drugs, advanced therapies for treatment of complex diseases, and to perform in silico design....... Furthermore, it serves as an industrial workhorse for production of a wide range of chemicals and pharmaceuticals. Systems biology involves the combination of novel experimental techniques from different disciplines as well as functional genomics, bioinformatics and mathematical modelling, and hence no single...... laboratory has access to all the necessary competences. For this reason the Yeast Systems Biology Network (YSBN) has been established. YSBN will coordinate research efforts, in yeast systems biology and, through the recently obtained EU funding for a Coordination Action, it will be possible to set...

  11. Systems biology solutions for biochemical production challenges

    DEFF Research Database (Denmark)

    Hansen, Anne Sofie Lærke; Lennen, Rebecca M; Sonnenschein, Nikolaus

    2017-01-01

    There is an urgent need to significantly accelerate the development of microbial cell factories to produce fuels and chemicals from renewable feedstocks in order to facilitate the transition to a biobased society. Methods commonly used within the field of systems biology including omics...... characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects. However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity...... compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering. Here we survey recent advanced applications of systems biology methods in engineering microbial production strains...

  12. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  13. Modeling of Biological Intelligence for SCM System Optimization

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  14. Modeling of Biological Intelligence for SCM System Optimization

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

  15. A dedicated database system for handling multi-level data in systems biology

    OpenAIRE

    Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

    2014-01-01

    Background Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging...

  16. Network science of biological systems at different scales: A review

    Science.gov (United States)

    Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

    2018-03-01

    Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

  17. Optical sensors and their applications for probing biological systems

    DEFF Research Database (Denmark)

    Palanco, Marta Espina

    There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant and mammal......There is a great interest in exploring and developing new optical sensitive methodologies for probing complex biological systems. In this project we developed non-invasive and sensitive biosensor strategies for studying physiologically relevant chemical and physical properties of plant...... of a trapped cell. The project could provide new insights into the desired biosensor for future membrane-protein cell studies....

  18. Biocellion: accelerating computer simulation of multicellular biological system models.

    Science.gov (United States)

    Kang, Seunghwa; Kahan, Simon; McDermott, Jason; Flann, Nicholas; Shmulevich, Ilya

    2014-11-01

    Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming. We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies. Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. ADAM: analysis of discrete models of biological systems using computer algebra.

    Science.gov (United States)

    Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

    2011-07-20

    Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web

  20. When physics is not "just physics": complexity science invites new measurement frames for exploring the physics of cognitive and biological development.

    Science.gov (United States)

    Kelty-Stephen, Damian; Dixon, James A

    2012-01-01

    The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.

  1. Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

    Science.gov (United States)

    Chen, Bor-Sen; Wu, Chia-Chou

    2013-01-01

    Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i) system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii) system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii) system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv) systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering. PMID:24709875

  2. Systems Biology as an Integrated Platform for Bioinformatics, Systems Synthetic Biology, and Systems Metabolic Engineering

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2013-10-01

    Full Text Available Systems biology aims at achieving a system-level understanding of living organisms and applying this knowledge to various fields such as synthetic biology, metabolic engineering, and medicine. System-level understanding of living organisms can be derived from insight into: (i system structure and the mechanism of biological networks such as gene regulation, protein interactions, signaling, and metabolic pathways; (ii system dynamics of biological networks, which provides an understanding of stability, robustness, and transduction ability through system identification, and through system analysis methods; (iii system control methods at different levels of biological networks, which provide an understanding of systematic mechanisms to robustly control system states, minimize malfunctions, and provide potential therapeutic targets in disease treatment; (iv systematic design methods for the modification and construction of biological networks with desired behaviors, which provide system design principles and system simulations for synthetic biology designs and systems metabolic engineering. This review describes current developments in systems biology, systems synthetic biology, and systems metabolic engineering for engineering and biology researchers. We also discuss challenges and future prospects for systems biology and the concept of systems biology as an integrated platform for bioinformatics, systems synthetic biology, and systems metabolic engineering.

  3. Large-scale computing techniques for complex system simulations

    CERN Document Server

    Dubitzky, Werner; Schott, Bernard

    2012-01-01

    Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and

  4. Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

    Science.gov (United States)

    Sudhir, Putty-Reddy; Chen, Chung-Hsuan

    2016-03-22

    A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

  5. Systems biology solutions for biochemical production challenges.

    Science.gov (United States)

    Hansen, Anne Sofie Lærke; Lennen, Rebecca M; Sonnenschein, Nikolaus; Herrgård, Markus J

    2017-06-01

    There is an urgent need to significantly accelerate the development of microbial cell factories to produce fuels and chemicals from renewable feedstocks in order to facilitate the transition to a biobased society. Methods commonly used within the field of systems biology including omics characterization, genome-scale metabolic modeling, and adaptive laboratory evolution can be readily deployed in metabolic engineering projects. However, high performance strains usually carry tens of genetic modifications and need to operate in challenging environmental conditions. This additional complexity compared to basic science research requires pushing systems biology strategies to their limits and often spurs innovative developments that benefit fields outside metabolic engineering. Here we survey recent advanced applications of systems biology methods in engineering microbial production strains for biofuels and -chemicals. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  6. Adapting to Biology: Maintaining Container-Closure System Compatibility with the Therapeutic Biologic Revolution.

    Science.gov (United States)

    Degrazio, Dominick

    Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to the dimension of evolving therapeutic biologics. Important concerns associated with this changeover are becoming forefront, as challenges develop of varying complexity uncommon with the synthesis and production of traditional drugs. Therefore, alternative measures must be established that aim to preserve the efficacy and functionality of a biologic that might not be implemented for small molecules. Conserving protein stability is relative to perpetuating a net equilibrium of both intrinsic and extrinsic factors. Key to sustaining this balance is the ability of container-closure systems to maintain their compatibility with the ever-changing dynamics of therapeutic biologics. Failure to recognize and adjust the material properties of packaging components to support compatibility with therapeutic biologics can compromise patient safety, drug productivity, and biological stability. This review will examine the differences between small-molecule drugs and therapeutic biologics, lay a basic foundation for understanding the stability of therapeutic biologics, and demonstrate potential sources of container-closure systems' incompatibilities with therapeutic biologics at a mechanistic level. Many pharmaceutical companies are transitioning their research and development drug product pipeline from traditional small-molecule injectables to recombinantly derived therapeutic biologics. Concerns associated with this transformation are becoming prominent, as therapeutic biologics are uncharacteristic to small-molecule drugs. Maintaining the stability of a therapeutic biologic is a combination of balancing intrinsic factors and external elements within the biologic's microenvironment. An important aspect of this balance is relegated to the overall compatibility of primary, parenteral container-closure systems with therapeutic biologics

  7. Complex network synchronization of chaotic systems with delay coupling

    International Nuclear Information System (INIS)

    Theesar, S. Jeeva Sathya; Ratnavelu, K.

    2014-01-01

    The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology

  8. Complex engineering systems science meets technology

    CERN Document Server

    Minai, Ali A; Bar-Yam, Yaneer

    2006-01-01

    Every time that we take money out of an ATM, surf the internet or simply turn on a light switch, we enjoy the benefits of complex engineered systems. Systems like power grids and global communication networks are so ubiquitous in our daily lives that we usually take them for granted, only noticing them when they break down. But how do such amazing technologies and infrastructures come to be what they are? How are these systems designed? How do distributed networks work? How are they made to respond rapidly in 'real time'? And as the demands that we place on these systems become increasingly complex, are traditional systems-engineering practices still relevant? This volume examines the difficulties that arise in creating highly complex engineered systems and new approaches that are being adopted. Topics addressed range from the formal representation and classification of distributed networked systems to revolutionary engineering practices inspired by biological evolution. By bringing together the latest resear...

  9. Systems Biology of Industrial Microorganisms

    Science.gov (United States)

    Papini, Marta; Salazar, Margarita; Nielsen, Jens

    The field of industrial biotechnology is expanding rapidly as the chemical industry is looking towards more sustainable production of chemicals that can be used as fuels or building blocks for production of solvents and materials. In connection with the development of sustainable bioprocesses, it is a major challenge to design and develop efficient cell factories that can ensure cost efficient conversion of the raw material into the chemical of interest. This is achieved through metabolic engineering, where the metabolism of the cell factory is engineered such that there is an efficient conversion of sugars, the typical raw materials in the fermentation industry, into the desired product. However, engineering of cellular metabolism is often challenging due to the complex regulation that has evolved in connection with adaptation of the different microorganisms to their ecological niches. In order to map these regulatory structures and further de-regulate them, as well as identify ingenious metabolic engineering strategies that full-fill mass balance constraints, tools from systems biology can be applied. This involves both high-throughput analysis tools like transcriptome, proteome and metabolome analysis, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies. It is in fact expected that systems biology may substantially improve the process of cell factory development, and we therefore propose the term Industrial Systems Biology for how systems biology will enhance the development of industrial biotechnology for sustainable chemical production.

  10. New Insights Into the Mechanisms and Biological Roles of D-Amino Acids in Complex Eco-Systems

    Science.gov (United States)

    Aliashkevich, Alena; Alvarez, Laura; Cava, Felipe

    2018-01-01

    In the environment bacteria share their habitat with a great diversity of organisms, from microbes to humans, animals and plants. In these complex communities, the production of extracellular effectors is a common strategy to control the biodiversity by interfering with the growth and/or viability of nearby microbes. One of such effectors relies on the production and release of extracellular D-amino acids which regulate diverse cellular processes such as cell wall biogenesis, biofilm integrity, and spore germination. Non-canonical D-amino acids are mainly produced by broad spectrum racemases (Bsr). Bsr’s promiscuity allows it to generate high concentrations of D-amino acids in environments with variable compositions of L-amino acids. However, it was not clear until recent whether these molecules exhibit divergent functions. Here we review the distinctive biological roles of D-amino acids, their mechanisms of action and their modulatory properties of the biodiversity of complex eco-systems. PMID:29681896

  11. Inverse Problems in Systems Biology: A Critical Review.

    Science.gov (United States)

    Guzzi, Rodolfo; Colombo, Teresa; Paci, Paola

    2018-01-01

    Systems Biology may be assimilated to a symbiotic cyclic interplaying between the forward and inverse problems. Computational models need to be continuously refined through experiments and in turn they help us to make limited experimental resources more efficient. Every time one does an experiment we know that there will be some noise that can disrupt our measurements. Despite the noise certainly is a problem, the inverse problems already involve the inference of missing information, even if the data is entirely reliable. So the addition of a certain limited noise does not fundamentally change the situation but can be used to solve the so-called ill-posed problem, as defined by Hadamard. It can be seen as an extra source of information. Recent studies have shown that complex systems, among others the systems biology, are poorly constrained and ill-conditioned because it is difficult to use experimental data to fully estimate their parameters. For these reasons was born the concept of sloppy models, a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. Furthermore the concept of sloppy models contains also the concept of un-identifiability, because the models are characterized by many parameters that are poorly constrained by experimental data. Then a strategy needs to be designed to infer, analyze, and understand biological systems. The aim of this work is to provide a critical review to the inverse problems in systems biology defining a strategy to determine the minimal set of information needed to overcome the problems arising from dynamic biological models that generally may have many unknown, non-measurable parameters.

  12. A Statistical Physics Characterization of the Complex Systems Dynamics: Quantifying Complexity from Spatio-Temporal Interactions

    Science.gov (United States)

    Koorehdavoudi, Hana; Bogdan, Paul

    2016-06-01

    Biological systems are frequently categorized as complex systems due to their capabilities of generating spatio-temporal structures from apparent random decisions. In spite of research on analyzing biological systems, we lack a quantifiable framework for measuring their complexity. To fill this gap, in this paper, we develop a new paradigm to study a collective group of N agents moving and interacting in a three-dimensional space. Our paradigm helps to identify the spatio-temporal states of the motion of the group and their associated transition probabilities. This framework enables the estimation of the free energy landscape corresponding to the identified states. Based on the energy landscape, we quantify missing information, emergence, self-organization and complexity for a collective motion. We show that the collective motion of the group of agents evolves to reach the most probable state with relatively lowest energy level and lowest missing information compared to other possible states. Our analysis demonstrates that the natural group of animals exhibit a higher degree of emergence, self-organization and complexity over time. Consequently, this algorithm can be integrated into new frameworks to engineer collective motions to achieve certain degrees of emergence, self-organization and complexity.

  13. Mössbauer study of some biological iron complexes

    Indian Academy of Sciences (India)

    Abstract. Some biological complexes containing iron are investigated experimentally at room temperature using the Mössbauer resonance. The complexes show quadrupole doublet and Kramer's degeneracy is found to exist. The electric field gradient, difference in s-electron densities and quadrupole coupling constant ...

  14. Finding optimal interaction interface alignments between biological complexes

    KAUST Repository

    Cui, Xuefeng

    2015-06-13

    Motivation: Biological molecules perform their functions through interactions with other molecules. Structure alignment of interaction interfaces between biological complexes is an indispensable step in detecting their structural similarities, which are keys to understanding their evolutionary histories and functions. Although various structure alignment methods have been developed to successfully access the similarities of protein structures or certain types of interaction interfaces, existing alignment tools cannot directly align arbitrary types of interfaces formed by protein, DNA or RNA molecules. Specifically, they require a \\'blackbox preprocessing\\' to standardize interface types and chain identifiers. Yet their performance is limited and sometimes unsatisfactory. Results: Here we introduce a novel method, PROSTA-inter, that automatically determines and aligns interaction interfaces between two arbitrary types of complex structures. Our method uses sequentially remote fragments to search for the optimal superimposition. The optimal residue matching problem is then formulated as a maximum weighted bipartite matching problem to detect the optimal sequence order-independent alignment. Benchmark evaluation on all non-redundant protein-DNA complexes in PDB shows significant performance improvement of our method over TM-align and iAlign (with the \\'blackbox preprocessing\\'). Two case studies where our method discovers, for the first time, structural similarities between two pairs of functionally related protein-DNA complexes are presented. We further demonstrate the power of our method on detecting structural similarities between a protein-protein complex and a protein-RNA complex, which is biologically known as a protein-RNA mimicry case. © The Author 2015. Published by Oxford University Press.

  15. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  16. Distributed redundancy and robustness in complex systems

    KAUST Repository

    Randles, Martin

    2011-03-01

    The uptake and increasing prevalence of Web 2.0 applications, promoting new large-scale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an \\'open-ended\\' manner where not all states of the system are prescribed at design-time. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components\\' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy. © 2010 Elsevier Inc.

  17. Systems Biology Knowledgebase for a New Era in Biology A Genomics:GTL Report from the May 2008 Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Gregurick, S.; Fredrickson, J. K.; Stevens, R.

    2009-03-01

    Biology has entered a systems-science era with the goal to establish a predictive understanding of the mechanisms of cellular function and the interactions of biological systems with their environment and with each other. Vast amounts of data on the composition, physiology, and function of complex biological systems and their natural environments are emerging from new analytical technologies. Effectively exploiting these data requires developing a new generation of capabilities for analyzing and managing the information. By revealing the core principles and processes conserved in collective genomes across all biology and by enabling insights into the interplay between an organism's genotype and its environment, systems biology will allow scientific breakthroughs in our ability to project behaviors of natural systems and to manipulate and engineer managed systems. These breakthroughs will benefit Department of Energy (DOE) missions in energy security, climate protection, and environmental remediation.

  18. Stochastic transport processes in discrete biological systems

    CERN Document Server

    Frehland, Eckart

    1982-01-01

    These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re­ cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio­ logical 'transport systems can be complex. For example, the tr...

  19. Complex Physical, Biophysical and Econophysical Systems

    Science.gov (United States)

    Dewar, Robert L.; Detering, Frank

    1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.

  20. Third International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems

    2006-01-01

    In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains selected transcripts from presentations given at the conference. Speakers include: Chris Adami, Kenneth Arrow, Michel Baranger, Dan Braha, Timothy Buchman, Michael Caramanis, Kathleen Carley, Greg Chaitin, David Clark, Jack Cohen, Jim Collins, George Cowan, Clay Easterly, Steven Eppinger, Irving Epstein, Dan Frey, Ary Goldberger, Helen Harte, Leroy Hood, Don Ingber, Atlee Jackson,...

  1. The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

    Science.gov (United States)

    Sumarno; Ibrahim, M.; Supardi, Z. A. I.

    2018-03-01

    The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

  2. Systems Biology for Organotypic Cell Cultures

    Energy Technology Data Exchange (ETDEWEB)

    Grego, Sonia [RTI International, Research Triangle Park, NC (United States); Dougherty, Edward R. [Texas A & M Univ., College Station, TX (United States); Alexander, Francis J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Auerbach, Scott S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Berridge, Brian R. [GlaxoSmithKline, Research Triangle Park, NC (United States); Bittner, Michael L. [Translational Genomics Research Inst., Phoenix, AZ (United States); Casey, Warren [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Cooley, Philip C. [RTI International, Research Triangle Park, NC (United States); Dash, Ajit [HemoShear Therapeutics, Charlottesville, VA (United States); Ferguson, Stephen S. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Fennell, Timothy R. [RTI International, Research Triangle Park, NC (United States); Hawkins, Brian T. [RTI International, Research Triangle Park, NC (United States); Hickey, Anthony J. [RTI International, Research Triangle Park, NC (United States); Kleensang, Andre [Johns Hopkins Univ., Baltimore, MD (United States). Center for Alternatives to Animal Testing; Liebman, Michael N. [IPQ Analytics, Kennett Square, PA (United States); Martin, Florian [Phillip Morris International, Neuchatel (Switzerland); Maull, Elizabeth A. [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Paragas, Jason [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Qiao, Guilin [Defense Threat Reduction Agency, Ft. Belvoir, VA (United States); Ramaiahgari, Sreenivasa [National Inst. of Environmental Health Sciences, Research Triangle Park, NC (United States); Sumner, Susan J. [RTI International, Research Triangle Park, NC (United States); Yoon, Miyoung [The Hamner Inst. for Health Sciences, Research Triangle Park, NC (United States); ScitoVation, Research Triangle Park, NC (United States)

    2016-08-04

    Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.

  3. Nonlinear Phenomena in Complex Systems: From Nano to Macro Scale

    CERN Document Server

    Stanley, H

    2014-01-01

    Topics of complex system physics and their interdisciplinary applications to different problems in seismology, biology, economy, sociology,  energy and nanotechnology are covered in this new work from renowned experts in their fields.  In  particular, contributed papers contain original results on network science, earthquake dynamics, econophysics, sociophysics, nanoscience and biological physics. Most of the papers use interdisciplinary approaches based on statistical physics, quantum physics and other topics of complex system physics.  Papers on econophysics and sociophysics are focussed on societal aspects of physics such as, opinion dynamics, public debates and financial and economic stability. This work will be of interest to statistical physicists, economists, biologists, seismologists and all scientists working in interdisciplinary topics of complexity.

  4. Feedback dynamics and cell function: Why systems biology is called Systems Biology.

    Science.gov (United States)

    Wolkenhauer, Olaf; Mesarovic, Mihajlo

    2005-05-01

    A new paradigm, like Systems Biology, should challenge the way research has been conducted previously. This Opinion article aims to present Systems Biology, not as the application of engineering principles to biology but as a merger of systems- and control theory with molecular- and cell biology. In our view, the central dogma of Systems Biology is that it is system dynamics that gives rise to the functioning and function of cells. The concepts of feedback regulation and control of pathways and the coordination of cell function are emphasized as an important area of Systems Biology research. The hurdles and risks for this area are discussed from the perspective of dynamic pathway modelling. Most of all, the aim of this article is to promote mathematical modelling and simulation as a part of molecular- and cell biology. Systems Biology is a success if it is widely accepted that there is nothing more practical than a good theory.

  5. Agent-Based Modeling in Molecular Systems Biology.

    Science.gov (United States)

    Soheilypour, Mohammad; Mofrad, Mohammad R K

    2018-06-08

    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. © 2018 WILEY Periodicals, Inc.

  6. Atomic switch networks as complex adaptive systems

    Science.gov (United States)

    Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

    2018-03-01

    Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

  7. Systematic metabolite annotation and identification in complex biological extracts : combining robust mass spectrometry fragmentation and nuclear magnetic resonance spectroscopy

    NARCIS (Netherlands)

    Hooft, van der J.J.J.

    2012-01-01

    Detailed knowledge of the chemical content of organisms, organs, tissues, and cells is needed to fully characterize complex biological systems. The high chemical variety of compounds present in biological systems is illustrated by the presence of a large variety of compounds, ranging from apolar

  8. Investigating cholesterol metabolism and ageing using a systems biology approach.

    Science.gov (United States)

    Morgan, A E; Mooney, K M; Wilkinson, S J; Pickles, N A; Mc Auley, M T

    2017-08-01

    CVD accounted for 27 % of all deaths in the UK in 2014, and was responsible for 1·7 million hospital admissions in 2013/2014. This condition becomes increasingly prevalent with age, affecting 34·1 and 29·8 % of males and females over 75 years of age respectively in 2011. The dysregulation of cholesterol metabolism with age, often observed as a rise in LDL-cholesterol, has been associated with the pathogenesis of CVD. To compound this problem, it is estimated by 2050, 22 % of the world's population will be over 60 years of age, in culmination with a growing resistance and intolerance to pre-existing cholesterol regulating drugs such as statins. Therefore, it is apparent research into additional therapies for hypercholesterolaemia and CVD prevention is a growing necessity. However, it is also imperative to recognise this complex biological system cannot be studied using a reductionist approach; rather its biological uniqueness necessitates a more integrated methodology, such as that offered by systems biology. In this review, we firstly discuss cholesterol metabolism and how it is affected by diet and the ageing process. Next, we describe therapeutic strategies for hypercholesterolaemia, and finally how the systems biology paradigm can be utilised to investigate how ageing interacts with complex systems such as cholesterol metabolism. We conclude by emphasising the need for nutritionists to work in parallel with the systems biology community, to develop novel approaches to studying cholesterol metabolism and its interaction with ageing.

  9. Summer School Mathematical Foundations of Complex Networked Information Systems

    CERN Document Server

    Fosson, Sophie; Ravazzi, Chiara

    2015-01-01

    Introducing the reader to the mathematics beyond complex networked systems, these lecture notes investigate graph theory, graphical models, and methods from statistical physics. Complex networked systems play a fundamental role in our society, both in everyday life and in scientific research, with applications ranging from physics and biology to economics and finance. The book is self-contained, and requires only an undergraduate mathematical background.

  10. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  11. Carbon nanomaterials in biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Pu Chun Ke [Laboratory of Single-Molecule Biophysics and Polymer Physics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634 (United States); Qiao Rui [Department of Mechanical Engineering, Clemson University, Clemson, SC 29634 (United States)

    2007-09-19

    This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

  12. Carbon nanomaterials in biological systems

    International Nuclear Information System (INIS)

    Pu Chun Ke; Qiao Rui

    2007-01-01

    This paper intends to reflect, from the biophysical viewpoint, our current understanding on interfacing nanomaterials, such as carbon nanotubes and fullerenes, with biological systems. Strategies for improving the solubility, and therefore, the bioavailability of nanomaterials in aqueous solutions are summarized. In particular, the underlining mechanisms of attaching biomacromolecules (DNA, RNA, proteins) and lysophospholipids onto carbon nanotubes and gallic acids onto fullerenes are analyzed. The diffusion and the cellular delivery of RNA-coated carbon nanotubes are characterized using fluorescence microscopy. The translocation of fullerenes across cell membranes is simulated using molecular dynamics to offer new insight into the complex issue of nanotoxicity. To assess the fate of nanomaterials in the environment, the biomodification of lipid-coated carbon nanotubes by the aquatic organism Daphnia magna is discussed. The aim of this paper is to illuminate the need for adopting multidisciplinary approaches in the field study of nanomaterials in biological systems and in the environment. (topical review)

  13. A dedicated database system for handling multi-level data in systems biology.

    Science.gov (United States)

    Pornputtapong, Natapol; Wanichthanarak, Kwanjeera; Nilsson, Avlant; Nookaew, Intawat; Nielsen, Jens

    2014-01-01

    Advances in high-throughput technologies have enabled extensive generation of multi-level omics data. These data are crucial for systems biology research, though they are complex, heterogeneous, highly dynamic, incomplete and distributed among public databases. This leads to difficulties in data accessibility and often results in errors when data are merged and integrated from varied resources. Therefore, integration and management of systems biological data remain very challenging. To overcome this, we designed and developed a dedicated database system that can serve and solve the vital issues in data management and hereby facilitate data integration, modeling and analysis in systems biology within a sole database. In addition, a yeast data repository was implemented as an integrated database environment which is operated by the database system. Two applications were implemented to demonstrate extensibility and utilization of the system. Both illustrate how the user can access the database via the web query function and implemented scripts. These scripts are specific for two sample cases: 1) Detecting the pheromone pathway in protein interaction networks; and 2) Finding metabolic reactions regulated by Snf1 kinase. In this study we present the design of database system which offers an extensible environment to efficiently capture the majority of biological entities and relations encountered in systems biology. Critical functions and control processes were designed and implemented to ensure consistent, efficient, secure and reliable transactions. The two sample cases on the yeast integrated data clearly demonstrate the value of a sole database environment for systems biology research.

  14. Computational Systems Chemical Biology

    OpenAIRE

    Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

    2011-01-01

    There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007).

  15. Morphogenesis and pattern formation in biological systems experiments and models

    CERN Document Server

    Noji, Sumihare; Ueno, Naoto; Maini, Philip

    2003-01-01

    A central goal of current biology is to decode the mechanisms that underlie the processes of morphogenesis and pattern formation. Concerned with the analysis of those phenomena, this book covers a broad range of research fields, including developmental biology, molecular biology, plant morphogenesis, ecology, epidemiology, medicine, paleontology, evolutionary biology, mathematical biology, and computational biology. In Morphogenesis and Pattern Formation in Biological Systems: Experiments and Models, experimental and theoretical aspects of biology are integrated for the construction and investigation of models of complex processes. This collection of articles on the latest advances by leading researchers not only brings together work from a wide spectrum of disciplines, but also provides a stepping-stone to the creation of new areas of discovery.

  16. Carbon-13 NMR spectroscopy of biological systems

    CERN Document Server

    Beckmann, Nicolau

    1995-01-01

    This book is intended to provide an in-depth understanding of 13C NMR as a tool in biological research. 13C NMR has provided unique information concerning complex biological systems, from proteins and nucleic acids to animals and humans. The subjects addressed include multidimensional heteronuclear techniques for structural studies of molecules in the liquid and solid states, the investigation of interactions in model membranes, the elucidation of metabolic pathwaysin vitro and in vivo on animals, and noninvasive metabolic studies performed on humans. The book is a unique mix of NMR methods and biological applications which makes it a convenient reference for those interested in research in this interdisciplinary area of physics, chemistry, biology, and medicine.Key Features* An interdisciplinary text with emphasis on both 13C NMR methodology and the relevant biological and biomedical issues* State-of-the-art 13C NMR techniques are described; Whenever possible, their advantages over other approaches are empha...

  17. From systems biology to systems biomedicine.

    Science.gov (United States)

    Antony, Paul M A; Balling, Rudi; Vlassis, Nikos

    2012-08-01

    Systems Biology is about combining theory, technology, and targeted experiments in a way that drives not only data accumulation but knowledge as well. The challenge in Systems Biomedicine is to furthermore translate mechanistic insights in biological systems to clinical application, with the central aim of improving patients' quality of life. The challenge is to find theoretically well-chosen models for the contextually correct and intelligible representation of multi-scale biological systems. In this review, we discuss the current state of Systems Biology, highlight the emergence of Systems Biomedicine, and highlight some of the topics and views that we think are important for the efficient application of Systems Theory in Biomedicine. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

    Science.gov (United States)

    Pathak, Rajesh Kumar; Gupta, Sanjay Mohan; Gaur, Vikram Singh; Pandey, Dinesh

    2015-01-01

    Abstract In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes. PMID:26484978

  19. Energy Flows in Low-Entropy Complex Systems

    Directory of Open Access Journals (Sweden)

    Eric J. Chaisson

    2015-12-01

    Full Text Available Nature’s many complex systems—physical, biological, and cultural—are islands of low-entropy order within increasingly disordered seas of surrounding, high-entropy chaos. Energy is a principal facilitator of the rising complexity of all such systems in the expanding Universe, including galaxies, stars, planets, life, society, and machines. A large amount of empirical evidence—relating neither entropy nor information, rather energy—suggests that an underlying simplicity guides the emergence and growth of complexity among many known, highly varied systems in the 14-billion-year-old Universe, from big bang to humankind. Energy flows are as centrally important to life and society as they are to stars and galaxies. In particular, the quantity energy rate density—the rate of energy flow per unit mass—can be used to explicate in a consistent, uniform, and unifying way a huge collection of diverse complex systems observed throughout Nature. Operationally, those systems able to utilize optimal amounts of energy tend to survive and those that cannot are non-randomly eliminated.

  20. Systems Biology-Based Platforms to Accelerate Research of Emerging Infectious Diseases.

    Science.gov (United States)

    Oh, Soo Jin; Choi, Young Ki; Shin, Ok Sarah

    2018-03-01

    Emerging infectious diseases (EIDs) pose a major threat to public health and security. Given the dynamic nature and significant impact of EIDs, the most effective way to prevent and protect against them is to develop vaccines in advance. Systems biology approaches provide an integrative way to understand the complex immune response to pathogens. They can lead to a greater understanding of EID pathogenesis and facilitate the evaluation of newly developed vaccine-induced immunity in a timely manner. In recent years, advances in high throughput technologies have enabled researchers to successfully apply systems biology methods to analyze immune responses to a variety of pathogens and vaccines. Despite recent advances, computational and biological challenges impede wider application of systems biology approaches. This review highlights recent advances in the fields of systems immunology and vaccinology, and presents ways that systems biology-based platforms can be applied to accelerate a deeper understanding of the molecular mechanisms of immunity against EIDs. © Copyright: Yonsei University College of Medicine 2018.

  1. Systems Biology-an interdisciplinary approach.

    Science.gov (United States)

    Friboulet, Alain; Thomas, Daniel

    2005-06-15

    System-level approaches in biology are not new but foundations of "Systems Biology" are achieved only now at the beginning of the 21st century [Kitano, H., 2001. Foundations of Systems Biology. MIT Press, Cambridge, MA]. The renewed interest for a system-level approach is linked to the progress in collecting experimental data and to the limits of the "reductionist" approach. System-level understanding of native biological and pathological systems is needed to provide potential therapeutic targets. Examples of interdisciplinary approach in Systems Biology are described in U.S., Japan and Europe. Robustness in biology, metabolic engineering and idiotypic networks are discussed in the framework of Systems Biology.

  2. Synthesis, Physical Characterization and Biological Activity of Some Schiff Base Complexes

    Directory of Open Access Journals (Sweden)

    R. Rajavel

    2008-01-01

    Full Text Available Structural modification of organic molecule has considerable biological relevance. Further, coordination of a biomolecules to the metal ions significantly alters the effectiveness of the biomolecules. In view of the antimicrobial activity ligand [bis-(2-aminobenzaldehyde] malonoyl dihydrazone], metal complexes with Cu(II, Ni(II, Zn(II and oxovanadium(IV have been synthesized and found to be potential antimicrobial agents. An attempt is also made to correlate the biological activities with geometry of the complexes. The complexes have been characterized by elemental analysis, molar conductance, spectra and cyclicvoltammetric measurements. The structural assessment of the complexes has been carried out based on electronic, infrared and molar conductivity values.

  3. Physics and biology

    International Nuclear Information System (INIS)

    Frauenfelder, H.

    1988-01-01

    The author points out that the coupling between physics and biology is becoming closer as time goes on. He tries to show that physical studies on biological systems not only yield insight into biology but also provide results of interest to physics. Biological systems are extremly complex system. Ideally one would like to understand the behavior of such systems in terms of the behavior of its constituent atoms. Since in small organisms this may be 10 20 atoms, it is clear these are not simple many-body systems. He reviews the basic elements of cells and then considers the broader questions of structure, complexity, and function, which must be looked at on levels from the cell to the organism. Despite the vast amount of observational material already in existence, biophysics and biological physics are only at a beginning. We can expect that physics will continue to interact strongly with biology. Actually, the connection also includes chemistry and mathematics. New tools that become available in physics will continue to be applied to biological problems. We can expect that the flow of information will not be one way; biological systems will provide new information on many old and new parts of physics, from reaction theory and transport phenomena to complexity, cooperativity, and nonlinear processes

  4. Genome Scale Modeling in Systems Biology: Algorithms and Resources

    Science.gov (United States)

    Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

    2014-01-01

    In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

  5. Complex Time-Delay Systems Theory and Applications

    CERN Document Server

    Atay, Fatihcan M

    2010-01-01

    Time delays in dynamical systems arise as an inevitable consequence of finite speeds of information transmission. Realistic models increasingly demand the inclusion of delays in order to properly understand, analyze, design, and control real-life systems. The goal of this book is to present the state-of-the-art in research on time-delay dynamics in the framework of complex systems and networks. While the mathematical theory of delay equations is quite mature, its application to the particular problems of complex systems and complexity is a newly emerging field, and the present volume aims to play a pioneering role in this perspective. The chapters in this volume are authored by renowned experts and cover both theory and applications in a wide range of fields, with examples extending from neuroscience and biology to laser physics and vehicle traffic. Furthermore, all chapters include sufficient introductory material and extensive bibliographies, making the book a self-contained reference for both students and ...

  6. From precision polymers to complex materials and systems

    NARCIS (Netherlands)

    Lutz, J.F.; Lehn, J.M.; Meijer, E.W.; Matyjaszewski, K.

    2016-01-01

    Complex chemical systems, such as living biological matter, are highly organized structures based on discrete molecules in constant dynamic interactions. These natural materials can evolve and adapt to their environment. By contrast, man-made materials exhibit simpler properties. In this Review, we

  7. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

    Directory of Open Access Journals (Sweden)

    Ina Aretz

    2016-04-01

    Full Text Available Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

  8. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology.

    Science.gov (United States)

    Aretz, Ina; Meierhofer, David

    2016-04-27

    Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

  9. Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

    International Nuclear Information System (INIS)

    Fang Jinqing

    1995-03-01

    Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.)

  10. Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

    Energy Technology Data Exchange (ETDEWEB)

    Jinqing, Fang [Academia Sinica, Beijing, BJ (China). Inst. of Atomic Energy

    1995-03-01

    Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.).

  11. Evolving a lingua franca and associated software infrastructure for computational systems biology: the Systems Biology Markup Language (SBML) project.

    Science.gov (United States)

    Hucka, M; Finney, A; Bornstein, B J; Keating, S M; Shapiro, B E; Matthews, J; Kovitz, B L; Schilstra, M J; Funahashi, A; Doyle, J C; Kitano, H

    2004-06-01

    Biologists are increasingly recognising that computational modelling is crucial for making sense of the vast quantities of complex experimental data that are now being collected. The systems biology field needs agreed-upon information standards if models are to be shared, evaluated and developed cooperatively. Over the last four years, our team has been developing the Systems Biology Markup Language (SBML) in collaboration with an international community of modellers and software developers. SBML has become a de facto standard format for representing formal, quantitative and qualitative models at the level of biochemical reactions and regulatory networks. In this article, we summarise the current and upcoming versions of SBML and our efforts at developing software infrastructure for supporting and broadening its use. We also provide a brief overview of the many SBML-compatible software tools available today.

  12. Attraction Basins as Gauges of Robustness against Boundary Conditions in Biological Complex Systems

    Science.gov (United States)

    Demongeot, Jacques; Goles, Eric; Morvan, Michel; Noual, Mathilde; Sené, Sylvain

    2010-01-01

    One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally. PMID:20700525

  13. Attraction basins as gauges of robustness against boundary conditions in biological complex systems.

    Directory of Open Access Journals (Sweden)

    Jacques Demongeot

    Full Text Available One fundamental concept in the context of biological systems on which researches have flourished in the past decade is that of the apparent robustness of these systems, i.e., their ability to resist to perturbations or constraints induced by external or boundary elements such as electromagnetic fields acting on neural networks, micro-RNAs acting on genetic networks and even hormone flows acting both on neural and genetic networks. Recent studies have shown the importance of addressing the question of the environmental robustness of biological networks such as neural and genetic networks. In some cases, external regulatory elements can be given a relevant formal representation by assimilating them to or modeling them by boundary conditions. This article presents a generic mathematical approach to understand the influence of boundary elements on the dynamics of regulation networks, considering their attraction basins as gauges of their robustness. The application of this method on a real genetic regulation network will point out a mathematical explanation of a biological phenomenon which has only been observed experimentally until now, namely the necessity of the presence of gibberellin for the flower of the plant Arabidopsis thaliana to develop normally.

  14. Simulation and Analysis of Complex Biological Processes: an Organisation Modelling Perspective

    NARCIS (Netherlands)

    Bosse, T.; Jonker, C.M.; Treur, J.

    2005-01-01

    This paper explores how the dynamics of complex biological processes can be modelled and simulated as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics

  15. An online model composition tool for system biology models.

    Science.gov (United States)

    Coskun, Sarp A; Cicek, A Ercument; Lai, Nicola; Dash, Ranjan K; Ozsoyoglu, Z Meral; Ozsoyoglu, Gultekin

    2013-09-05

    There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user's input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well.

  16. Integrative systems and synthetic biology of cell-matrix adhesion sites.

    Science.gov (United States)

    Zamir, Eli

    2016-09-02

    The complexity of cell-matrix adhesion convolves its roles in the development and functioning of multicellular organisms and their evolutionary tinkering. Cell-matrix adhesion is mediated by sites along the plasma membrane that anchor the actin cytoskeleton to the matrix via a large number of proteins, collectively called the integrin adhesome. Fundamental challenges for understanding how cell-matrix adhesion sites assemble and function arise from their multi-functionality, rapid dynamics, large number of components and molecular diversity. Systems biology faces these challenges in its strive to understand how the integrin adhesome gives rise to functional adhesion sites. Synthetic biology enables engineering intracellular modules and circuits with properties of interest. In this review I discuss some of the fundamental questions in systems biology of cell-matrix adhesion and how synthetic biology can help addressing them.

  17. Statistical physics of complex systems a concise introduction

    CERN Document Server

    Bertin, Eric

    2016-01-01

    This course-tested primer provides graduate students and non-specialists with a basic understanding of the concepts and methods of statistical physics and demonstrates their wide range of applications to interdisciplinary topics in the field of complex system sciences, including selected aspects of theoretical modeling in biology and the social sciences. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting units, and on the other to predict the macroscopic, collective behavior of the system considered from the perspective of the microscopic laws governing the dynamics of the individual entities. These two goals are essentially also shared by what is now called 'complex systems science', and as such, systems studied in the framework of statistical physics may be considered to be among the simplest examples of complex systems – while also offering a rather well developed mathematical treatment. The second ...

  18. Multiway modeling and analysis in stem cell systems biology

    Directory of Open Access Journals (Sweden)

    Vandenberg Scott L

    2008-07-01

    Full Text Available Abstract Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.. A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a

  19. Biological conversion system

    Science.gov (United States)

    Scott, C.D.

    A system for bioconversion of organic material comprises a primary bioreactor column wherein a biological active agent (zymomonas mobilis) converts the organic material (sugar) to a product (alcohol), a rejuvenator column wherein the biological activity of said biological active agent is enhanced, and means for circulating said biological active agent between said primary bioreactor column and said rejuvenator column.

  20. “Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

    Directory of Open Access Journals (Sweden)

    Nora A. Gutierrez Najera

    2017-05-01

    Full Text Available The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome. In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention that in turn are programmed by genes and influenced by environmental processes (epigenetic. Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity or more than one disease (multimorbidity adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics. The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed.

  1. Complex network problems in physics, computer science and biology

    Science.gov (United States)

    Cojocaru, Radu Ionut

    There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe

  2. What does systems biology mean for drug development?

    Science.gov (United States)

    Schrattenholz, André; Soskić, Vukić

    2008-01-01

    The complexity and flexibility of cellular architectures is increasingly recognized by impressive progress on the side of molecular analytics, i.e. proteomics, genomics and metabolomics. One of the messages from systems biology is that the number of molecular species in cellular networks is orders of magnitude bigger than anticipated by genomic analysis, in particular by fast posttranslational modifications of proteins. The requirements to manage external signals, integrate spatiotemporal signal transduction inside an organism and at the same time optimizing networks of biochemical and chemical reactions result in chemically extremely fine tuned molecular entities. Chemical side reactions of enzymatic activity, like e.g. random oxidative damage of proteins by free radicals during aging constantly introduce epigenetic alterations of protein targets. These events gradually and on an individual stochastic scale, keep modifying activities of these targets, and their affinities and selectivities towards biological and pharmacological ligands. One further message is that many of the key reactions in living systems are essentially based on interactions of low affinities and even low selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. So, in complex disorders like cancer or neurodegenerative diseases, which are rooted in relatively subtle and multimodal dysfunction of important physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which still dominate the pharmaceutical industry increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade and the treatment of "complex diseases" remains a most pressing medical need. Currently a change of paradigm can be observed with

  3. Can We Advance Macroscopic Quantum Systems Outside the Framework of Complex Decoherence Theory?

    Science.gov (United States)

    Brezinski, Mark E; Rupnick, Maria

    2016-01-01

    Macroscopic quantum systems (MQS) are macroscopic systems driven by quantum rather than classical mechanics, a long studied area with minimal success till recently. Harnessing the benefits of quantum mechanics on a macroscopic level would revolutionize fields ranging from telecommunication to biology, the latter focused on here for reasons discussed. Contrary to misconceptions, there are no known physical laws that prevent the development of MQS. Instead, they are generally believed universally lost in complex systems from environmental entanglements (decoherence). But we argue success is achievable MQS with decoherence compensation developed, naturally or artificially, from top-down rather current reductionist approaches. This paper advances the MQS field by a complex systems approach to decoherence. First, why complex system decoherence approaches (top-down) are needed is discussed. Specifically, complex adaptive systems (CAS) are not amenable to reductionist models (and their master equations) because of emergent behaviour, approximation failures, not accounting for quantum compensatory mechanisms, ignoring path integrals, and the subentity problem. In addition, since MQS must exist within the context of the classical world, where rapid decoherence and prolonged coherence are both needed. Nature has already demonstrated this for quantum subsystems such as photosynthesis and magnetoreception. Second, we perform a preliminary study that illustrates a top-down approach to potential MQS. In summary, reductionist arguments against MQS are not justifiable. It is more likely they are not easily detectable in large intact classical systems or have been destroyed by reductionist experimental set-ups. This complex systems decoherence approach, using top down investigations, is critical to paradigm shifts in MQS research both in biological and non-biological systems. PMID:29200743

  4. The Promise of Systems Biology Approaches for Revealing Host Pathogen Interactions in Malaria

    Directory of Open Access Journals (Sweden)

    Meghan Zuck

    2017-11-01

    Full Text Available Despite global eradication efforts over the past century, malaria remains a devastating public health burden, causing almost half a million deaths annually (WHO, 2016. A detailed understanding of the mechanisms that control malaria infection has been hindered by technical challenges of studying a complex parasite life cycle in multiple hosts. While many interventions targeting the parasite have been implemented, the complex biology of Plasmodium poses a major challenge, and must be addressed to enable eradication. New approaches for elucidating key host-parasite interactions, and predicting how the parasite will respond in a variety of biological settings, could dramatically enhance the efficacy and longevity of intervention strategies. The field of systems biology has developed methodologies and principles that are well poised to meet these challenges. In this review, we focus our attention on the Liver Stage of the Plasmodium lifecycle and issue a “call to arms” for using systems biology approaches to forge a new era in malaria research. These approaches will reveal insights into the complex interplay between host and pathogen, and could ultimately lead to novel intervention strategies that contribute to malaria eradication.

  5. Interacting complex systems: Theory and application to real-world situations

    Science.gov (United States)

    Piccinini, Nicola

    The interest in complex systems has increased exponentially during the past years because it was found helpful in addressing many of today's challenges. The study of the brain, biology, earthquakes, markets and social sciences are only a few examples of the fields that have benefited from the investigation of complex systems. Internet, the increased mobility of people and the raising energy demand are among the factors that brought in contact complex systems that were isolated till a few years ago. A theory for the interaction between complex systems is becoming more and more urgent to help mankind in this transition. The present work builds upon the most recent results in this field by solving a theoretical problem that prevented previous work to be applied to important complex systems, like the brain. It also shows preliminary laboratory results of perturbation of in vitro neural networks that were done to test the theory. Finally, it gives a preview of the studies that are being done to create a theory that is even closer to the interaction between real complex systems.

  6. Real-Time Tracking the Synthesis and Degradation of Albumin in Complex Biological Systems with a near-Infrared Fluorescent Probe.

    Science.gov (United States)

    Jin, Qiang; Feng, Lei; Zhang, Shui-Jun; Wang, Dan-Dan; Wang, Fang-Jun; Zhang, Yi; Cui, Jing-Nan; Guo, Wen-Zhi; Ge, Guang-Bo; Yang, Ling

    2017-09-19

    In this study, a novel fluorescent detection system for biological sensing of human albumin (HA) was developed on the basis of the pseudoesterase activity and substrate preference of HA. The designed near-infrared (NIR) fluorescent probe (DDAP) could be effectively hydrolyzed by HA, accompanied by significant changes in both color and fluorescence spectrum. The sensing mechanism was fully investigated by fluorescence spectroscopy, NMR, and mass spectra. DDAP exhibited excellent selectivity and sensitivity toward HA over a variety of human plasma proteins, hydrolases, and abundant biomolecules found in human body. The probe has been successfully applied to measure native HA in diluted plasma samples and the secreted HA in the hepatocyte culture supernatant. DDAP has also been used for fluorescence imaging of HA reabsorption in living renal cells, and the results show that the probe exhibits good cell permeability, low cytotoxicity and high imaging resolution. Furthermore, DDAP has been successfully used for real-time tracking the uptaking and degradation of albumin in ex vivo mouse kidney models for the first time. All these results clearly demonstrated that DDAP-based assay held great promise for real-time sensing and tracking HA in complex biological systems, which would be very useful for basic researches and clinical diagnosis of HA-associated diseases.

  7. Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

    Science.gov (United States)

    Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

    2016-10-20

    The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

  8. Boolean modeling in systems biology: an overview of methodology and applications

    International Nuclear Information System (INIS)

    Wang, Rui-Sheng; Albert, Réka; Saadatpour, Assieh

    2012-01-01

    Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology. (paper)

  9. Systems biology: the reincarnation of systems theory applied in biology?

    Science.gov (United States)

    Wolkenhauer, O

    2001-09-01

    With the availability of quantitative data on the transcriptome and proteome level, there is an increasing interest in formal mathematical models of gene expression and regulation. International conferences, research institutes and research groups concerned with systems biology have appeared in recent years and systems theory, the study of organisation and behaviour per se, is indeed a natural conceptual framework for such a task. This is, however, not the first time that systems theory has been applied in modelling cellular processes. Notably in the 1960s systems theory and biology enjoyed considerable interest among eminent scientists, mathematicians and engineers. Why did these early attempts vanish from research agendas? Here we shall review the domain of systems theory, its application to biology and the lessons that can be learned from the work of Robert Rosen. Rosen emerged from the early developments in the 1960s as a main critic but also developed a new alternative perspective to living systems, a concept that deserves a fresh look in the post-genome era of bioinformatics.

  10. Approaching complexity by stochastic methods: From biological systems to turbulence

    Energy Technology Data Exchange (ETDEWEB)

    Friedrich, Rudolf [Institute for Theoretical Physics, University of Muenster, D-48149 Muenster (Germany); Peinke, Joachim [Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Sahimi, Muhammad [Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089-1211 (United States); Reza Rahimi Tabar, M., E-mail: mohammed.r.rahimi.tabar@uni-oldenburg.de [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Fachbereich Physik, Universitaet Osnabrueck, Barbarastrasse 7, 49076 Osnabrueck (Germany)

    2011-09-15

    This review addresses a central question in the field of complex systems: given a fluctuating (in time or space), sequentially measured set of experimental data, how should one analyze the data, assess their underlying trends, and discover the characteristics of the fluctuations that generate the experimental traces? In recent years, significant progress has been made in addressing this question for a class of stochastic processes that can be modeled by Langevin equations, including additive as well as multiplicative fluctuations or noise. Important results have emerged from the analysis of temporal data for such diverse fields as neuroscience, cardiology, finance, economy, surface science, turbulence, seismic time series and epileptic brain dynamics, to name but a few. Furthermore, it has been recognized that a similar approach can be applied to the data that depend on a length scale, such as velocity increments in fully developed turbulent flow, or height increments that characterize rough surfaces. A basic ingredient of the approach to the analysis of fluctuating data is the presence of a Markovian property, which can be detected in real systems above a certain time or length scale. This scale is referred to as the Markov-Einstein (ME) scale, and has turned out to be a useful characteristic of complex systems. We provide a review of the operational methods that have been developed for analyzing stochastic data in time and scale. We address in detail the following issues: (i) reconstruction of stochastic evolution equations from data in terms of the Langevin equations or the corresponding Fokker-Planck equations and (ii) intermittency, cascades, and multiscale correlation functions.

  11. Approaching complexity by stochastic methods: From biological systems to turbulence

    International Nuclear Information System (INIS)

    Friedrich, Rudolf; Peinke, Joachim; Sahimi, Muhammad; Reza Rahimi Tabar, M.

    2011-01-01

    This review addresses a central question in the field of complex systems: given a fluctuating (in time or space), sequentially measured set of experimental data, how should one analyze the data, assess their underlying trends, and discover the characteristics of the fluctuations that generate the experimental traces? In recent years, significant progress has been made in addressing this question for a class of stochastic processes that can be modeled by Langevin equations, including additive as well as multiplicative fluctuations or noise. Important results have emerged from the analysis of temporal data for such diverse fields as neuroscience, cardiology, finance, economy, surface science, turbulence, seismic time series and epileptic brain dynamics, to name but a few. Furthermore, it has been recognized that a similar approach can be applied to the data that depend on a length scale, such as velocity increments in fully developed turbulent flow, or height increments that characterize rough surfaces. A basic ingredient of the approach to the analysis of fluctuating data is the presence of a Markovian property, which can be detected in real systems above a certain time or length scale. This scale is referred to as the Markov-Einstein (ME) scale, and has turned out to be a useful characteristic of complex systems. We provide a review of the operational methods that have been developed for analyzing stochastic data in time and scale. We address in detail the following issues: (i) reconstruction of stochastic evolution equations from data in terms of the Langevin equations or the corresponding Fokker-Planck equations and (ii) intermittency, cascades, and multiscale correlation functions.

  12. Newton, Laplace, and The Epistemology of Systems Biology

    Science.gov (United States)

    Bittner, Michael L.; Dougherty, Edward R.

    2012-01-01

    For science, theoretical or applied, to significantly advance, researchers must use the most appropriate mathematical methods. A century and a half elapsed between Newton’s development of the calculus and Laplace’s development of celestial mechanics. One cannot imagine the latter without the former. Today, more than three-quarters of a century has elapsed since the birth of stochastic systems theory. This article provides a perspective on the utilization of systems theory as the proper vehicle for the development of systems biology and its application to complex regulatory diseases such as cancer. PMID:23170064

  13. The semiotics of control and modeling relations in complex systems.

    Science.gov (United States)

    Joslyn, C

    2001-01-01

    We provide a conceptual analysis of ideas and principles from the systems theory discourse which underlie Pattee's semantic or semiotic closure, which is itself foundational for a school of theoretical biology derived from systems theory and cybernetics, and is now being related to biological semiotics and explicated in the relational biological school of Rashevsky and Rosen. Atomic control systems and models are described as the canonical forms of semiotic organization, sharing measurement relations, but differing topologically in that control systems are circularly and models linearly related to their environments. Computation in control systems is introduced, motivating hierarchical decomposition, hybrid modeling and control systems, and anticipatory or model-based control. The semiotic relations in complex control systems are described in terms of relational constraints, and rules and laws are distinguished as contingent and necessary functional entailments, respectively. Finally, selection as a meta-level of constraint is introduced as the necessary condition for semantic relations in control systems and models.

  14. Evolution of complexity in RNA-like replicator systems

    Directory of Open Access Journals (Sweden)

    Hogeweg Paulien

    2008-03-01

    Full Text Available Abstract Background The evolution of complexity is among the most important questions in biology. The evolution of complexity is often observed as the increase of genetic information or that of the organizational complexity of a system. It is well recognized that the formation of biological organization – be it of molecules or ecosystems – is ultimately instructed by the genetic information, whereas it is also true that the genetic information is functional only in the context of the organization. Therefore, to obtain a more complete picture of the evolution of complexity, we must study the evolution of both information and organization. Results Here we investigate the evolution of complexity in a simulated RNA-like replicator system. The simplicity of the system allows us to explicitly model the genotype-phenotype-interaction mapping of individual replicators, whereby we avoid preconceiving the functionality of genotypes (information or the ecological organization of replicators in the model. In particular, the model assumes that interactions among replicators – to replicate or to be replicated – depend on their secondary structures and base-pair matching. The results showed that a population of replicators, originally consisting of one genotype, evolves to form a complex ecosystem of up to four species. During this diversification, the species evolve through acquiring unique genotypes with distinct ecological functionality. The analysis of this diversification reveals that parasitic replicators, which have been thought to destabilize the replicator's diversity, actually promote the evolution of diversity through generating a novel "niche" for catalytic replicators. This also makes the current replicator system extremely stable upon the evolution of parasites. The results also show that the stability of the system crucially depends on the spatial pattern formation of replicators. Finally, the evolutionary dynamics is shown to

  15. Fostering synergy between cell biology and systems biology.

    Science.gov (United States)

    Eddy, James A; Funk, Cory C; Price, Nathan D

    2015-08-01

    In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  16. Systems thinking and complexity: considerations for health promoting schools.

    Science.gov (United States)

    Rosas, Scott R

    2017-04-01

    The health promoting schools concept reflects a comprehensive and integrated philosophy to improving student and personnel health and well-being. Conceptualized as a configuration of interacting, interdependent parts connected through a web of relationships that form a whole greater than the sum of its parts, school health promotion initiatives often target several levels (e.g. individual, professional, procedural and policy) simultaneously. Health promoting initiatives, such as those operationalized under the whole school approach, include several interconnected components that are coordinated to improve health outcomes in complex settings. These complex systems interventions are embedded in intricate arrangements of physical, biological, ecological, social, political and organizational relationships. Systems thinking and characteristics of complex adaptive systems are introduced in this article to provide a perspective that emphasizes the patterns of inter-relationships associated with the nonlinear, dynamic and adaptive nature of complex hierarchical systems. Four systems thinking areas: knowledge, networks, models and organizing are explored as a means to further manage the complex nature of the development and sustainability of health promoting schools. Applying systems thinking and insights about complex adaptive systems can illuminate how to address challenges found in settings with both complicated (i.e. multi-level and multisite) and complex aspects (i.e. synergistic processes and emergent outcomes). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. Complex systems dynamics in aging: new evidence, continuing questions.

    Science.gov (United States)

    Cohen, Alan A

    2016-02-01

    There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.

  18. A systems biology approach to studying Tai Chi, physiological complexity and healthy aging: design and rationale of a pragmatic randomized controlled trial.

    Science.gov (United States)

    Wayne, Peter M; Manor, Brad; Novak, Vera; Costa, Madelena D; Hausdorff, Jeffrey M; Goldberger, Ary L; Ahn, Andrew C; Yeh, Gloria Y; Peng, C-K; Lough, Matthew; Davis, Roger B; Quilty, Mary T; Lipsitz, Lewis A

    2013-01-01

    Aging is typically associated with progressive multi-system impairment that leads to decreased physical and cognitive function and reduced adaptability to stress. Due to its capacity to characterize complex dynamics within and between physiological systems, the emerging field of complex systems biology and its array of quantitative tools show great promise for improving our understanding of aging, monitoring senescence, and providing biomarkers for evaluating novel interventions, including promising mind-body exercises, that treat age-related disease and promote healthy aging. An ongoing, two-arm randomized clinical trial is evaluating the potential of Tai Chi mind-body exercise to attenuate age-related loss of complexity. A total of 60 Tai Chi-naïve healthy older adults (aged 50-79) are being randomized to either six months of Tai Chi training (n=30), or to a waitlist control receiving unaltered usual medical care (n=30). Our primary outcomes are complexity-based measures of heart rate, standing postural sway and gait stride interval dynamics assessed at 3 and 6months. Multiscale entropy and detrended fluctuation analysis are used as entropy- and fractal-based measures of complexity, respectively. Secondary outcomes include measures of physical and psychological function and tests of physiological adaptability also assessed at 3 and 6months. Results of this study may lead to novel biomarkers that help us monitor and understand the physiological processes of aging and explore the potential benefits of Tai Chi and related mind-body exercises for healthy aging. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Ionic interactions in biological and physical systems: a variational treatment.

    Science.gov (United States)

    Eisenberg, Bob

    2013-01-01

    Chemistry is about chemical reactions. Chemistry is about electrons changing their configurations as atoms and molecules react. Chemistry has for more than a century studied reactions as if they occurred in ideal conditions of infinitely dilute solutions. But most reactions occur in salt solutions that are not ideal. In those solutions everything (charged) interacts with everything else (charged) through the electric field, which is short and long range extending to the boundaries of the system. Mathematics has recently been developed to deal with interacting systems of this sort. The variational theory of complex fluids has spawned the theory of liquid crystals (or vice versa). In my view, ionic solutions should be viewed as complex fluids, particularly in the biological and engineering context. In both biology and electrochemistry ionic solutions are mixtures highly concentrated (to approximately 10 M) where they are most important, near electrodes, nucleic ids, proteins, active sites of enzymes, and ionic channels. Ca2+ is always involved in biological solutions because the concentration (really free energy per mole) of Ca2+ in a particular location is the signal that controls many biological functions. Such interacting systems are not simple fluids, and it is no wonder that analysis of interactions, such as the Hofmeister series, rooted in that tradition has not succeeded as one would hope. Here, we present a variational treatment of ard spheres in a frictional dielectric with the hope that such a treatment of an lectrolyte as a complex fluid will be productive. The theory automatically extends to spatially nonuniform boundary conditions and the nonequilibrium systems and flows they produce. The theory is unavoidably self-consistent since differential equations are derived (not assumed) from models of (Helmholtz free) nergy and dissipation of the electrolyte. The origin of the Hofmeister series is (in my view) an inverse problem that becomes well posed when

  20. cellPACK: a virtual mesoscope to model and visualize structural systems biology.

    Science.gov (United States)

    Johnson, Graham T; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S; Sanner, Michel F; Olson, Arthur J

    2015-01-01

    cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

  1. Systems Biology for Mapping Genotype-Phenotype Relations in Yeast

    KAUST Repository

    Nielsen, Jens

    2016-01-25

    The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals and materials. Through metabolic engineering of this yeast a number of novel new industrial processes have been developed over the last 10 years. Besides its wide industrial use, S. cerevisiae serves as an eukaryal model organism, and many systems biology tools have therefore been developed for this organism. Among these genome-scale metabolic models have shown to be most successful as they easy integrate with omics data and at the same time have been shown to have excellent predictive power. Despite our extensive knowledge of yeast metabolism and its regulation we are still facing challenges when we want to engineer complex traits, such as improved tolerance to toxic metabolites like butanol and elevated temperatures or when we want to engineer the highly complex protein secretory pathway. In this presentation it will be demonstrated how we can combine directed evolution with systems biology analysis to identify novel targets for rational design-build-test of yeast strains that have improved phenotypic properties. In this lecture an overview of systems biology of yeast will be presented together with examples of how genome-scale metabolic modeling can be used for prediction of cellular growth at different conditions. Examples will also be given on how adaptive laboratory evolution can be used for identifying targets for improving tolerance towards butanol, increased temperature and low pH and for improving secretion of heterologous proteins.

  2. Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

    Science.gov (United States)

    Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

    2015-09-04

    The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

  3. Linking structural features of protein complexes and biological function.

    Science.gov (United States)

    Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

    2015-09-01

    Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

  4. Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations

    KAUST Repository

    Gomez-Cabrero, David; Tegner, Jesper

    2017-01-01

    The rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity

  5. Assessing the Possibility of Biological Complexity on Other Worlds, with an Estimate of the Occurrence of Complex Life in the Milky Way Galaxy

    Directory of Open Access Journals (Sweden)

    Louis N. Irwin

    2014-05-01

    Full Text Available Rational speculation about biological evolution on other worlds is one of the outstanding challenges in astrobiology. With the growing confirmation that multiplanetary systems abound in the universe, the prospect that life occurs redundantly throughout the cosmos is gaining widespread support. Given the enormous number of possible abodes for life likely to be discovered on an ongoing basis, the prospect that life could have evolved into complex, macro-organismic communities in at least some cases merits consideration. Toward that end, we here propose a Biological Complexity Index (BCI, designed to provide a quantitative estimate of the relative probability that complex, macro-organismic life forms could have emerged on other worlds. The BCI ranks planets and moons by basic, first-order characteristics detectable with available technology. By our calculation only 11 (~1.7% of the extrasolar planets known to date have a BCI above that of Europa; but by extrapolation, the total of such planets could exceed 100 million in our galaxy alone. This is the first quantitative assessment of the plausibility of complex life throughout the universe based on empirical data. It supports the view that the evolution of complex life on other worlds is rare in frequency but large in absolute number.

  6. Information and self-organization a macroscopic approach to complex systems

    CERN Document Server

    Haken, Hermann

    1988-01-01

    Complex systems are ubiquitous, and practically all branches of science ranging from physics through chemistry and biology to economics and sociology have to deal with them. In this book we wish to present concepts and methods for dealing with complex systems from a unifying point of view. Therefore it may be of inter­ est to graduate students, professors and research workers who are concerned with theoretical work in the above-mentioned fields. The basic idea for our unified ap­ proach sterns from that of synergetics. In order to find unifying principles we shall focus our attention on those situations where a complex system changes its macroscopic behavior qualitatively, or in other words, where it changes its macroscopic spatial, temporal or functional structure. Until now, the theory of synergetics has usually begun with a microscopic or mesoscopic description of a complex system. In this book we present an approach which starts out from macroscopic data. In particular we shall treat systems that acquir...

  7. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    International Nuclear Information System (INIS)

    Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

    2014-01-01

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  8. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Energy Technology Data Exchange (ETDEWEB)

    Lewis, Daniel D. [Integrative Genetics and Genomics, University of California Davis, Davis, CA (United States); Department of Biomedical Engineering, University of California Davis, Davis, CA (United States); Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng, E-mail: cmtan@ucdavis.edu [Department of Biomedical Engineering, University of California Davis, Davis, CA (United States)

    2014-12-09

    As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  9. Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

    Science.gov (United States)

    Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

    2018-01-01

    Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

  10. Systems biology of fungal infection

    Directory of Open Access Journals (Sweden)

    Fabian eHorn

    2012-04-01

    Full Text Available Elucidation of pathogenicity mechanisms of the most important human pathogenic fungi, Aspergillus fumigatus and Candida albicans, has gained great interest in the light of the steadily increasing number of cases of invasive fungal infections.A key feature of these infections is the interaction of the different fungal morphotypes with epithelial and immune effector cells in the human host. Because of the high level of complexity, it is necessary to describe and understand invasive fungal infection by taking a systems biological approach, i.e., by a comprehensive quantitative analysis of the non-linear and selective interactions of a large number of functionally diverse, and frequently multifunctional, sets of elements, e.g., genes, proteins, metabolites, which produce coherent and emergent behaviours in time and space. The recent advances in systems biology will now make it possible to uncover the structure and dynamics of molecular and cellular cause-effect relationships within these pathogenic interactions.We review current efforts to integrate omics and image-based data of host-pathogen interactions into network and spatio-temporal models. The modelling will help to elucidate pathogenicity mechanisms and to identify diagnostic biomarkers and potential drug targets for therapy and could thus pave the way for novel intervention strategies based on novel antifungal drugs and cell therapy.

  11. Modeling complex biological flows in multi-scale systems using the APDEC framework

    Science.gov (United States)

    Trebotich, David

    2006-09-01

    We have developed advanced numerical algorithms to model biological fluids in multiscale flow environments using the software framework developed under the SciDAC APDEC ISIC. The foundation of our computational effort is an approach for modeling DNA laden fluids as ''bead-rod'' polymers whose dynamics are fully coupled to an incompressible viscous solvent. The method is capable of modeling short range forces and interactions between particles using soft potentials and rigid constraints. Our methods are based on higher-order finite difference methods in complex geometry with adaptivity, leveraging algorithms and solvers in the APDEC Framework. Our Cartesian grid embedded boundary approach to incompressible viscous flow in irregular geometries has also been interfaced to a fast and accurate level-sets method within the APDEC Framework for extracting surfaces from volume renderings of medical image data and used to simulate cardio-vascular and pulmonary flows in critical anatomies.

  12. Micro-separation toward systems biology.

    Science.gov (United States)

    Liu, Bi-Feng; Xu, Bo; Zhang, Guisen; Du, Wei; Luo, Qingming

    2006-02-17

    Current biology is experiencing transformation in logic or philosophy that forces us to reevaluate the concept of cell, tissue or entire organism as a collection of individual components. Systems biology that aims at understanding biological system at the systems level is an emerging research area, which involves interdisciplinary collaborations of life sciences, computational and mathematical sciences, systems engineering, and analytical technology, etc. For analytical chemistry, developing innovative methods to meet the requirement of systems biology represents new challenges as also opportunities and responsibility. In this review, systems biology-oriented micro-separation technologies are introduced for comprehensive profiling of genome, proteome and metabolome, characterization of biomolecules interaction and single cell analysis such as capillary electrophoresis, ultra-thin layer gel electrophoresis, micro-column liquid chromatography, and their multidimensional combinations, parallel integrations, microfabricated formats, and nano technology involvement. Future challenges and directions are also suggested.

  13. Nutritional Systems Biology

    DEFF Research Database (Denmark)

    Jensen, Kasper

    and network biology has the potential to increase our understanding of how small molecules affect metabolic pathways and homeostasis, how this perturbation changes at the disease state, and to what extent individual genotypes contribute to this. A fruitful strategy in approaching and exploring the field...... biology research. The paper also shows as a proof-of-concept that a systems biology approach to diet is meaningful and demonstrates some basic principles on how to work with diet systematic. The second chapter of this thesis we developed the resource NutriChem v1.0. A foodchemical database linking...... sites of diet on the disease pathway. We propose a framework for interrogating the critical targets in colon cancer process and identifying plant-based dietary interventions as important modifiers using a systems chemical biology approach. The fifth chapter of the thesis is on discovering of novel anti...

  14. Screening the efficient biological prospects of triazole allied mixed ligand metal complexes

    Science.gov (United States)

    Utthra, Ponnukalai Ponya; Kumaravel, Ganesan; Raman, Natarajan

    2017-12-01

    Triazole appended mixed ligand complexes (1-8) of the general formula [ML (bpy/phen)2]Cl2, where M = Cu(II), Co(II), Ni(II) and Zn(II), L = triazole appended Schiff base (E)sbnd N-(4-nitrobenzylidene)-1H-1,2,4-triazol-3-amine and bpy/phen = 2,2‧-bipyridine/1,10-phenanthroline, have been synthesized. The design and synthesis of this elaborate ligand has been performed with the aim of increasing stability and conjugation of 1,2,4 triazole, whose Schiff base derivatives are known as biologically active compounds thereby exploring their DNA binding affinity and other biological applications. The compounds have been comprehensively characterized by elemental analysis, spectroscopic methods (IR, UV-Vis, EPR, 1H and 13C NMR spectroscopy), ESI mass spectrometry and magnetic susceptibility measurements. The complexes were found to exhibit octahedral geometry. The complexes 1-8 were subjected to DNA binding techniques evaluated using UV-Vis absorption, CV, CD, Fluorescence spectroscopy and hydrodynamic measurements. Complex 5 showed a Kb value of 3.9 × 105 M-1. The DNA damaging efficacy for the complexes was observed to be high compared to the ligand. The antimicrobial screening of the compounds against bacterial and fungal strains indicates that the complexes possess excellent antimicrobial activity than the ligand. The overall biological activity of the complexes with phen as a co-ligand possessed superior potential than the ligand.

  15. Perspective: Differential dynamic microscopy extracts multi-scale activity in complex fluids and biological systems

    Science.gov (United States)

    Cerbino, Roberto; Cicuta, Pietro

    2017-09-01

    Differential dynamic microscopy (DDM) is a technique that exploits optical microscopy to obtain local, multi-scale quantitative information about dynamic samples, in most cases without user intervention. It is proving extremely useful in understanding dynamics in liquid suspensions, soft materials, cells, and tissues. In DDM, image sequences are analyzed via a combination of image differences and spatial Fourier transforms to obtain information equivalent to that obtained by means of light scattering techniques. Compared to light scattering, DDM offers obvious advantages, principally (a) simplicity of the setup; (b) possibility of removing static contributions along the optical path; (c) power of simultaneous different microscopy contrast mechanisms; and (d) flexibility of choosing an analysis region, analogous to a scattering volume. For many questions, DDM has also advantages compared to segmentation/tracking approaches and to correlation techniques like particle image velocimetry. The very straightforward DDM approach, originally demonstrated with bright field microscopy of aqueous colloids, has lately been used to probe a variety of other complex fluids and biological systems with many different imaging methods, including dark-field, differential interference contrast, wide-field, light-sheet, and confocal microscopy. The number of adopting groups is rapidly increasing and so are the applications. Here, we briefly recall the working principles of DDM, we highlight its advantages and limitations, we outline recent experimental breakthroughs, and we provide a perspective on future challenges and directions. DDM can become a standard primary tool in every laboratory equipped with a microscope, at the very least as a first bias-free automated evaluation of the dynamics in a system.

  16. Drawing inspiration from biological optical systems

    Science.gov (United States)

    Wolpert, H. D.

    2009-08-01

    Bio-Mimicking/Bio-Inspiration: How can we not be inspired by Nature? Life has evolved on earth over the last 3.5 to 4 billion years. Materials formed during this time were not toxic; they were created at low temperatures and low pressures unlike many of the materials developed today. The natural materials formed are self-assembled, multifunctional, nonlinear, complex, adaptive, self-repairing and biodegradable. The designs that failed are fossils. Those that survived are the success stories. Natural materials are mostly formed from organics, inorganic crystals and amorphous phases. The materials make economic sense by optimizing the design of the structures or systems to meet multiple needs. We constantly "see" many similar strategies in approaches, between man and nature, but we seldom look at the details of natures approaches. The power of image processing, in many of natures creatures, is a detail that is often overlooked. Seldon does the engineer interact with the biologist and learn what nature has to teach us. The variety and complexity of biological materials and the optical systems formed should inspire us.

  17. Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

    Science.gov (United States)

    Hilfinger, Andreas; Paulsson, Johan

    2011-07-19

    From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

  18. Simulation of biological flow and transport in complex geometries using embedded boundary/volume-of-fluid methods

    International Nuclear Information System (INIS)

    Trebotich, David

    2007-01-01

    We have developed a simulation capability to model multiscale flow and transport in complex biological systems based on algorithms and software infrastructure developed under the SciDAC APDEC CET. The foundation of this work is a new hybrid fluid-particle method for modeling polymer fluids in irregular microscale geometries that enables long-time simulation of validation experiments. Both continuum viscoelastic and discrete particle representations have been used to model the constitutive behavior of polymer fluids. Complex flow environment geometries are represented on Cartesian grids using an implicit function. Direct simulation of flow in the irregular geometry is then possible using embedded boundary/volume-of-fluid methods without loss of geometric detail. This capability has been used to simulate biological flows in a variety of application geometries including biomedical microdevices, anatomical structures and porous media

  19. Dermal tumorigen PAH and complex mixtures for biological research

    International Nuclear Information System (INIS)

    Griest, W.H.; Guerin, M.R.; Ho, C.

    1985-01-01

    Thirteen commercially available, commonly reported four-five ring dermal tumorigen PAHs, were determined in a set of complex mixtures consisting of crude and upgraded coal liquids, and petroleum crude oils and their distillate fractions. Semi-preparative scale, normal phase high performance liquid chromatographic fractionation followed by capillary column gas chromatography or gas chromatography-mass spectroscopy were used for the measurements. Deuterated or carbon-14 labeled PAH served as internal standards or allowed recovery corrections. Approaches for the preparation and measurement of radiolabeled PAH were examined to provide chemical probes for biological study. Synthetic routes for production of 14 C labeled dihydrobenzo[a]pyrene and 14 C- or 3 H 10-azabenzo[a]pyrene are being studied to provide tracers for fundamental studies in tracheal transplant and skin penetration systems. (DT)

  20. Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling

    Directory of Open Access Journals (Sweden)

    Samar Hayat Khan Tareen

    2015-07-01

    Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model

  1. Notions of similarity for systems biology models.

    Science.gov (United States)

    Henkel, Ron; Hoehndorf, Robert; Kacprowski, Tim; Knüpfer, Christian; Liebermeister, Wolfram; Waltemath, Dagmar

    2018-01-01

    Systems biology models are rapidly increasing in complexity, size and numbers. When building large models, researchers rely on software tools for the retrieval, comparison, combination and merging of models, as well as for version control. These tools need to be able to quantify the differences and similarities between computational models. However, depending on the specific application, the notion of 'similarity' may greatly vary. A general notion of model similarity, applicable to various types of models, is still missing. Here we survey existing methods for the comparison of models, introduce quantitative measures for model similarity, and discuss potential applications of combined similarity measures. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on a combination of different model aspects. The six aspects that we define as potentially relevant for similarity are underlying encoding, references to biological entities, quantitative behaviour, qualitative behaviour, mathematical equations and parameters and network structure. We argue that future similarity measures will benefit from combining these model aspects in flexible, problem-specific ways to mimic users' intuition about model similarity, and to support complex model searches in databases. © The Author 2016. Published by Oxford University Press.

  2. Data based identification and prediction of nonlinear and complex dynamical systems

    Science.gov (United States)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  3. Data based identification and prediction of nonlinear and complex dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

    2016-07-12

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  4. Data based identification and prediction of nonlinear and complex dynamical systems

    International Nuclear Information System (INIS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  5. Conceptual modeling in systems biology fosters empirical findings: the mRNA lifecycle.

    Directory of Open Access Journals (Sweden)

    Dov Dori

    Full Text Available One of the main obstacles to understanding complex biological systems is the extent and rapid evolution of information, way beyond the capacity individuals to manage and comprehend. Current modeling approaches and tools lack adequate capacity to model concurrently structure and behavior of biological systems. Here we propose Object-Process Methodology (OPM, a holistic conceptual modeling paradigm, as a means to model both diagrammatically and textually biological systems formally and intuitively at any desired number of levels of detail. OPM combines objects, e.g., proteins, and processes, e.g., transcription, in a way that is simple and easily comprehensible to researchers and scholars. As a case in point, we modeled the yeast mRNA lifecycle. The mRNA lifecycle involves mRNA synthesis in the nucleus, mRNA transport to the cytoplasm, and its subsequent translation and degradation therein. Recent studies have identified specific cytoplasmic foci, termed processing bodies that contain large complexes of mRNAs and decay factors. Our OPM model of this cellular subsystem, presented here, led to the discovery of a new constituent of these complexes, the translation termination factor eRF3. Association of eRF3 with processing bodies is observed after a long-term starvation period. We suggest that OPM can eventually serve as a comprehensive evolvable model of the entire living cell system. The model would serve as a research and communication platform, highlighting unknown and uncertain aspects that can be addressed empirically and updated consequently while maintaining consistency.

  6. Excited states in biological systems

    International Nuclear Information System (INIS)

    Cilento, G.; Zinner, K.; Bechara, E.J.H.; Duran, N.; Baptista, R.C. de; Shimizu, Y.; Augusto, O.; Faljoni-Alario, A.; Vidigal, C.C.C.; Oliveira, O.M.M.F.; Haun, M.

    1979-01-01

    Some aspects of bioluminescence related to bioenergetics are discussed: 1. chemical generation of excited species, by means of two general processes: electron transference and cyclic - and linear peroxide cleavage; 2. biological systems capable of generating excited states and 3. biological functions of these states, specially the non-emissive ones (tripletes). The production and the role of non-emissive excited states in biological systems are analysed, the main purpose of the study being the search for non-emissive states. Experiences carried out in biological systems are described; results and conclusions are given. (M.A.) [pt

  7. Systems biology and biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2010-12-01

    Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

  8. A microfluidic dialysis device for complex biological mixture SERS analysis

    KAUST Repository

    Perozziello, Gerardo; Candeloro, Patrizio; Gentile, Francesco T.; Coluccio, Maria Laura; Tallerico, Marco; De Grazia, Antonio; Nicastri, Annalisa; Perri, Angela Mena; Parrotta, Elvira; Pardeo, Francesca; Catalano, Rossella; Cuda, Giovanni; Di Fabrizio, Enzo M.

    2015-01-01

    In this paper, we present a microfluidic device fabricated with a simple and inexpensive process allowing rapid filtering of peptides from a complex mixture. The polymer microfluidic device can be used for sample preparation in biological

  9. Telemetry System of Biological Parameters

    Directory of Open Access Journals (Sweden)

    Jan Spisak

    2005-01-01

    Full Text Available The mobile telemetry system of biological parameters serves for reading and wireless data transfer of measured values of selected biological parameters to an outlying computer. It concerns basically long time monitoring of vital function of car pilot.The goal of this projects is to propose mobile telemetry system for reading, wireless transfer and processing of biological parameters of car pilot during physical and psychical stress. It has to be made with respect to minimal consumption, weight and maximal device mobility. This system has to eliminate signal noise, which is created by biological artifacts and disturbances during the data transfer.

  10. Logical analysis of biological systems

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian

    2005-01-01

    R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005.......R. Mardare, Logical analysis of biological systems. Fundamenta Informaticae, N 64:271-285, 2005....

  11. Institute for Genomics and Systems Biology

    Science.gov (United States)

    Institute for Genomics and Systems Biology Discover. Predict. Improve. Advancing Human and , 2015 See all Research Papers Featured Video Introduction to Systems Biology Video: Introduction to Systems Biology News Jack Gilbert Heading UChicago Startup that Aims to Predict Behavior of Trillions of

  12. Radiosynthesis and biological evaluation of the 99mTc-tricarbonyl moxifloxacin dithiocarbamate complex as a potential Staphylococcus aureus infection radiotracer

    International Nuclear Information System (INIS)

    Shah, Syed Qaiser; Khan, Muhammad Rafiullah

    2011-01-01

    In the present investigation, radiosynthesis of the 99m Tc-tricarbonyl moxifloxacin dithiocarbamate complex ( 99m Tc(CO) 3 -MXND) and its biological evaluation in male Wister rats (MWR) artificially infected with Staphylococcus aureus (S. aureus) was assessed. The 99m Tc(CO) 3 -MXND complex was radiochemically examined in terms of stability in saline and in serum and biologically its in-vitro binding with S. aureus and percent absorption in MWR models. Radiochemically the 99m Tc(CO) 3 -MXND complex showed more than 90% stability in saline up to 240 min and in serum 14.95% undesirable species was appeared within 16 h. In-vitro the 99m Tc(CO) 3 -MXND complex showed saturated binding with S. aureus. In MWR artificially infected with live S. aureus the complex showed about six fold higher uptakes in the infected muscle as compared to the normal muscle. However, insignificant change in the uptake of 99m Tc(CO) 3 -MXND complex in the infected and inflamed or normal muscle was observed in the MWR infected with heat killed S. aureus. The 99m Tc(CO) 3 -MXND complex disappeared from the circulatory system and appeared in the urinary system within 60-90 min followed by excretion through normal route of urinary system. Based on the elevated and stable radiochemical succumb in saline, serum, saturated in-vitro binding with S. aureus and higher accumulation in the target organ of the MWR, we recommend the 99m Tc(CO) 3 -MXND complex for radio-localization of the infection induced by S. aureus in human.

  13. Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

    Science.gov (United States)

    Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

    2013-01-01

    Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

  14. Biophysics and systems biology.

    Science.gov (United States)

    Noble, Denis

    2010-03-13

    Biophysics at the systems level, as distinct from molecular biophysics, acquired its most famous paradigm in the work of Hodgkin and Huxley, who integrated their equations for the nerve impulse in 1952. Their approach has since been extended to other organs of the body, notably including the heart. The modern field of computational biology has expanded rapidly during the first decade of the twenty-first century and, through its contribution to what is now called systems biology, it is set to revise many of the fundamental principles of biology, including the relations between genotypes and phenotypes. Evolutionary theory, in particular, will require re-assessment. To succeed in this, computational and systems biology will need to develop the theoretical framework required to deal with multilevel interactions. While computational power is necessary, and is forthcoming, it is not sufficient. We will also require mathematical insight, perhaps of a nature we have not yet identified. This article is therefore also a challenge to mathematicians to develop such insights.

  15. Quantum Dynamics in Biological Systems

    Science.gov (United States)

    Shim, Sangwoo

    In the first part of this dissertation, recent efforts to understand quantum mechanical effects in biological systems are discussed. Especially, long-lived quantum coherences observed during the electronic energy transfer process in the Fenna-Matthews-Olson complex at physiological condition are studied extensively using theories of open quantum systems. In addition to the usual master equation based approaches, the effect of the protein structure is investigated in atomistic detail through the combined application of quantum chemistry and molecular dynamics simulations. To evaluate the thermalized reduced density matrix, a path-integral Monte Carlo method with a novel importance sampling approach is developed for excitons coupled to an arbitrary phonon bath at a finite temperature. In the second part of the thesis, simulations of molecular systems and applications to vibrational spectra are discussed. First, the quantum dynamics of a molecule is simulated by combining semiclassical initial value representation and density funcitonal theory with analytic derivatives. A computationally-tractable approximation to the sum-of-states formalism of Raman spectra is subsequently discussed.

  16. Inverse problems in systems biology

    International Nuclear Information System (INIS)

    Engl, Heinz W; Lu, James; Müller, Stefan; Flamm, Christoph; Schuster, Peter; Kügler, Philipp

    2009-01-01

    Systems biology is a new discipline built upon the premise that an understanding of how cells and organisms carry out their functions cannot be gained by looking at cellular components in isolation. Instead, consideration of the interplay between the parts of systems is indispensable for analyzing, modeling, and predicting systems' behavior. Studying biological processes under this premise, systems biology combines experimental techniques and computational methods in order to construct predictive models. Both in building and utilizing models of biological systems, inverse problems arise at several occasions, for example, (i) when experimental time series and steady state data are used to construct biochemical reaction networks, (ii) when model parameters are identified that capture underlying mechanisms or (iii) when desired qualitative behavior such as bistability or limit cycle oscillations is engineered by proper choices of parameter combinations. In this paper we review principles of the modeling process in systems biology and illustrate the ill-posedness and regularization of parameter identification problems in that context. Furthermore, we discuss the methodology of qualitative inverse problems and demonstrate how sparsity enforcing regularization allows the determination of key reaction mechanisms underlying the qualitative behavior. (topical review)

  17. Geometric triangular chiral hexagon crystal-like complexes organization in pathological tissues biological collision order.

    Directory of Open Access Journals (Sweden)

    Jairo A Díaz

    Full Text Available The present study describes and documents self-assembly of geometric triangular chiral hexagon crystal like complex organizations (GTCHC in human pathological tissues. The authors have found this architectural geometric expression at macroscopic and microscopic levels mainly in cancer processes. This study is based essentially on macroscopic and histopathologic analyses of 3000 surgical specimens: 2600 inflammatory lesions and 400 malignant tumours. Geometric complexes identified photographically at macroscopic level were located in the gross surgical specimen, and these areas were carefully dissected. Samples were taken to carry out histologic analysis. Based on the hypothesis of a collision genesis mechanism and because it is difficult to carry out an appropriate methodological observation in biological systems, the authors designed a model base on other dynamic systems to obtain indirect information in which a strong white flash wave light discharge, generated by an electronic device, hits over the lines of electrical conductance structured in helicoidal pattern. In their experimental model, the authors were able to reproduce and to predict polarity, chirality, helicoid geometry, triangular and hexagonal clusters through electromagnetic sequential collisions. They determined that similar events among constituents of extracelular matrix which drive and produce piezoelectric activity are responsible for the genesis of GTCHC complexes in pathological tissues. This research suggests that molecular crystals represented by triangular chiral hexagons derived from a collision-attraction event against collagen type I fibrils emerge at microscopic and macroscopic scales presenting a lateral assembly of each side of hypertrophy helicoid fibers, that represent energy flow in cooperative hierarchically chiral electromagnetic interaction in pathological tissues and arises as a geometry of the equilibrium in perturbed biological systems. Further

  18. Geometric triangular chiral hexagon crystal-like complexes organization in pathological tissues biological collision order.

    Science.gov (United States)

    Díaz, Jairo A; Jaramillo, Natalia A; Murillo, Mauricio F

    2007-12-12

    The present study describes and documents self-assembly of geometric triangular chiral hexagon crystal like complex organizations (GTCHC) in human pathological tissues. The authors have found this architectural geometric expression at macroscopic and microscopic levels mainly in cancer processes. This study is based essentially on macroscopic and histopathologic analyses of 3000 surgical specimens: 2600 inflammatory lesions and 400 malignant tumours. Geometric complexes identified photographically at macroscopic level were located in the gross surgical specimen, and these areas were carefully dissected. Samples were taken to carry out histologic analysis. Based on the hypothesis of a collision genesis mechanism and because it is difficult to carry out an appropriate methodological observation in biological systems, the authors designed a model base on other dynamic systems to obtain indirect information in which a strong white flash wave light discharge, generated by an electronic device, hits over the lines of electrical conductance structured in helicoidal pattern. In their experimental model, the authors were able to reproduce and to predict polarity, chirality, helicoid geometry, triangular and hexagonal clusters through electromagnetic sequential collisions. They determined that similar events among constituents of extracelular matrix which drive and produce piezoelectric activity are responsible for the genesis of GTCHC complexes in pathological tissues. This research suggests that molecular crystals represented by triangular chiral hexagons derived from a collision-attraction event against collagen type I fibrils emerge at microscopic and macroscopic scales presenting a lateral assembly of each side of hypertrophy helicoid fibers, that represent energy flow in cooperative hierarchically chiral electromagnetic interaction in pathological tissues and arises as a geometry of the equilibrium in perturbed biological systems. Further interdisciplinary studies must

  19. Systems biology in critical-care nursing.

    Science.gov (United States)

    Schallom, Lynn; Thimmesch, Amanda R; Pierce, Janet D

    2011-01-01

    Systems biology applies advances in technology and new fields of study including genomics, transcriptomics, proteomics, and metabolomics to the development of new treatments and approaches of care for the critically ill and injured patient. An understanding of systems biology enhances a nurse's ability to implement evidence-based practice and to educate patients and families on novel testing and therapies. Systems biology is an integrated and holistic view of humans in relationship with the environment. Biomarkers are used to measure the presence and severity of disease and are rapidly expanding in systems biology endeavors. A systems biology approach using predictive, preventive, and participatory involvement is being utilized in a plethora of conditions of critical illness and injury including sepsis, cancer, pulmonary disease, and traumatic injuries.

  20. Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

    Science.gov (United States)

    Saks, Valdur; Monge, Claire; Guzun, Rita

    2009-01-01

    We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed. PMID:19399243

  1. Compartmental study of biological systems

    International Nuclear Information System (INIS)

    Moretti, J.L.

    1975-01-01

    The compartmental analysis of biological system is dealt with on several chapters devoted successively to: terminology; a mathematical and symbolic account of a system at equilibrium; different compartment systems; analysis of the experimental results. For this it is pointed out that the application of compartmental systems to biological phenomena is not always without danger. Sometimes the compartmental system established in a reference subject fails to conform in the patient. The compartments can divide into two or join together, completely changing the aspect of the system so that parameters calculated with the old model become entirely false. The conclusion is that the setting up of a compartmental system to represent a biological phenomenon is a tricky undertaking and the results must be constantly criticized and questioned [fr

  2. Radical production in biological systems

    International Nuclear Information System (INIS)

    Johnson, J.R.; Akabani, G.

    1994-10-01

    This paper describes our effort to develop a metric for radiation exposure that is more fundamental than adsorbed dose and upon which a metric for exposure to chemicals could be based. This metric is based on the production of radicals by the two agents. Radicals produced by radiation in biological systems commonly assumed to be the same as those produced in water despite the presence of a variety of complex molecules. This may explain why the extensive efforts to describe the relationship between energy deposition (track structure) and molecular damage to DNA, based on the spectrum of radicals produced, have not been successful in explaining simple biological effects such as cell killing. Current models assume that DNA and its basic elements are immersed in water-like media and only model the production and diffusion of water-based radicals and their interaction with DNA structures; these models lack the cross sections associated with each macro-component of DNA and only treat water-based radicals. It has been found that such models are not realistic because DNA is not immersed in pure water. A computer code capable of simulating electron tracks, low-energy electrons, energy deposition in small molecules, and radical production and diffusion in water like media has been developed. This code is still in at a primitive stage and development is continuing. It is being used to study radical production by radiation, and radical diffusion and interactions in simple molecular systems following their production. We are extending the code to radical production by chemicals to complement our PBPK modeling efforts. It therefore has been developed primarily for use with radionuclides that are in biological materials, and not for radiation fields

  3. A geometric initial guess for localized electronic orbitals in modular biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Beckman, P. G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Univ. of Chicago, IL (United States); Fattebert, J. L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lau, E. Y. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Osei-Kuffuor, D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-09-11

    Recent first-principles molecular dynamics algorithms using localized electronic orbitals have achieved O(N) complexity and controlled accuracy in simulating systems with finite band gaps. However, accurately deter- mining the centers of these localized orbitals during simulation setup may require O(N3) operations, which is computationally infeasible for many biological systems. We present an O(N) approach for approximating orbital centers in proteins, DNA, and RNA which uses non-localized solutions for a set of fixed-size subproblems to create a set of geometric maps applicable to larger systems. This scalable approach, used as an initial guess in the O(N) first-principles molecular dynamics code MGmol, facilitates first-principles simulations in biological systems of sizes which were previously impossible.

  4. A Concise Introduction to the Statistical Physics of Complex Systems

    CERN Document Server

    Bertin, Eric

    2012-01-01

    This concise primer (based on lectures given at summer schools on complex systems and on a masters degree course in complex systems modeling) will provide graduate students and newcomers to the field with the basic knowledge of the concepts and methods of statistical physics and its potential for application to interdisciplinary topics.  Indeed, in recent years, statistical physics has begun to attract the interest of a broad community of researchers in the field of complex system sciences, ranging from biology to the social sciences, economics and computer science. More generally, a growing number of graduate students and researchers feel the need to learn some basic concepts and questions originating in other disciplines without necessarily having to master all of the corresponding technicalities and jargon. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting ‘entities’, and on the other to predict...

  5. Methods of Model Reduction for Large-Scale Biological Systems: A Survey of Current Methods and Trends.

    Science.gov (United States)

    Snowden, Thomas J; van der Graaf, Piet H; Tindall, Marcus J

    2017-07-01

    Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed.

  6. Function of dynamic models in systems biology: linking structure to behaviour.

    Science.gov (United States)

    Knüpfer, Christian; Beckstein, Clemens

    2013-10-08

    Dynamic models in Systems Biology are used in computational simulation experiments for addressing biological questions. The complexity of the modelled biological systems and the growing number and size of the models calls for computer support for modelling and simulation in Systems Biology. This computer support has to be based on formal representations of relevant knowledge fragments. In this paper we describe different functional aspects of dynamic models. This description is conceptually embedded in our "meaning facets" framework which systematises the interpretation of dynamic models in structural, functional and behavioural facets. Here we focus on how function links the structure and the behaviour of a model. Models play a specific role (teleological function) in the scientific process of finding explanations for dynamic phenomena. In order to fulfil this role a model has to be used in simulation experiments (pragmatical function). A simulation experiment always refers to a specific situation and a state of the model and the modelled system (conditional function). We claim that the function of dynamic models refers to both the simulation experiment executed by software (intrinsic function) and the biological experiment which produces the phenomena under investigation (extrinsic function). We use the presented conceptual framework for the function of dynamic models to review formal accounts for functional aspects of models in Systems Biology, such as checklists, ontologies, and formal languages. Furthermore, we identify missing formal accounts for some of the functional aspects. In order to fill one of these gaps we propose an ontology for the teleological function of models. We have thoroughly analysed the role and use of models in Systems Biology. The resulting conceptual framework for the function of models is an important first step towards a comprehensive formal representation of the functional knowledge involved in the modelling and simulation process

  7. Application of integrative genomics and systems biology to conventional and in vitro reproductive traits in cattle

    DEFF Research Database (Denmark)

    Mazzoni, Gianluca; Pedersen, Hanne S.; de Oliveira Junior, Gerson A.

    2017-01-01

    by both conventional and ARTs such as OPU-IVP. The integration of systems biology information across different biological layers generates a complete view of the different molecular networks that control complex traits and can provide a strong contribution to the understanding of traits related to ARTs....

  8. Systems Biology

    Indian Academy of Sciences (India)

    IAS Admin

    study and understand the function of biological systems, particu- larly, the response of such .... understand the organisation and behaviour of prokaryotic sys- tems. ... relationship of the structure of a target molecule to its ability to bind a certain ...

  9. Calculating life? Duelling discourses in interdisciplinary systems biology.

    Science.gov (United States)

    Calvert, Jane; Fujimura, Joan H

    2011-06-01

    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. Copyright © 2010 Elsevier Ltd. All rights reserved.

  10. Constant-Distance Mode Nanospray Desorption Electrospray Ionization Mass Spectrometry Imaging of Biological Samples with Complex Topography

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Son N.; Liyu, Andrey V.; Chu, Rosalie K.; Anderton, Christopher R.; Laskin, Julia

    2017-01-17

    A new approach for constant distance mode mass spectrometry imaging of biological samples using nanospray desorption electrospray ionization (nano-DESI MSI) was developed by integrating a shear-force probe with nano-DESI probe. The technical concept and basic instrumental setup as well as general operation of the system are described. Mechanical dampening of resonant oscillations due to the presence of shear forces between the probe and the sample surface enables constant-distance imaging mode via a computer controlled closed feedback loop. The capability of simultaneous chemical and topographic imaging of complex biological samples is demonstrated using living Bacillus Subtilis ATCC 49760 colonies on agar plates. The constant-distance mode nano-DESI MSI enabled imaging of many metabolites including non-ribosomal peptides (surfactin, plipastatin and iturin) and iron-bound heme on the surface of living bacterial colonies ranging in diameter from 10 mm to 13 mm with height variations of up to 0.8 mm above the agar plate. Co-registration of ion images to topographic images provided higher-contrast images. Constant-mode nano-DESI MSI is ideally suited for imaging biological samples of complex topography in their native state.

  11. Collaborative Systems Biology Projects for the Military Medical Community.

    Science.gov (United States)

    Zalatoris, Jeffrey J; Scheerer, Julia B; Lebeda, Frank J

    2017-09-01

    This pilot study was conducted to examine, for the first time, the ongoing systems biology research and development projects within the laboratories and centers of the U.S. Army Medical Research and Materiel Command (USAMRMC). The analysis has provided an understanding of the breadth of systems biology activities, resources, and collaborations across all USAMRMC subordinate laboratories. The Systems Biology Collaboration Center at USAMRMC issued a survey regarding systems biology research projects to the eight U.S.-based USAMRMC laboratories and centers in August 2016. This survey included a data call worksheet to gather self-identified project and programmatic information. The general topics focused on the investigators and their projects, on the project's research areas, on omics and other large data types being collected and stored, on the analytical or computational tools being used, and on identifying intramural (i.e., USAMRMC) and extramural collaborations. Among seven of the eight laboratories, 62 unique systems biology studies were funded and active during the final quarter of fiscal year 2016. Of 29 preselected medical Research Task Areas, 20 were associated with these studies, some of which were applicable to two or more Research Task Areas. Overall, studies were categorized among six general types of objectives: biological mechanisms of disease, risk of/susceptibility to injury or disease, innate mechanisms of healing, diagnostic and prognostic biomarkers, and host/patient responses to vaccines, and therapeutic strategies including host responses to therapies. We identified eight types of omics studies and four types of study subjects. Studies were categorized on a scale of increasing complexity from single study subject/single omics technology studies (23/62) to studies integrating results across two study subject types and two or more omics technologies (13/62). Investigators at seven USAMRMC laboratories had collaborations with systems biology experts

  12. Growing trend of CE at the omics level: the frontier of systems biology.

    Science.gov (United States)

    Oh, Eulsik; Hasan, Md Nabiul; Jamshed, Muhammad; Park, Soo Hyun; Hong, Hye-Min; Song, Eun Joo; Yoo, Young Sook

    2010-01-01

    In a novel attempt to comprehend the complexity of life, systems biology has recently emerged as a state-of-the-art approach for biological research in contrast to the reductionist approaches that have been used in molecular cell biology since the 1950s. Because a massive amount of information is required in many systems biology studies of life processes, we have increasingly come to depend on techniques that provide high-throughput omics data. CE and CE coupled to MS have served as powerful analytical tools for providing qualitative and quantitative omics data. Recent systems biology studies have focused strongly on the diagnosis and treatment of diseases. The increasing number of clinical research papers on drug discovery and disease therapies reflects this growing interest among scientists. Since such clinical research reflects one of the ultimate purposes of bioscience, these trends will be sustained for a long time. Thus, this review mainly focuses on the application of CE and CE-MS in diagnosis as well as on the latest CE methods developed. Furthermore, we outline the new challenges that arose in 2008 and later in elucidating the system-level functions of the bioconstituents of living organisms.

  13. Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems.

    Science.gov (United States)

    Bashor, Caleb J; Horwitz, Andrew A; Peisajovich, Sergio G; Lim, Wendell A

    2010-01-01

    The living cell is an incredibly complex entity, and the goal of predictively and quantitatively understanding its function is one of the next great challenges in biology. Much of what we know about the cell concerns its constituent parts, but to a great extent we have yet to decode how these parts are organized to yield complex physiological function. Classically, we have learned about the organization of cellular networks by disrupting them through genetic or chemical means. The emerging discipline of synthetic biology offers an additional, powerful approach to study systems. By rearranging the parts that comprise existing networks, we can gain valuable insight into the hierarchical logic of the networks and identify the modular building blocks that evolution uses to generate innovative function. In addition, by building minimal toy networks, one can systematically explore the relationship between network structure and function. Here, we outline recent work that uses synthetic biology approaches to investigate the organization and function of cellular networks, and describe a vision for a synthetic biology toolkit that could be used to interrogate the design principles of diverse systems.

  14. Temperature-dependent phase transitions in zeptoliter volumes of a complex biological membrane

    International Nuclear Information System (INIS)

    Nikiforov, Maxim P; Jesse, Stephen; Kalinin, Sergei V; Hohlbauch, Sophia; Proksch, Roger; King, William P; Voitchovsky, Kislon; Contera, Sonia Antoranz

    2011-01-01

    Phase transitions in purple membrane have been a topic of debate for the past two decades. In this work we present studies of a reversible transition of purple membrane in the 50-60 deg. C range in zeptoliter volumes under different heating regimes (global heating and local heating). The temperature of the reversible phase transition is 52 ± 5 deg. C for both local and global heating, supporting the hypothesis that this transition is mainly due to a structural rearrangement of bR molecules and trimers. To achieve high resolution measurements of temperature-dependent phase transitions, a new scanning probe microscopy-based method was developed. We believe that our new technique can be extended to other biological systems and can contribute to the understanding of inhomogeneous phase transitions in complex systems.

  15. Iterative Systems Biology for Medicine – time for advancing from network signature to mechanistic equations

    KAUST Repository

    Gomez-Cabrero, David

    2017-05-09

    The rise and growth of Systems Biology following the sequencing of the human genome has been astounding. Early on, an iterative wet-dry methodology was formulated which turned out as a successful approach in deciphering biological complexity. Such type of analysis effectively identified and associated molecular network signatures operative in biological processes across different systems. Yet, it has proven difficult to distinguish between causes and consequences, thus making it challenging to attack medical questions where we require precise causative drug targets and disease mechanisms beyond a web of associated markers. Here we review principal advances with regard to identification of structure, dynamics, control, and design of biological systems, following the structure in the visionary review from 2002 by Dr. Kitano. Yet, here we find that the underlying challenge of finding the governing mechanistic system equations enabling precision medicine remains open thus rendering clinical translation of systems biology arduous. However, stunning advances in raw computational power, generation of high-precision multi-faceted biological data, combined with powerful algorithms hold promise to set the stage for data-driven identification of equations implicating a fundamental understanding of living systems during health and disease.

  16. "Life-bearing molecules" versus "life-embodying systems": Two contrasting views on the what-is-life (WIL) problem persisting from the early days of molecular biology to the post-genomic cell- and organism-level biology.

    Science.gov (United States)

    Sato, Naoki

    2018-05-01

    "What is life?" is an ultimate biological quest for the principle that makes organisms alive. This 'WIL problem' is not, however, a simple one that we have a straightforward strategy to attack. From the beginning, molecular biology tried to identify molecules that bear the essence of life: the double helical DNA represented replication, and enzymes were micro-actuators of biological activities. A dominating idea behind these mainstream biological studies relies on the identification of life-bearing molecules, which themselves are models of life. Another, prevalent idea emphasizes that life resides in the whole system of an organism, but not in some particular molecules. The behavior of a complex system may be considered to embody the essence of life. The thermodynamic view of life system in the early 20th century was remodeled as physics of complex systems and systems biology. The two views contrast with each other, but they are no longer heritage of the historical dualism in biology, such as mechanism/materialism versus vitalism, or reductionism versus holism. These two views are both materialistic and mechanistic, and act as driving forces of modern biology. In reality, molecules function in a context of systems, whereas systems presuppose functional molecules. A key notion to reconcile this conflict is that subjects of biological studies are given before we start to study them. Cell- or organism-level biology is destined to the dialectic of molecules and systems, but this antagonism can be resolved by dynamic thinking involving biological evolution. Copyright © 2018 Elsevier B.V. All rights reserved.

  17. Philosophical Basis and Some Historical Aspects of Systems Biology: From Hegel to Noble - Applications for Bioenergetic Research

    Directory of Open Access Journals (Sweden)

    Valdur Saks

    2009-03-01

    Full Text Available We live in times of paradigmatic changes for the biological sciences. Reductionism, that for the last six decades has been the philosophical basis of biochemistry and molecular biology, is being displaced by Systems Biology, which favors the study of integrated systems. Historically, Systems Biology - defined as the higher level analysis of complex biological systems - was pioneered by Claude Bernard in physiology, Norbert Wiener with the development of cybernetics, and Erwin Schrödinger in his thermodynamic approach to the living. Systems Biology applies methods inspired by cybernetics, network analysis, and non-equilibrium dynamics of open systems. These developments follow very precisely the dialectical principles of development from thesis to antithesis to synthesis discovered by Hegel. Systems Biology opens new perspectives for studies of the integrated processes of energy metabolism in different cells. These integrated systems acquire new, system-level properties due to interaction of cellular components, such as metabolic compartmentation, channeling and functional coupling mechanisms, which are central for regulation of the energy fluxes. State of the art of these studies in the new area of Molecular System Bioenergetics is analyzed.

  18. Applicability of Computational Systems Biology in Toxicology

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning; Hadrup, Niels; Audouze, Karine Marie Laure

    2014-01-01

    be used to establish hypotheses on links between the chemical and human diseases. Such information can also be applied for designing more intelligent animal/cell experiments that can test the established hypotheses. Here, we describe how and why to apply an integrative systems biology method......Systems biology as a research field has emerged within the last few decades. Systems biology, often defined as the antithesis of the reductionist approach, integrates information about individual components of a biological system. In integrative systems biology, large data sets from various sources...... and databases are used to model and predict effects of chemicals on, for instance, human health. In toxicology, computational systems biology enables identification of important pathways and molecules from large data sets; tasks that can be extremely laborious when performed by a classical literature search...

  19. Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

    Directory of Open Access Journals (Sweden)

    Daniel eLewis

    2014-12-01

    Full Text Available As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo systems, with only a few examples of prominent work done on predicting the dynamics of cell-free systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

  20. PREFACE: Complex Networks: from Biology to Information Technology

    Science.gov (United States)

    Barrat, A.; Boccaletti, S.; Caldarelli, G.; Chessa, A.; Latora, V.; Motter, A. E.

    2008-06-01

    The field of complex networks is one of the most active areas in contemporary statistical physics. Ten years after seminal work initiated the modern study of networks, interest in the field is in fact still growing, as indicated by the ever increasing number of publications in network science. The reason for such a resounding success is most likely the simplicity and broad significance of the approach that, through graph theory, allows researchers to address a variety of different complex systems within a common framework. This special issue comprises a selection of contributions presented at the workshop 'Complex Networks: from Biology to Information Technology' held in July 2007 in Pula (Cagliari), Italy as a satellite of the general conference STATPHYS23. The contributions cover a wide range of problems that are currently among the most important questions in the area of complex networks and that are likely to stimulate future research. The issue is organised into four sections. The first two sections describe 'methods' to study the structure and the dynamics of complex networks, respectively. After this methodological part, the issue proceeds with a section on applications to biological systems. The issue closes with a section concentrating on applications to the study of social and technological networks. The first section, entitled Methods: The Structure, consists of six contributions focused on the characterisation and analysis of structural properties of complex networks: The paper Motif-based communities in complex networks by Arenas et al is a study of the occurrence of characteristic small subgraphs in complex networks. These subgraphs, known as motifs, are used to define general classes of nodes and their communities by extending the mathematical expression of the Newman-Girvan modularity. The same line of research, aimed at characterising network structure through the analysis of particular subgraphs, is explored by Bianconi and Gulbahce in Algorithm

  1. The complexity of DNA damage: relevance to biological consequences

    International Nuclear Information System (INIS)

    Ward, J.F.

    1994-01-01

    Ionizing radiation causes both singly and multiply damaged sites in DNA when the range of radical migration is limited by the presence of hydroxyl radical scavengers (e.g. within cells). Multiply damaged sites are considered to be more biologically relevant because of the challenges they present to cellular repair mechanisms. These sites occur in the form of DNA double-strand breaks (dsb) but also as other multiple damages that can be converted to dsb during attempted repair. The presence of a dsb can lead to loss of base sequence information and/or can permit the two ends of a break to separate and rejoin with the wrong partner. (Multiply damaged sites may also be the biologically relevant type of damage caused by other agents, such as UVA, B and/or C light, and some antitumour antibiotics). The quantitative data available from radiation studies of DNA are shown to support the proposed mechanisms for the production of complex damage in cellular DNA, i.e. via scavengable and non-scavengable mechanisms. The yields of complex damages can in turn be used to support the conclusion that cellular mutations are a consequence of the presence of these damages within a gene. (Author)

  2. Editorial overview : Systems biology for biotechnology

    NARCIS (Netherlands)

    Heinemann, Matthias; Pilpel, Yitzhak

    About 15 years ago, systems biology was introduced as a novel approach to biological research. On the one side, its introduction was a result of the recognition that through solely the reductionist approach, we would ulti- mately not be able to understand how biological systems function as a whole.

  3. Evolving cell models for systems and synthetic biology.

    Science.gov (United States)

    Cao, Hongqing; Romero-Campero, Francisco J; Heeb, Stephan; Cámara, Miguel; Krasnogor, Natalio

    2010-03-01

    This paper proposes a new methodology for the automated design of cell models for systems and synthetic biology. Our modelling framework is based on P systems, a discrete, stochastic and modular formal modelling language. The automated design of biological models comprising the optimization of the model structure and its stochastic kinetic constants is performed using an evolutionary algorithm. The evolutionary algorithm evolves model structures by combining different modules taken from a predefined module library and then it fine-tunes the associated stochastic kinetic constants. We investigate four alternative objective functions for the fitness calculation within the evolutionary algorithm: (1) equally weighted sum method, (2) normalization method, (3) randomly weighted sum method, and (4) equally weighted product method. The effectiveness of the methodology is tested on four case studies of increasing complexity including negative and positive autoregulation as well as two gene networks implementing a pulse generator and a bandwidth detector. We provide a systematic analysis of the evolutionary algorithm's results as well as of the resulting evolved cell models.

  4. Quantum Effects in Biological Systems

    CERN Document Server

    2016-01-01

    Since the last decade the study of quantum mechanical phenomena in biological systems has become a vibrant field of research. Initially sparked by evidence of quantum effects in energy transport that is instrumental for photosynthesis, quantum biology asks the question of how methods and models from quantum theory can help us to understand fundamental mechanisms in living organisms. This approach entails a paradigm change challenging the related disciplines: The successful framework of quantum theory is taken out of its low-temperature, microscopic regimes and applied to hot and dense macroscopic environments, thereby extending the toolbox of biology and biochemistry at the same time. The Quantum Effects in Biological Systems conference is a platform for researchers from biology, chemistry and physics to present and discuss the latest developments in the field of quantum biology. After meetings in Lisbon (2009), Harvard (2010), Ulm (2011), Berkeley (2012), Vienna (2013), Singapore (2014) and Florence (2015),...

  5. From precision polymers to complex materials and systems

    Science.gov (United States)

    Lutz, Jean-François; Lehn, Jean-Marie; Meijer, E. W.; Matyjaszewski, Krzysztof

    2016-05-01

    Complex chemical systems, such as living biological matter, are highly organized structures based on discrete molecules in constant dynamic interactions. These natural materials can evolve and adapt to their environment. By contrast, man-made materials exhibit simpler properties. In this Review, we highlight that most of the necessary elements for the development of more complex synthetic matter are available today. Using modern strategies, such as controlled radical polymerizations, supramolecular polymerizations or stepwise synthesis, polymers with precisely controlled molecular structures can be synthesized. Moreover, such tailored polymers can be folded or self-assembled into defined nanoscale morphologies. These self-organized macromolecular objects can be at thermal equilibrium or can be driven out of equilibrium. Recently, in the latter case, interesting dynamic materials have been developed. However, this is just a start, and more complex adaptive materials are anticipated.

  6. Static Analysis for Systems Biology

    DEFF Research Database (Denmark)

    Nielson, Flemming; Nielson, Hanne Riis; Rosa, D. Schuch da

    2004-01-01

    This paper shows how static analysis techniques can help understanding biological systems. Based on a simple example we illustrate the outcome of performing three different analyses extracting information of increasing precision. We conclude by reporting on the potential impact and exploitation o...... of these techniques in systems biology....

  7. Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

    Science.gov (United States)

    Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

    This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

  8. A comparison of the application of a biological and phenetic species concept in the Hebeloma crustuliniforme complex within a phylogenetic framework

    DEFF Research Database (Denmark)

    Aanen, Duur Kornelis; Kuyper, T.W.

    2004-01-01

    a major factor. Intercompatibility tests and DNA based phylogenies indicate that most biological species are very closely related and hence provide support for the claim that correspondence between a biological species concept and a phenetic species concept in the H. crustuliniforme complex is not likely...... biological species in that complex. Based on two nuclear sequences, we present a best estimate of the phylogeny of biological species within the complex. Using this phylogeny, on the basis of strict monophyly only two species can be morphologically recognised among 22 biological species. Relaxing......A method is presented to derive an operational phenetic species concept for the Hebeloma crustuliniforme complex in northwestern Europe. The complex was found to consist of at least 22 biological species (intercompatibility groups; ICGs). Almost none of these biological species could be recognised...

  9. Kirigami artificial muscles with complex biologically inspired morphologies

    International Nuclear Information System (INIS)

    Sareh, Sina; Rossiter, Jonathan

    2013-01-01

    In this paper we present bio-inspired smart structures which exploit the actuation of flexible ionic polymer composites and the kirigami design principle. Kirigami design is used to convert planar actuators into active 3D structures capable of large out-of-plane displacement and that replicate biological mechanisms. Here we present the burstbot, a fluid control and propulsion mechanism based on the atrioventricular cuspid valve, and the vortibot, a spiral actuator based on Vorticella campanula, a ciliate protozoa. Models derived from biological counterparts are used as a platform for design optimization and actuator performance measurement. The symmetric and asymmetric fluid interactions of the burstbot are investigated and the effectiveness in fluid transport applications is demonstrated. The vortibot actuator is geometrically optimized as a camera positioner capable of 360° scanning. Experimental results for a one-turn spiral actuator show complex actuation derived from a single degree of freedom control signal. (paper)

  10. Towards physical principles of biological evolution

    Science.gov (United States)

    Katsnelson, Mikhail I.; Wolf, Yuri I.; Koonin, Eugene V.

    2018-03-01

    Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. Such systems are characterized by frustration whereby local state with minimal free energy conflict with the global minimum, resulting in ‘emergent phenomena’. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. These frustration effects appear to drive the evolution of biological complexity. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort. However, it is unrealistic to expect that such a theory can be created in one scoop; if it ever comes to being, this can only happen through integration of multiple physical models of evolutionary processes. Furthermore, the existing framework of theoretical physics is unlikely to suffice

  11. Dinitrosyl iron complexes and S-nitrosothiols are two possible forms for stabilization and transport of nitric oxide in biological systems.

    Science.gov (United States)

    Vanin, A F

    1998-07-01

    The physicochemical properties, mechanisms of synthesis and decomposition of dinitrosyl iron complexes (DNICs) with thiol-containing ligands and of S-nitrosothiols (RS-NO), and the potential role of these compounds in storage and transport of NO in biological systems are reviewed. Special attention is given to the phenomenon of mutual transformation of DNIC and RS-NO catalyzed by Fe2+. Each Fe2+ binds two neutral NO molecules in the DNICs, catalyzes their mutual oxidation--reduction with formation of nitrous oxide and nitrosonium ions appearing in the DNICs. These ions S-nitrosate thiol-compounds with RS-NO formation. Fe2+ binds two RS-NO molecules and catalyzes their mutual oxidation--reduction followed by decomposition of the resulting molecules. Mutual conversion of DNICs and RS-NO regulated by iron, thiol, and NO levels is suggested to provide NO transport in cells and tissues.

  12. Synthetic biology: engineering molecular computers

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Complicated systems cannot survive the rigors of a chaotic environment, without balancing mechanisms that sense, decide upon and counteract the exerted disturbances. Especially so with living organisms, forced by competition to incredible complexities, escalating also their self-controlling plight. Therefore, they compute. Can we harness biological mechanisms to create artificial computing systems? Biology offers several levels of design abstraction: molecular machines, cells, organisms... ranging from the more easily-defined to the more inherently complex. At the bottom of this stack we find the nucleic acids, RNA and DNA, with their digital structure and relatively precise interactions. They are central enablers of designing artificial biological systems, in the confluence of engineering and biology, that we call Synthetic biology. In the first part, let us follow their trail towards an overview of building computing machines with molecules -- and in the second part, take the case study of iGEM Greece 201...

  13. FY 1997 report on the results of the industrial technology R and D project. Development of technology to use biological resources such as the complex biological system (Development of biological use petroleum substitution fuel production technology); 1997 nendo fukugo seibutsukei nado seibutsu shigen riyo gijutsu kaihatsu seika hokokusho. Seibutsu riyo sekiyu daitai nenryo seizo gijutsu no kaihatsu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1998-03-01

    Experimental researches were conducted and the FY 1997 results were reported with the aim of establishing analytical technology for the complex biological system by which the complex biological system can be analyzed in such a state as it is using the molecular biological method. In the study of the molecular genetic analytical technology, PCR primers used for amplification of topoisomerase II genes of the whole eukaryote was designed. As to the histochemical analytical technology, a study was made on the new constitution microorganism detection method by the hybridization method and the antibody specific dyeing method, and the following were conducted: manifestation in quantity of colibacillus and the recovery, refining, and construction of peptide library by fuzzy display method. Concerning the functional analytical technology, technological researches were made such as the environmental adaptation mechanism of high thermophile and the information transfer mechanism among bacteria through cell membranes for elucidation of the special environment detection/response mechanism and the special environment adaptation/resistance mechanism. As to the separation/culture technology, various anaerobic microorganisms were separated from marine sponge for the development of a method of culturing in 3D matrices. (NEDO)

  14. Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

    Science.gov (United States)

    Weber, Bruce H

    2011-03-01

    Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.

  15. Analyzing the Biology on the System Level

    OpenAIRE

    Tong, Wei

    2016-01-01

    Although various genome projects have provided us enormous static sequence information, understanding of the sophisticated biology continues to require integrating the computational modeling, system analysis, technology development for experiments, and quantitative experiments all together to analyze the biology architecture on various levels, which is just the origin of systems biology subject. This review discusses the object, its characteristics, and research attentions in systems biology,...

  16. Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

    Science.gov (United States)

    Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

    2017-12-15

    This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

  17. Comparative systems biology between human and animal models based on next-generation sequencing methods.

    Science.gov (United States)

    Zhao, Yu-Qi; Li, Gong-Hua; Huang, Jing-Fei

    2013-04-01

    Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.

  18. Synthetic biology: programming cells for biomedical applications.

    Science.gov (United States)

    Hörner, Maximilian; Reischmann, Nadine; Weber, Wilfried

    2012-01-01

    The emerging field of synthetic biology is a novel biological discipline at the interface between traditional biology, chemistry, and engineering sciences. Synthetic biology aims at the rational design of complex synthetic biological devices and systems with desired properties by combining compatible, modular biological parts in a systematic manner. While the first engineered systems were mainly proof-of-principle studies to demonstrate the power of the modular engineering approach of synthetic biology, subsequent systems focus on applications in the health, environmental, and energy sectors. This review describes recent approaches for biomedical applications that were developed along the synthetic biology design hierarchy, at the level of individual parts, of devices, and of complex multicellular systems. It describes how synthetic biological parts can be used for the synthesis of drug-delivery tools, how synthetic biological devices can facilitate the discovery of novel drugs, and how multicellular synthetic ecosystems can give insight into population dynamics of parasites and hosts. These examples demonstrate how this new discipline could contribute to novel solutions in the biopharmaceutical industry.

  19. Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

    Science.gov (United States)

    Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

    2009-10-15

    Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated

  20. Biologically inspired collision avoidance system for unmanned vehicles

    Science.gov (United States)

    Ortiz, Fernando E.; Graham, Brett; Spagnoli, Kyle; Kelmelis, Eric J.

    2009-05-01

    In this project, we collaborate with researchers in the neuroscience department at the University of Delaware to develop an Field Programmable Gate Array (FPGA)-based embedded computer, inspired by the brains of small vertebrates (fish). The mechanisms of object detection and avoidance in fish have been extensively studied by our Delaware collaborators. The midbrain optic tectum is a biological multimodal navigation controller capable of processing input from all senses that convey spatial information, including vision, audition, touch, and lateral-line (water current sensing in fish). Unfortunately, computational complexity makes these models too slow for use in real-time applications. These simulations are run offline on state-of-the-art desktop computers, presenting a gap between the application and the target platform: a low-power embedded device. EM Photonics has expertise in developing of high-performance computers based on commodity platforms such as graphic cards (GPUs) and FPGAs. FPGAs offer (1) high computational power, low power consumption and small footprint (in line with typical autonomous vehicle constraints), and (2) the ability to implement massively-parallel computational architectures, which can be leveraged to closely emulate biological systems. Combining UD's brain modeling algorithms and the power of FPGAs, this computer enables autonomous navigation in complex environments, and further types of onboard neural processing in future applications.

  1. Characteristic responses of biological and nanoscale systems in the terahertz frequency range

    Energy Technology Data Exchange (ETDEWEB)

    Angeluts, A A; Balakin, A V; Evdokimov, M G; Ozheredov, I A; Sapozhnikov, D A; Solyankin, P M; Shkurinov, A P [International Laser Center, M. V. Lomonosov Moscow State University, Moscow (Russian Federation); Esaulkov, M N; Nazarov, M M [Institute on Laser and Information Technologies, Russian Academy of Sciences, Shatura, Moscow Region (Russian Federation); Cherkasova, O P [Institute of Laser Physics, Siberian Branch, Russian Academy of Sciences, Novosibirsk (Russian Federation)

    2014-07-31

    This paper briefly examines methods for the generation of pulsed terahertz radiation and principles of pulsed terahertz spectroscopy, an advanced informative method for studies of complex biological and nanostructured systems. Some of its practical applications are described. Using a number of steroid hormones as examples, we demonstrate that terahertz spectroscopy in combination with molecular dynamics methods and computer simulation allows one to gain information about the structure of molecules in crystals. A 'terahertz colour vision' method is proposed for analysis of pulsed terahertz signals reflected from biological tissues and it is shown that this method can be effectively used to analyse the properties of biological tissues and for early skin cancer diagnosis. (laser biophotonics)

  2. Monitoring prion protein expression in complex biological samples by SERS for diagnostic applications

    Energy Technology Data Exchange (ETDEWEB)

    Manno, D; Filippo, E; Fiore, R; Serra, A [Dipartimento di Scienza dei Materiali, Universita del Salento, Lecce (Italy); Urso, E; Rizzello, A; Maffia, M [Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Universita del Salento, Lecce (Italy)

    2010-04-23

    Surface-enhanced Raman spectroscopy (SERS) allows a new insight into the analysis of cell physiology. In this work, the difficulty of producing suitable substrates that, besides permitting the amplification of the Raman signal, do not interact with the biological material causing alteration, has been overcome by a combined method of hydrothermal green synthesis and thermal annealing. The SERS analysis of the cell membrane has been performed with special attention to the cellular prion protein PrP{sup C}. In addition, SERS has also been used to reveal the prion protein-Cu(II) interaction in four different cell models (B104, SH-SY5Y, GN11, HeLa), expressing PrP{sup C} at different levels. A significant implication of the current work consists of the intriguing possibility of revealing and quantifying prion protein expression in complex biological samples by a cheap SERS-based method, replacing the expensive and time-consuming immuno-assay systems commonly employed.

  3. Monitoring prion protein expression in complex biological samples by SERS for diagnostic applications

    International Nuclear Information System (INIS)

    Manno, D; Filippo, E; Fiore, R; Serra, A; Urso, E; Rizzello, A; Maffia, M

    2010-01-01

    Surface-enhanced Raman spectroscopy (SERS) allows a new insight into the analysis of cell physiology. In this work, the difficulty of producing suitable substrates that, besides permitting the amplification of the Raman signal, do not interact with the biological material causing alteration, has been overcome by a combined method of hydrothermal green synthesis and thermal annealing. The SERS analysis of the cell membrane has been performed with special attention to the cellular prion protein PrP C . In addition, SERS has also been used to reveal the prion protein-Cu(II) interaction in four different cell models (B104, SH-SY5Y, GN11, HeLa), expressing PrP C at different levels. A significant implication of the current work consists of the intriguing possibility of revealing and quantifying prion protein expression in complex biological samples by a cheap SERS-based method, replacing the expensive and time-consuming immuno-assay systems commonly employed.

  4. Guidelines for Reproducibly Building and Simulating Systems Biology Models.

    Science.gov (United States)

    Medley, J Kyle; Goldberg, Arthur P; Karr, Jonathan R

    2016-10-01

    Reproducibility is the cornerstone of the scientific method. However, currently, many systems biology models cannot easily be reproduced. This paper presents methods that address this problem. We analyzed the recent Mycoplasma genitalium whole-cell (WC) model to determine the requirements for reproducible modeling. We determined that reproducible modeling requires both repeatable model building and repeatable simulation. New standards and simulation software tools are needed to enhance and verify the reproducibility of modeling. New standards are needed to explicitly document every data source and assumption, and new deterministic parallel simulation tools are needed to quickly simulate large, complex models. We anticipate that these new standards and software will enable researchers to reproducibly build and simulate more complex models, including WC models.

  5. A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

    Science.gov (United States)

    Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

    2016-06-17

    Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

  6. Large, dynamic, multi-protein complexes: a challenge for structural biology

    Czech Academy of Sciences Publication Activity Database

    Rozycki, B.; Bouřa, Evžen

    2014-01-01

    Roč. 26, č. 46 (2014), 463103/1-463103/11 ISSN 0953-8984 R&D Projects: GA MŠk LO1302 EU Projects: European Commission(XE) 333916 - STARPI4K Institutional support: RVO:61388963 Keywords : protein structure * multi-protein complexes * hybrid methods of structural biology Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 2.346, year: 2014

  7. Chemometric and Statistical Analyses of ToF-SIMS Spectra of Increasingly Complex Biological Samples

    Energy Technology Data Exchange (ETDEWEB)

    Berman, E S; Wu, L; Fortson, S L; Nelson, D O; Kulp, K S; Wu, K J

    2007-10-24

    Characterizing and classifying molecular variation within biological samples is critical for determining fundamental mechanisms of biological processes that will lead to new insights including improved disease understanding. Towards these ends, time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to examine increasingly complex samples of biological relevance, including monosaccharide isomers, pure proteins, complex protein mixtures, and mouse embryo tissues. The complex mass spectral data sets produced were analyzed using five common statistical and chemometric multivariate analysis techniques: principal component analysis (PCA), linear discriminant analysis (LDA), partial least squares discriminant analysis (PLSDA), soft independent modeling of class analogy (SIMCA), and decision tree analysis by recursive partitioning. PCA was found to be a valuable first step in multivariate analysis, providing insight both into the relative groupings of samples and into the molecular basis for those groupings. For the monosaccharides, pure proteins and protein mixture samples, all of LDA, PLSDA, and SIMCA were found to produce excellent classification given a sufficient number of compound variables calculated. For the mouse embryo tissues, however, SIMCA did not produce as accurate a classification. The decision tree analysis was found to be the least successful for all the data sets, providing neither as accurate a classification nor chemical insight for any of the tested samples. Based on these results we conclude that as the complexity of the sample increases, so must the sophistication of the multivariate technique used to classify the samples. PCA is a preferred first step for understanding ToF-SIMS data that can be followed by either LDA or PLSDA for effective classification analysis. This study demonstrates the strength of ToF-SIMS combined with multivariate statistical and chemometric techniques to classify increasingly complex biological samples

  8. Macro to microfluidics system for biological environmental monitoring.

    Science.gov (United States)

    Delattre, Cyril; Allier, Cédric P; Fouillet, Yves; Jary, Dorothée; Bottausci, Frederic; Bouvier, Denis; Delapierre, Guillaume; Quinaud, Manuelle; Rival, Arnaud; Davoust, Laurent; Peponnet, Christine

    2012-01-01

    Biological environmental monitoring (BEM) is a growing field of research which challenges both microfluidics and system automation. The aim is to develop a transportable system with analysis throughput which satisfies the requirements: (i) fully autonomous, (ii) complete protocol integration from sample collection to final analysis, (iii) detection of diluted molecules or biological species in a large real life environmental sample volume, (iv) robustness and (v) flexibility and versatility. This paper discusses all these specifications in order to define an original fluidic architecture based on three connected modules, a sampling module, a sample preparation module and a detection module. The sample preparation module highly concentrates on the pathogens present in a few mL samples of complex and unknown solutions and purifies the pathogens' nucleic acids into a few μL of a controlled buffer. To do so, a two-step concentration protocol based on magnetic beads is automated in a reusable macro-to-micro fluidic system. The detection module is a PCR based miniaturized platform using digital microfluidics, where reactions are performed in 64 nL droplets handled by electrowetting on dielectric (EWOD) actuation. The design and manufacture of the two modules are reported as well as their respective performances. To demonstrate the integration of the complete protocol in the same system, first results of pathogen detection are shown. Copyright © 2012 Elsevier B.V. All rights reserved.

  9. Atomic switch networks-nanoarchitectonic design of a complex system for natural computing.

    Science.gov (United States)

    Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Aono, M; Stieg, A Z; Gimzewski, J K

    2015-05-22

    Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing-a burgeoning field that investigates the computational aptitude of complex biologically inspired systems.

  10. Ten questions about systems biology

    DEFF Research Database (Denmark)

    Joyner, Michael J; Pedersen, Bente K

    2011-01-01

    to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many......In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...

  11. Ten questions about systems biology

    DEFF Research Database (Denmark)

    Joyner, Michael J; Pedersen, Bente K

    2011-01-01

    In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist...... to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many...

  12. Intelligibility in microbial complex systems: Wittgenstein and the score of life.

    Science.gov (United States)

    Baquero, Fernando; Moya, Andrés

    2012-01-01

    Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the "score of life" metaphor is more accurate to express the complexity of living systems than the classic "book of life." Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life.

  13. Biological Recovery of Platinum Complexes from Diluted Aqueous Streams by Axenic Cultures.

    Directory of Open Access Journals (Sweden)

    Synthia Maes

    Full Text Available The widespread use of platinum in high-tech and catalytic applications has led to the production of diverse Pt loaded wastewaters. Effective recovery strategies are needed for the treatment of low concentrated waste streams to prevent pollution and to stimulate recovery of this precious resource. The biological recovery of five common environmental Pt-complexes was studied under acidic conditions; the chloro-complexes PtCl42- and PtCl62-, the amine-complex Pt(NH34Cl2 and the pharmaceutical complexes cisplatin and carboplatin. Five bacterial species were screened on their platinum recovery potential; the Gram-negative species Shewanella oneidensis MR-1, Cupriavidus metallidurans CH34, Geobacter metallireducens, and Pseudomonas stutzeri, and the Gram-positive species Bacillus toyonensis. Overall, PtCl42- and PtCl62- were completely recovered by all bacterial species while only S. oneidensis and C. metallidurans were able to recover cisplatin quantitatively (99%, all in the presence of H2 as electron donor at pH 2. Carboplatin was only partly recovered (max. 25% at pH 7, whereas no recovery was observed in the case of the Pt-tetraamine complex. Transmission electron microscopy (TEM revealed the presence of both intra- and extracellular platinum particles. Flow cytometry based microbial viability assessment demonstrated the decrease in number of intact bacterial cells during platinum reduction and indicated C. metallidurans to be the most resistant species. This study showed the effective and complete biological recovery of three common Pt-complexes, and estimated the fate and transport of the Pt-complexes in wastewater treatment plants and the natural environment.

  14. Nanoparticulate Tubular Immunostimulating Complexes: Novel Formulation of Effective Adjuvants and Antigen Delivery Systems

    Directory of Open Access Journals (Sweden)

    Nina Sanina

    2017-01-01

    Full Text Available New generation vaccines, based on isolated antigens, are safer than traditional ones, comprising the whole pathogen. However, major part of purified antigens has weak immunogenicity. Therefore, elaboration of new adjuvants, more effective and safe, is an urgent problem of vaccinology. Tubular immunostimulating complexes (TI-complexes are a new type of nanoparticulate antigen delivery systems with adjuvant activity. TI-complexes consist of cholesterol and compounds isolated from marine hydrobionts: cucumarioside A2-2 (CDA from Cucumaria japonica and monogalactosyldiacylglycerol (MGDG from marine algae or seagrass. These components were selected due to immunomodulatory and other biological activities. Glycolipid MGDG from marine macrophytes comprises a high level of polyunsaturated fatty acids (PUFAs, which demonstrate immunomodulatory properties. CDA is a well-characterized individual compound capable of forming stable complex with cholesterol. Such complexes do not possess hemolytic activity. Ultralow doses of cucumariosides stimulate cell as well as humoral immunity. Therefore, TI-complexes comprising biologically active components turned out to be more effective than the strongest adjuvants: immunostimulating complexes (ISCOMs and complete Freund’s adjuvant. In the present review, we discuss results published in series of our articles on elaboration, qualitative and quantitative composition, ultrastructure, and immunostimulating activity of TI-complexes. The review allows immersion in the history of creating TI-complexes.

  15. Genomes, Phylogeny, and Evolutionary Systems Biology

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Monica

    2005-03-25

    With the completion of the human genome and the growing number of diverse genomes being sequenced, a new age of evolutionary research is currently taking shape. The myriad of technological breakthroughs in biology that are leading to the unification of broad scientific fields such as molecular biology, biochemistry, physics, mathematics and computer science are now known as systems biology. Here I present an overview, with an emphasis on eukaryotes, of how the postgenomics era is adopting comparative approaches that go beyond comparisons among model organisms to shape the nascent field of evolutionary systems biology.

  16. Interspecies Systems Biology Uncovers Metabolites Affecting C. elegans Gene Expression and Life History Traits

    Science.gov (United States)

    Watson, Emma; MacNeil, Lesley T.; Ritter, Ashlyn D.; Yilmaz, L. Safak; Rosebrock, Adam P.; Caudy, Amy A.; Walhout, Albertha J. M.

    2014-01-01

    SUMMARY Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here we used an interspecies systems biology approach with Caenorhabditis elegans and two if its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animal’s gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development and reduces fertility, but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology. PMID:24529378

  17. Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems

    Science.gov (United States)

    Steinberg, Marc

    2011-06-01

    This paper presents a selective survey of theoretical and experimental progress in the development of biologicallyinspired approaches for complex surveillance and reconnaissance problems with multiple, heterogeneous autonomous systems. The focus is on approaches that may address ISR problems that can quickly become mathematically intractable or otherwise impractical to implement using traditional optimization techniques as the size and complexity of the problem is increased. These problems require dealing with complex spatiotemporal objectives and constraints at a variety of levels from motion planning to task allocation. There is also a need to ensure solutions are reliable and robust to uncertainty and communications limitations. First, the paper will provide a short introduction to the current state of relevant biological research as relates to collective animal behavior. Second, the paper will describe research on largely decentralized, reactive, or swarm approaches that have been inspired by biological phenomena such as schools of fish, flocks of birds, ant colonies, and insect swarms. Next, the paper will discuss approaches towards more complex organizational and cooperative mechanisms in team and coalition behaviors in order to provide mission coverage of large, complex areas. Relevant team behavior may be derived from recent advances in understanding of the social and cooperative behaviors used for collaboration by tens of animals with higher-level cognitive abilities such as mammals and birds. Finally, the paper will briefly discuss challenges involved in user interaction with these types of systems.

  18. BIOZON: a system for unification, management and analysis of heterogeneous biological data

    Directory of Open Access Journals (Sweden)

    Yona Golan

    2006-02-01

    Full Text Available Abstract Background Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability. Description Here we present a system (Biozon that addresses these problems, and offers biologists a new knowledge resource to navigate through and explore. Biozon unifies multiple biological databases consisting of a variety of data types (such as DNA sequences, proteins, interactions and cellular pathways. It is fundamentally different from previous efforts as it uses a single extensive and tightly connected graph schema wrapped with hierarchical ontology of documents and relations. Beyond warehousing existing data, Biozon computes and stores novel derived data, such as similarity relationships and functional predictions. The integration of similarity data allows propagation of knowledge through inference and fuzzy searches. Sophisticated methods of query that span multiple data types were implemented and first-of-a-kind biological ranking systems were explored and integrated. Conclusion The Biozon system is an extensive knowledge resource of heterogeneous biological data. Currently, it holds more than 100 million biological documents and 6.5 billion relations between them. The database is accessible through an advanced web interface that supports complex queries, "fuzzy" searches, data materialization and more, online at http://biozon.org.

  19. Machine learning and complex-network for personalized and systems biomedicine

    KAUST Repository

    Cannistraci, Carlo Vittorio

    2016-01-27

    The talk will begin with an introduction on using machine learning to discover hidden information and unexpected patterns in large biomedical datasets. Then, recent results on the use of complex network theory in biomedicine and neuroscience will be discussed. In particular, metagenomics and metabolomics data, approaches for drug-target repositioning, functional/structural MR connectomes and gut-brain axis data will be presented. The conclusion will outline the novel and exciting perspectives offered by the translation of these methods from systems biology to systems medicine.

  20. A study of ruthenium complexes of some biologically relevant a-N ...

    Indian Academy of Sciences (India)

    Home; Journals; Journal of Chemical Sciences; Volume 112; Issue 3. A study of ruthenium complexes of some biologically relevant ∙ -N-heterocyclic ... Author Affiliations. P Sengupta1 S Ghosh1. Department of Inorganic Chemistry, Indian Association for the Cultivation of Science, Jadavpur, Calcutta 700 032, India ...

  1. [Physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands underlying biological activities of these complexes].

    Science.gov (United States)

    Vanin, A F; Borodulin, R R; Kubrina, L N; Mikoian, V D; Burbaev, D Sh

    2013-01-01

    Current notions and new experimental data of the authors on physico-chemical features of dinitrosyl iron complexes with natural thiol-containing ligands (glutathione or cysteine), underlying the ability of the complexes to act as NO molecule and nitrosonium ion donors, are considered. This ability determines various biological activities of dinitrosyl iron complexes--inducing long-lasting vasodilation and thereby long-lasting hypotension in human and animals, inhibiting pellet aggregation, increasing red blood cell elasticity, thereby stimulating microcirculation, and reducing necrotic zone in animals with myocardial infarction. Moreover, dinitrosyl iron complexes are capable of accelerating skin wound healing, improving the function of penile cavernous tissue, blocking apoptosis development in cell cultures. When decomposed dinitrosyl iron complexes can exert cytotoxic effect that can be used for curing infectious and carcinogenic pathologies.

  2. Aspergilli: Systems biology and industrial applications

    DEFF Research Database (Denmark)

    Knuf, Christoph; Nielsen, Jens

    2012-01-01

    possible to implement systems biology tools to advance metabolic engineering. These tools include genome-wide transcription analysis and genome-scale metabolic models. Herein, we review achievements in the field and highlight the impact of Aspergillus systems biology on industrial biotechnology....

  3. How do biological systems escape 'chaotic' state?

    Indian Academy of Sciences (India)

    B J Rao

    2018-02-13

    Feb 13, 2018 ... Lorencova 2016), sociology, physics, computer science, economics and even biology ... dynamic complexity associated with them at multiple levels? .... Social anthropology and the science of chaos (Oxford: Berghahn Books).

  4. Generalized Combination Complex Synchronization for Fractional-Order Chaotic Complex Systems

    Directory of Open Access Journals (Sweden)

    Cuimei Jiang

    2015-07-01

    Full Text Available Based on two fractional-order chaotic complex drive systems and one fractional-order chaotic complex response system with different dimensions, we propose generalized combination complex synchronization. In this new synchronization scheme, there are two complex scaling matrices that are non-square matrices. On the basis of the stability theory of fractional-order linear systems, we design a general controller via active control. Additionally, by virtue of two complex scaling matrices, generalized combination complex synchronization between fractional-order chaotic complex systems and real systems is investigated. Finally, three typical examples are given to demonstrate the effectiveness and feasibility of the schemes.

  5. Integrated Network Analysis and Effective Tools in Plant Systems Biology

    Directory of Open Access Journals (Sweden)

    Atsushi eFukushima

    2014-11-01

    Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

  6. Systems biology perspectives on minimal and simpler cells.

    Science.gov (United States)

    Xavier, Joana C; Patil, Kiran Raosaheb; Rocha, Isabel

    2014-09-01

    The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  7. Systems Biology Perspectives on Minimal and Simpler Cells

    Science.gov (United States)

    Xavier, Joana C.; Patil, Kiran Raosaheb

    2014-01-01

    SUMMARY The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. PMID:25184563

  8. Data integration, systems approach and multilevel description of complex biosystems

    International Nuclear Information System (INIS)

    Hernández-Lemus, Enrique

    2013-01-01

    Recent years have witnessed the development of new quantitative approaches and theoretical tenets in the biological sciences. The advent of high throughput experiments in genomics, proteomics and electrophysiology (to cite just a few examples) have provided the researchers with unprecedented amounts of data to be analyzed. Large datasets, however can not provide the means to achieve a complete understanding of the underlying biological phenomena, unless they are supplied with a solid theoretical framework and with proper analytical tools. It is now widely accepted that by using and extending some of the paradigmatic principles of what has been called complex systems theory, some degree of advance in this direction can be attained. We will be presenting ways in which by using data integration techniques (linear, non-linear, combinatorial, graphical), multidimensional-multilevel descriptions (multifractal modeling, dimensionality reduction, computational learning), as well as an approach based in systems theory (interaction maps, probabilistic graphical models, non-equilibrium physics) have allowed us to better understand some problems in the interface of Statistical Physics and Computational Biology

  9. Model checking biological systems described using ambient calculus

    DEFF Research Database (Denmark)

    Mardare, Radu Iulian; Priami, Corrado; Qualia, Paola

    2005-01-01

    Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005.......Model checking biological systems described using ambient calculus. In Proc. of the second International Workshop on Computational Methods in Systems Biology (CMSB04), Lecture Notes in Bioinformatics 3082:85-103, Springer, 2005....

  10. Organizing principles as tools for bridging the gap between system theory and biological experimentation.

    Science.gov (United States)

    Mekios, Constantinos

    2016-04-01

    Twentieth-century theoretical efforts towards the articulation of general system properties came short of having the significant impact on biological practice that their proponents envisioned. Although the latter did arrive at preliminary mathematical formulations of such properties, they had little success in showing how these could be productively incorporated into the research agenda of biologists. Consequently, the gap that kept system-theoretic principles cut-off from biological experimentation persisted. More recently, however, simple theoretical tools have proved readily applicable within the context of systems biology. In particular, examples reviewed in this paper suggest that rigorous mathematical expressions of design principles, imported primarily from engineering, could produce experimentally confirmable predictions of the regulatory properties of small biological networks. But this is not enough for contemporary systems biologists who adopt the holistic aspirations of early systemologists, seeking high-level organizing principles that could provide insights into problems of biological complexity at the whole-system level. While the presented evidence is not conclusive about whether this strategy could lead to the realization of the lofty goal of a comprehensive explanatory integration, it suggests that the ongoing quest for organizing principles is pragmatically advantageous for systems biologists. The formalisms postulated in the course of this process can serve as bridges between system-theoretic concepts and the results of molecular experimentation: they constitute theoretical tools for generalizing molecular data, thus producing increasingly accurate explanations of system-wide phenomena.

  11. Biological Systems Thinking for Control Engineering Design

    Directory of Open Access Journals (Sweden)

    D. J. Murray-Smith

    2004-01-01

    Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

  12. Transition metal complexes of some biologically active ligands; synthesis characterization and bioactivities

    International Nuclear Information System (INIS)

    Rehman, S.; Ali, N.; Nisar, M.

    2009-01-01

    Transition/representative transition metals complexes of biologically active chelating agent 1,2-dipyrolodinoethane were synthesized and characterized through spectral and analytical data. The complexes are of the formula (M(L)X/sub 2/). Where (M = Co (II), Ni (II), Cu (II), Zn (II), Hg (II) and Cd (II) and X = CI, Br, NO/sub 3/). Tetrahedral geometry has been proposed to these-metal complexes with the help of magnetic measurements, elemental analysis, chemical stoichiometry and spectroscopic data Antibacterial activity of the ligand and its metal complexes were screened against Eschereschi coli, Klebsiello pneumonia, Proteus mirabilis, Proteus vulhari, Streptococcus pneumonia, Salmonella Iyphi, Bacilh,s anthrax, Streptococcus fecalis and Staphylococcus aureus. Complexes were found to be active against Eschereschi coli, Klebsiella pneumonia, Proteus mirabilis and Proteus vulharis. (author)

  13. Integration of systems biology with organs-on-chips to humanize therapeutic development

    Science.gov (United States)

    Edington, Collin D.; Cirit, Murat; Chen, Wen Li Kelly; Clark, Amanda M.; Wells, Alan; Trumper, David L.; Griffith, Linda G.

    2017-02-01

    "Mice are not little people" - a refrain becoming louder as the gaps between animal models and human disease become more apparent. At the same time, three emerging approaches are headed toward integration: powerful systems biology analysis of cell-cell and intracellular signaling networks in patient-derived samples; 3D tissue engineered models of human organ systems, often made from stem cells; and micro-fluidic and meso-fluidic devices that enable living systems to be sustained, perturbed and analyzed for weeks in culture. Integration of these rapidly moving fields has the potential to revolutionize development of therapeutics for complex, chronic diseases, including those that have weak genetic bases and substantial contributions from gene-environment interactions. Technical challenges in modeling complex diseases with "organs on chips" approaches include the need for relatively large tissue masses and organ-organ cross talk to capture systemic effects, such that current microfluidic formats often fail to capture the required scale and complexity for interconnected systems. These constraints drive development of new strategies for designing in vitro models, including perfusing organ models, as well as "mesofluidic" pumping and circulation in platforms connecting several organ systems, to achieve the appropriate physiological relevance.

  14. Has Neo-Darwinism failed clinical medicine: does systems biology have to?

    Science.gov (United States)

    Joyner, Michael J

    2015-01-01

    In this essay I argue that Neo-Darwinism ultimately led to an oversimplified genotype equals phenotype view of human disease. This view has been called into question by the unexpected results of the Human Genome Project which has painted a far more complex picture of the genetic features of human disease than was anticipated. Cell centric Systems Biology is now attempting to reconcile this complexity. However, it too is limited because most common chronic diseases have systemic components not predicted by their intracellular responses alone. In this context, congestive heart failure is a classic example of this general problem and I discuss it as a systemic disease vs. one solely related to dysfunctional cardiomyocytes. I close by arguing that a physiological perspective is essential to reconcile reductionism with what is required to understand and treat disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. A system for success: BMC Systems Biology, a new open access journal.

    Science.gov (United States)

    Hodgkinson, Matt J; Webb, Penelope A

    2007-09-04

    BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

  16. Hierarchical structure of biological systems: a bioengineering approach.

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems.

  17. Evaluating the biological activity of oil-polluted soils using a complex index

    Science.gov (United States)

    Kabirov, R. R.; Kireeva, N. A.; Kabirov, T. R.; Dubovik, I. Ye.; Yakupova, A. B.; Safiullina, L. M.

    2012-02-01

    A complex index characterizing the biological activity of soils (BAS) is suggested. It is based on an estimate of the level of activity of catalase; the number of heterotrophic and hydrocarbon oxidizing microorganisms, microscopic fungi, algae, and cyanobacteria; and the degree of development of higher plants and insects in the studied soil. The data on using the BAS coefficient for evaluating the efficiency of rehabilitation measures for oil-polluted soils are given. Such measures included introducing the following biological preparations: Lenoil based on a natural consortium of microorganisms Bacillus brevis and Arthrobacter sp.; the Azolen biofertilizer with complex action based on Azotobacter vinelandii; the Belvitamil biopreparation, which is the active silt of pulp and paper production; and a ready-mixed industrial association of aerobic and anaerobic microorganisms that contains hydrocarbon oxidizing microorganisms of the Arthrobacter, Bacillus, Candida, Desulfovibrio, and Pseudomonas genera.

  18. An engineering design approach to systems biology.

    Science.gov (United States)

    Janes, Kevin A; Chandran, Preethi L; Ford, Roseanne M; Lazzara, Matthew J; Papin, Jason A; Peirce, Shayn M; Saucerman, Jeffrey J; Lauffenburger, Douglas A

    2017-07-17

    Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

  19. ‘Integrative Physiology 2.0’: integration of systems biology into physiology and its application to cardiovascular homeostasis

    Science.gov (United States)

    Kuster, Diederik W D; Merkus, Daphne; van der Velden, Jolanda; Verhoeven, Adrie J M; Duncker, Dirk J

    2011-01-01

    Since the completion of the Human Genome Project and the advent of the large scaled unbiased ‘-omics’ techniques, the field of systems biology has emerged. Systems biology aims to move away from the traditional reductionist molecular approach, which focused on understanding the role of single genes or proteins, towards a more holistic approach by studying networks and interactions between individual components of networks. From a conceptual standpoint, systems biology elicits a ‘back to the future’ experience for any integrative physiologist. However, many of the new techniques and modalities employed by systems biologists yield tremendous potential for integrative physiologists to expand their tool arsenal to (quantitatively) study complex biological processes, such as cardiac remodelling and heart failure, in a truly holistic fashion. We therefore advocate that systems biology should not become/stay a separate discipline with ‘-omics’ as its playing field, but should be integrated into physiology to create ‘Integrative Physiology 2.0’. PMID:21224228

  20. Hologenomics: Systems-Level Host Biology.

    Science.gov (United States)

    Theis, Kevin R

    2018-01-01

    The hologenome concept of evolution is a hypothesis explaining host evolution in the context of the host microbiomes. As a hypothesis, it needs to be evaluated, especially with respect to the extent of fidelity of transgenerational coassociation of host and microbial lineages and the relative fitness consequences of repeated associations within natural holobiont populations. Behavioral ecologists are in a prime position to test these predictions because they typically focus on animal phenotypes that are quantifiable, conduct studies over multiple generations within natural animal populations, and collect metadata on genetic relatedness and relative reproductive success within these populations. Regardless of the conclusion on the hologenome concept as an evolutionary hypothesis, a hologenomic perspective has applied value as a systems-level framework for host biology, including in medicine. Specifically, it emphasizes investigating the multivarious and dynamic interactions between patient genomes and the genomes of their diverse microbiota when attempting to elucidate etiologies of complex, noninfectious diseases.

  1. The Feasibility of Systems Thinking in Biology Education

    Science.gov (United States)

    Boersma, Kerst; Waarlo, Arend Jan; Klaassen, Kees

    2011-01-01

    Systems thinking in biology education is an up and coming research topic, as yet with contrasting feasibility claims. In biology education systems thinking can be understood as thinking backward and forward between concrete biological objects and processes and systems models representing systems theoretical characteristics. Some studies claim that…

  2. Interspecies systems biology uncovers metabolites affecting C. elegans gene expression and life history traits.

    Science.gov (United States)

    Watson, Emma; MacNeil, Lesley T; Ritter, Ashlyn D; Yilmaz, L Safak; Rosebrock, Adam P; Caudy, Amy A; Walhout, Albertha J M

    2014-02-13

    Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here, we used an interspecies systems biology approach with Caenorhabditis elegans and two of its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animal's gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development, and reduces fertility but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid, preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Mass balances for a biological life support system simulation model

    Science.gov (United States)

    Volk, Tyler; Rummel, John D.

    1987-01-01

    Design decisions to aid the development of future space based biological life support systems (BLSS) can be made with simulation models. The biochemistry stoichiometry was developed for: (1) protein, carbohydrate, fat, fiber, and lignin production in the edible and inedible parts of plants; (2) food consumption and production of organic solids in urine, feces, and wash water by the humans; and (3) operation of the waste processor. Flux values for all components are derived for a steady state system with wheat as the sole food source. The large scale dynamics of a materially closed (BLSS) computer model is described in a companion paper. An extension of this methodology can explore multifood systems and more complex biochemical dynamics while maintaining whole system closure as a focus.

  4. Answering biological questions: Querying a systems biology database for nutrigenomics

    NARCIS (Netherlands)

    Evelo, C.T.; Bochove, K. van; Saito, J.T.

    2011-01-01

    The requirement of systems biology for connecting different levels of biological research leads directly to a need for integrating vast amounts of diverse information in general and of omics data in particular. The nutritional phenotype database addresses this challenge for nutrigenomics. A

  5. Interactomes, manufacturomes and relational biology: analogies between systems biology and manufacturing systems

    Science.gov (United States)

    2011-01-01

    Background We review and extend the work of Rosen and Casti who discuss category theory with regards to systems biology and manufacturing systems, respectively. Results We describe anticipatory systems, or long-range feed-forward chemical reaction chains, and compare them to open-loop manufacturing processes. We then close the loop by discussing metabolism-repair systems and describe the rationality of the self-referential equation f = f (f). This relationship is derived from some boundary conditions that, in molecular systems biology, can be stated as the cardinality of the following molecular sets must be about equal: metabolome, genome, proteome. We show that this conjecture is not likely correct so the problem of self-referential mappings for describing the boundary between living and nonliving systems remains an open question. We calculate a lower and upper bound for the number of edges in the molecular interaction network (the interactome) for two cellular organisms and for two manufacturomes for CMOS integrated circuit manufacturing. Conclusions We show that the relevant mapping relations may not be Abelian, and that these problems cannot yet be resolved because the interactomes and manufacturomes are incomplete. PMID:21689427

  6. Complex Systems Science for Subsurface Fate and Transport Report from the August 2009 Workshop

    Energy Technology Data Exchange (ETDEWEB)

    None

    2010-03-01

    in models can provide a basis for testing hypotheses, guiding experiment design, integrating scientific knowledge on multiple environmental systems into a common framework, and translating this information to support informed decision making and policies. Subsurface behavior typically has been investigated using reductionist, or bottom-up approaches. In these approaches, mechanisms of small-scale processes are quantified, and key aspects of their behaviors are moved up to the prediction scale using scaling laws and models. Reductionism has and will continue to yield essential and comprehensive understanding of the molecular and microscopic underpinnings of component processes. However, system-scale predictions cannot always be made with bottom-up approaches because the behaviors of subsurface environments often simply do not result from the sum of smaller-scale process interactions. Systems exhibiting such behavior are termed complex and can range from the molecular to field scale in size. Complex systems contain many interactive parts and display collective behavior including emergence, feedback, and adaptive mechanisms. Microorganisms - key moderators of subsurface chemical processes - further challenge system understanding and prediction because they are adaptive life forms existing in an environment difficult to observe and measure. A new scientific approach termed complex systems science has evolved from the critical need to understand and model these systems, whose distinguishing features increasingly are found to be common in the natural world. In contrast to reductionist approaches, complexity methods often use a top-down approach to identify key interactions controlling diagnostic variables at the prediction scale; general macroscopic laws controlling system-scale behavior; and essential, simplified models of subsystem interactions that enable prediction. This approach is analogous to systems biology, which emphasizes the tight coupling between

  7. Complex Systems Science for Subsurface Fate and Transport Report from the August 2009 Workshop

    International Nuclear Information System (INIS)

    2010-01-01

    can provide a basis for testing hypotheses, guiding experiment design, integrating scientific knowledge on multiple environmental systems into a common framework, and translating this information to support informed decision making and policies. Subsurface behavior typically has been investigated using reductionist, or bottom-up approaches. In these approaches, mechanisms of small-scale processes are quantified, and key aspects of their behaviors are moved up to the prediction scale using scaling laws and models. Reductionism has and will continue to yield essential and comprehensive understanding of the molecular and microscopic underpinnings of component processes. However, system-scale predictions cannot always be made with bottom-up approaches because the behaviors of subsurface environments often simply do not result from the sum of smaller-scale process interactions. Systems exhibiting such behavior are termed complex and can range from the molecular to field scale in size. Complex systems contain many interactive parts and display collective behavior including emergence, feedback, and adaptive mechanisms. Microorganisms - key moderators of subsurface chemical processes - further challenge system understanding and prediction because they are adaptive life forms existing in an environment difficult to observe and measure. A new scientific approach termed complex systems science has evolved from the critical need to understand and model these systems, whose distinguishing features increasingly are found to be common in the natural world. In contrast to reductionist approaches, complexity methods often use a top-down approach to identify key interactions controlling diagnostic variables at the prediction scale; general macroscopic laws controlling system-scale behavior; and essential, simplified models of subsystem interactions that enable prediction. This approach is analogous to systems biology, which emphasizes the tight coupling between experimentation and

  8. Controlling Complex Systems and Developing Dynamic Technology

    Science.gov (United States)

    Avizienis, Audrius Victor

    In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit

  9. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    Energy Technology Data Exchange (ETDEWEB)

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  10. Aluminum-Induced Entropy in Biological Systems: Implications for Neurological Disease

    Directory of Open Access Journals (Sweden)

    Christopher A. Shaw

    2014-01-01

    Full Text Available Over the last 200 years, mining, smelting, and refining of aluminum (Al in various forms have increasingly exposed living species to this naturally abundant metal. Because of its prevalence in the earth’s crust, prior to its recent uses it was regarded as inert and therefore harmless. However, Al is invariably toxic to living systems and has no known beneficial role in any biological systems. Humans are increasingly exposed to Al from food, water, medicinals, vaccines, and cosmetics, as well as from industrial occupational exposure. Al disrupts biological self-ordering, energy transduction, and signaling systems, thus increasing biosemiotic entropy. Beginning with the biophysics of water, disruption progresses through the macromolecules that are crucial to living processes (DNAs, RNAs, proteoglycans, and proteins. It injures cells, circuits, and subsystems and can cause catastrophic failures ending in death. Al forms toxic complexes with other elements, such as fluorine, and interacts negatively with mercury, lead, and glyphosate. Al negatively impacts the central nervous system in all species that have been studied, including humans. Because of the global impacts of Al on water dynamics and biosemiotic systems, CNS disorders in humans are sensitive indicators of the Al toxicants to which we are being exposed.

  11. Dynamics and thermodynamics in hierarchically organized systems applications in physics, biology and economics

    CERN Document Server

    Auger, P

    2013-01-01

    One of the most fundamental and efficient ways of conceptualizing complex systems is to organize them hierarchically. A hierarchically organized system is represented by a network of interconnected subsystems, each of which has its own network of subsystems, and so on, until some elementary subsystems are reached that are not further decomposed. This original and important book proposes a general mathematical theory of a hierarchical system and shows how it can be applied to very different topics such as physics (Hamiltonian systems), biology (coupling the molecular and the cellular levels), e

  12. Atomic switch networks—nanoarchitectonic design of a complex system for natural computing

    International Nuclear Information System (INIS)

    Demis, E C; Aguilera, R; Sillin, H O; Scharnhorst, K; Sandouk, E J; Gimzewski, J K; Aono, M; Stieg, A Z

    2015-01-01

    Self-organized complex systems are ubiquitous in nature, and the structural complexity of these natural systems can be used as a model to design new classes of functional nanotechnology based on highly interconnected networks of interacting units. Conventional fabrication methods for electronic computing devices are subject to known scaling limits, confining the diversity of possible architectures. This work explores methods of fabricating a self-organized complex device known as an atomic switch network and discusses its potential utility in computing. Through a merger of top-down and bottom-up techniques guided by mathematical and nanoarchitectonic design principles, we have produced functional devices comprising nanoscale elements whose intrinsic nonlinear dynamics and memorization capabilities produce robust patterns of distributed activity and a capacity for nonlinear transformation of input signals when configured in the appropriate network architecture. Their operational characteristics represent a unique potential for hardware implementation of natural computation, specifically in the area of reservoir computing—a burgeoning field that investigates the computational aptitude of complex biologically inspired systems. (paper)

  13. A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

    Energy Technology Data Exchange (ETDEWEB)

    Aderem, Alan; Adkins, Joshua N.; Ansong, Charles; Galagan, James; Kaiser, Shari; Korth, Marcus J.; Law, G. L.; McDermott, Jason E.; Proll, Sean; Rosenberger, Carrie; Schoolnik, Gary; Katze, Michael G.

    2011-02-01

    The 20th century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and water borne illnesses are frequent, multi-drug resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past—including the intense focus on individual genes and proteins typical of molecular biology—have not been sufficient to address these challenges. The first decade of the 21st century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program we think that the time is at hand to redefine the pathogen-host research paradigm.

  14. Novel synthesis on poly (vinyl alcohol): characterization, complexation a biological activity

    International Nuclear Information System (INIS)

    El-Sawy, N.M.; Elassar, A.Z.; Al-Fulaij, O.

    2002-01-01

    Poly(vinyl alcohol), PVA, readily condensed with phenyl hydrazine and malononitrile in basic medium to give the hydrazone and pyran derivatives, respectively. PVA reacted with chloroacetonitrile, biuet and thiophene carbonyl chloride to give modified polymeric materials. While addition of PVA to acrylonitrile and phenyl isothiocyanate gives the ether and thiocarbamate ester derivatives, respectively. Hydroxylamine hydrochloride reacted with the modified, carbonitrile containing, polymer to give the amidoxime derivative. The amidoximated products of PVA and carbamate ester of polymeric material were complexed with CUCL2 solution. The complex materials were confirmed by using UV and ESDS measurements. The morphology of PVA and complex with CUII was observed by SEM. Biological activity of some of the prepared compounds was investigated toward bacteria and fungi

  15. Systematic synergy modeling: understanding drug synergy from a systems biology perspective.

    Science.gov (United States)

    Chen, Di; Liu, Xi; Yang, Yiping; Yang, Hongjun; Lu, Peng

    2015-09-16

    Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose-response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and "omic"-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

  16. Application of computational systems biology to explore environmental toxicity hazards

    DEFF Research Database (Denmark)

    Audouze, Karine Marie Laure; Grandjean, Philippe

    2011-01-01

    Background: Computer-based modeling is part of a new approach to predictive toxicology.Objectives: We investigated the usefulness of an integrated computational systems biology approach in a case study involving the isomers and metabolites of the pesticide dichlorodiphenyltrichloroethane (DDT......) to ascertain their possible links to relevant adverse effects.Methods: We extracted chemical-protein association networks for each DDT isomer and its metabolites using ChemProt, a disease chemical biology database that includes both binding and gene expression data, and we explored protein-protein interactions...... using a human interactome network. To identify associated dysfunctions and diseases, we integrated protein-disease annotations into the protein complexes using the Online Mendelian Inheritance in Man database and the Comparative Toxicogenomics Database.Results: We found 175 human proteins linked to p,p´-DDT...

  17. Integrative radiation systems biology

    International Nuclear Information System (INIS)

    Unger, Kristian

    2014-01-01

    Maximisation of the ratio of normal tissue preservation and tumour cell reduction is the main concept of radiotherapy alone or combined with chemo-, immuno- or biologically targeted therapy. The foremost parameter influencing this ratio is radiation sensitivity and its modulation towards a more efficient killing of tumour cells and a better preservation of normal tissue at the same time is the overall aim of modern therapy schemas. Nevertheless, this requires a deep understanding of the molecular mechanisms of radiation sensitivity in order to identify its key players as potential therapeutic targets. Moreover, the success of conventional approaches that tried to statistically associate altered radiation sensitivity with any molecular phenotype such as gene expression proofed to be somewhat limited since the number of clinically used targets is rather sparse. However, currently a paradigm shift is taking place from pure frequentistic association analysis to the rather holistic systems biology approach that seeks to mathematically model the system to be investigated and to allow the prediction of an altered phenotype as the function of one single or a signature of biomarkers. Integrative systems biology also considers the data from different molecular levels such as the genome, transcriptome or proteome in order to partially or fully comprehend the causal chain of molecular mechanisms. An example for the application of this concept currently carried out at the Clinical Cooperation Group “Personalized Radiotherapy in Head and Neck Cancer” of the Helmholtz-Zentrum München and the LMU Munich is described. This review article strives for providing a compact overview on the state of the art of systems biology, its actual challenges, potential applications, chances and limitations in radiation oncology research working towards improved personalised therapy concepts using this relatively new methodology

  18. Developments in the Tools and Methodologies of Synthetic Biology

    Science.gov (United States)

    Kelwick, Richard; MacDonald, James T.; Webb, Alexander J.; Freemont, Paul

    2014-01-01

    Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community. PMID:25505788

  19. Developments in the tools and methodologies of synthetic biology

    Directory of Open Access Journals (Sweden)

    Richard eKelwick

    2014-11-01

    Full Text Available Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices or systems. However, biological systems are generally complex and unpredictable and are therefore intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a ‘body of knowledge’ from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled and its functionality tested. At each stage of the design cycle an expanding repertoire of tools is being developed. In this review we highlight several of these tools in terms of their applications and benefits to the synthetic biology community.

  20. Complexity and Chaos - State-of-the-Art; Formulations and Measures of Complexity

    Science.gov (United States)

    2007-09-01

    196] GREEN , DG. Syntactic modelling and simulation. Simulation, 1990, 54, 281-286. [197] GREEN , DG. Emergent Behaviour in Biological...Systems. In GREEN , DG; BOSSOMAIER, TJ (Eds). Complex Systems - From Biology to Computation. Amsterdam: OS Press, 1993, 24-35. [198] GREENBERG, WJ. A...Transactions on Systems, Man and Cybernetics, 1989, 19, 1073-1077. [369] RAMSEY, FP. The foundations of mathematics. London: Routledge & Kegan Paul, 1950

  1. Predicting biological system objectives de novo from internal state measurements

    Directory of Open Access Journals (Sweden)

    Maranas Costas D

    2008-01-01

    Full Text Available Abstract Background Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth and the subsequent application of linear programming (LP to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning. Results We present a novel method called Biological Objective Solution Search (BOSS for the inference of an objective function of a biological system from its underlying network stoichiometry as well as experimentally-measured state variables. Specifically, BOSS identifies a system objective by defining a putative stoichiometric "objective reaction," adding this reaction to the existing set of stoichiometric constraints arising from known interactions within a network, and maximizing the putative objective reaction via LP, all the while minimizing the difference between the resultant in silico flux distribution and available experimental (e.g., isotopomer flux data. This new approach allows for discovery of objectives with previously unknown stoichiometry, thus extending the biological relevance from earlier methods. We verify our approach on the well-characterized central metabolic network of Saccharomyces cerevisiae. Conclusion We illustrate how BOSS offers insight into the functional organization of biochemical networks

  2. Single molecule tools for enzymology, structural biology, systems biology and nanotechnology: an update

    Science.gov (United States)

    Widom, Julia R.; Dhakal, Soma; Heinicke, Laurie A.; Walter, Nils G.

    2015-01-01

    Toxicology is the highly interdisciplinary field studying the adverse effects of chemicals on living organisms. It requires sensitive tools to detect such effects. After their initial implementation during the 1990s, single-molecule fluorescence detection tools were quickly recognized for their potential to contribute greatly to many different areas of scientific inquiry. In the intervening time, technical advances in the field have generated ever-improving spatial and temporal resolution, and have enabled the application of single-molecule fluorescence to increasingly complex systems, such as live cells. In this review, we give an overview of the optical components necessary to implement the most common versions of single-molecule fluorescence detection. We then discuss current applications to enzymology and structural studies, systems biology, and nanotechnology, presenting the technical considerations that are unique to each area of study, along with noteworthy recent results. We also highlight future directions that have the potential to revolutionize these areas of study by further exploiting the capabilities of single-molecule fluorescence microscopy. PMID:25212907

  3. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    NARCIS (Netherlands)

    Mayer, Gert; Heerspink, Hiddo J. L.; Aschauer, Constantin; Heinzel, Andreas; Heinze, Georg; Kainz, Alexander; Sunzenauer, Judith; Perco, Paul; de Zeeuw, Dick; Rossing, Peter; Pena, Michelle; Oberbauer, Rainer

    OBJECTIVE: Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large

  4. Tensegrity I. Cell structure and hierarchical systems biology

    Science.gov (United States)

    Ingber, Donald E.

    2003-01-01

    In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

  5. Implementation of Complex Biological Logic Circuits Using Spatially Distributed Multicellular Consortia

    Science.gov (United States)

    Urrios, Arturo; de Nadal, Eulàlia; Solé, Ricard; Posas, Francesc

    2016-01-01

    Engineered synthetic biological devices have been designed to perform a variety of functions from sensing molecules and bioremediation to energy production and biomedicine. Notwithstanding, a major limitation of in vivo circuit implementation is the constraint associated to the use of standard methodologies for circuit design. Thus, future success of these devices depends on obtaining circuits with scalable complexity and reusable parts. Here we show how to build complex computational devices using multicellular consortia and space as key computational elements. This spatial modular design grants scalability since its general architecture is independent of the circuit’s complexity, minimizes wiring requirements and allows component reusability with minimal genetic engineering. The potential use of this approach is demonstrated by implementation of complex logical functions with up to six inputs, thus demonstrating the scalability and flexibility of this method. The potential implications of our results are outlined. PMID:26829588

  6. Inorganic concepts relevant to metal binding, activity, and toxicity in a biological system

    Energy Technology Data Exchange (ETDEWEB)

    Hoeschele, J.D. (Warner-Lambert Co., Ann Arbor, MI (USA). Parke-Davis Pharmaceutical Research Div.); Turner, J.E.; England, M.W. (Oak Ridge National Lab., TN (USA))

    1990-01-01

    The purpose of this paper is to review selected physical and inorganic concepts and factors which might be important in assessing and/or understanding the fact and disposition of a metal system in a biological environment. Hopefully, such inquiries will ultimately permit us to understand, rationalize, and predict differences and trends in biological effects as a function of the basic nature of a metal system and, in optimal cases, serve as input to a system of guidelines for the notion of Chemical Dosimetry.'' The plan of this paper is to first review, in general terms, the basic principles of the Crystal Field Theory (CFT), a unifying theory of bonding in metal complexes. This will provide the necessary theoretical background for the subsequent discussion of selected concepts and factors. 21 refs., 7 figs., 6 tabs.

  7. Bioremediation 3.0: Engineering pollutant-removing bacteria in the times of systemic biology

    DEFF Research Database (Denmark)

    Dvořák, Pavel; Nikel, Pablo Ivan; Damborskýc, Jiří

    2017-01-01

    pollutants with no external intervention, the onset of genetic engineering in the 1980s allowed the possibility of rational design of bacteria to catabolize specific compounds, which could eventually be released into the environment as bioremediation agents. The complexity of this endeavour and the lack...... of fundamental knowledge nonetheless led to the virtual abandonment of such a recombinant DNA-based bioremediation only a decade later. In a twist of events, the last few years have witnessed the emergence of new systemic fields (including systems and synthetic biology, and metabolic engineering) that allow....... In this article, we analyze how contemporary systemic biology is helping to take the design of bioremediation agents back to the core of environmental biotechnology. We inspect a number of recent strategies for catabolic pathway construction and optimization and we bring them together by proposing an engineering...

  8. Characterising the Development of the Understanding of Human Body Systems in High-School Biology Students--A Longitudinal Study

    Science.gov (United States)

    Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

    2017-01-01

    Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated…

  9. Metabolomics: Definitions and Significance in Systems Biology.

    Science.gov (United States)

    Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

    2017-01-01

    Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

  10. Synthesis, characterization and biological assay of Salicylaldehyde Schiff base Cu(II) complexes and their precursors

    Science.gov (United States)

    Iftikhar, Bushra; Javed, Kanwal; Khan, Muhammad Saif Ullah; Akhter, Zareen; Mirza, Bushra; Mckee, Vickie

    2018-03-01

    Three new Schiff base ligands were synthesized by the reaction of Salicylaldehyde with semi-aromatic diamines, prepared by the reduction of corresponding dinitro-compounds, and were further used for the formation of complexes with Cu(II) metal ion. The structural features of the synthesized compounds were confirmed by their physical properties and infrared, electronic and NMR spectroscopic techniques. The studies revealed that the synthesized Schiff bases existed as tetradentate ligands and bonded to the metal ion through the phenolic oxygen and azomethine nitrogen. One of the dinitro precursors was also analyzed by single crystal X-ray crystallography, which showed that it crystallizes in monoclinic system with space group P2/n. The thermal behavior of the Cu(II) complexes was determined by thermogravimetric analysis (TGA) and kinetic parameters were evaluated from the data. Schiff base ligands, their precursors and metal complexes were also screened for antibacterial, antifungal, antitumor, Brine shrimp lethality, DPPH free radical scavenging and DNA damage assays. The results of these analyses indicated the substantial potential of the synthesized Schiff bases, their precursors and Cu(II) complexes in biological field as future drugs.

  11. USBF-system of biological wastewater treatment; Elsistema USBF en la depuracion biologica de aguas residuales

    Energy Technology Data Exchange (ETDEWEB)

    Ampudia Gutierrez, J.

    2003-07-01

    An advanced system of biological wastewater treatment, has been developed by the company Depuralia. This system brings up a technological innovation, which has been awarded with several international awards. The wastewater treatment, occurs in an activated sludge reactor of extended aeration with a very low mass loading, with a nitrification-denitrification process, and water separation-clarification by upflow sludge blanket-filtration. The arrangement of a compact biological reactor enables complex wastewater treatment. High efficiency of the separation through sludge filtration provides functionality of the equipment with high concentration of activated sludge, with less implementation surface and volume. The elements of the biological reactor are described, the advantages are enumerated, and the results obtained in several accomplishments are shown; in the industrial as well as in the urban water treatment plants. (Author) 9 refs.

  12. Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

    Science.gov (United States)

    Loppini, Alessandro

    2018-03-01

    Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

  13. Synchronization in complex networks

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.; Diaz-Guilera, A.; Moreno, Y.; Zhou, C.; Kurths, J.

    2007-12-12

    Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analytical approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.

  14. Mathematical models in biology bringing mathematics to life

    CERN Document Server

    Ferraro, Maria; Guarracino, Mario

    2015-01-01

    This book presents an exciting collection of contributions based on the workshop “Bringing Maths to Life” held October 27-29, 2014 in Naples, Italy.  The state-of-the art research in biology and the statistical and analytical challenges facing huge masses of data collection are treated in this Work. Specific topics explored in depth surround the sessions and special invited sessions of the workshop and include genetic variability via differential expression, molecular dynamics and modeling, complex biological systems viewed from quantitative models, and microscopy images processing, to name several. In depth discussions of the mathematical analysis required to extract insights from complex bodies of biological datasets, to aid development in the field novel algorithms, methods and software tools for genetic variability, molecular dynamics, and complex biological systems are presented in this book. Researchers and graduate students in biology, life science, and mathematics/statistics will find the content...

  15. The female gametophyte: an emerging model for cell type-specific systems biology in plant development

    Directory of Open Access Journals (Sweden)

    Marc William Schmid

    2015-11-01

    Full Text Available Systems biology, a holistic approach describing a system emerging from the interactions of its molecular components, critically depends on accurate qualitative determination and quantitative measurements of these components. Development and improvement of large-scale profiling methods (omics now facilitates comprehensive measurements of many relevant molecules. For multicellular organisms, such as animals, fungi, algae, and plants, the complexity of the system is augmented by the presence of specialized cell types and organs, and a complex interplay within and between them. Cell type-specific analyses are therefore crucial for the understanding of developmental processes and environmental responses. This review first gives an overview of current methods used for large-scale profiling of specific cell types exemplified by recent advances in plant biology. The focus then lies on suitable model systems to study plant development and cell type specification. We introduce the female gametophyte of flowering plants as an ideal model to study fundamental developmental processes. Moreover, the female reproductive lineage is of importance for the emergence of evolutionary novelties such as an unequal parental contribution to the tissue nurturing the embryo or the clonal production of seeds by asexual reproduction (apomixis. Understanding these processes is not only interesting from a developmental or evolutionary perspective, but bears great potential for further crop improvement and the simplification of breeding efforts. We finally highlight novel methods, which are already available or which will likely soon facilitate large-scale profiling of the specific cell types of the female gametophyte in both model and non-model species. We conclude that it may take only few years until an evolutionary systems biology approach toward female gametogenesis may decipher some of its biologically most interesting and economically most valuable processes.

  16. Synthesis, characterization and biological activities of semicarbazones and their copper complexes.

    Science.gov (United States)

    Venkatachalam, Taracad K; Bernhardt, Paul V; Noble, Chris J; Fletcher, Nicholas; Pierens, Gregory K; Thurecht, Kris J; Reutens, David C

    2016-09-01

    Substituted semicarbazones/thiosemicarbazones and their copper complexes have been prepared and several single crystal structures examined. The copper complexes of these semicarbazone/thiosemicarbazones were prepared and several crystal structures examined. The single crystal X-ray structure of the pyridyl-substituted semicarbazone showed two types of copper complexes, a monomer and a dimer. We also found that the p-nitrophenyl semicarbazone formed a conventional 'magic lantern' acetate-bridged dimer. Electron Paramagnetic Resonance (EPR) of several of the copper complexes was consistent with the results of single crystal X-ray crystallography. The EPR spectra of the p-nitrophenyl semicarbazone copper complex in dimethylsulfoxide (DMSO) showed the presence of two species, confirming the structural information. Since thiosemicarbazones and semicarbazones have been reported to exhibit anticancer activity, we examined the anticancer activity of several of the derivatives reported in the present study and interestingly only the thiosemicarbazone showed activity while the semicarbazones were not active indicating that introduction of sulphur atom alters the biological profile of these thiosemicarbazones. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

    Science.gov (United States)

    Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

    2012-01-01

    Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

  18. Y-12 National Security Complex Biological Monitoring and Abatement Program 2007 Calendar Yeare Report

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, M.J.; Greeley, M. S. Jr.; Morris, G. W.; Roy, W. K.; Ryan, M. G.; Smith, J. G.; Southworth, G. R.

    2008-07-01

    The National Pollutant Discharge Elimination System (NPDES) permit issued for the Oak Ridge Y-12 National Security Complex (Y-12 Complex) which became effective May 1, 2006, continued a requirement for a Biological Monitoring and Abatement Program (BMAP). The BMAP was originally developed in 1985 to demonstrate that the effluent limitations established for the Y-12 Complex protected the classified uses of the receiving stream (East Fork Poplar Creek: EFPC), in particular, the growth and propagation of aquatic life (Loar et al. 1989). The objectives of the current BMAP are similar, specifically to assess stream ecological conditions relative to regulatory limits and criteria, to assess ecological impacts as well as recovery in response to Y-12 operations, and to investigate the causes of continuing impacts. The BMAP consists of three tasks that reflect complementary approaches to evaluating the effects of the Y-12 Complex discharges on the biotic integrity of EFPC. These tasks include: (1) bioaccumulation monitoring, (2) benthic macroinvertebrate community monitoring, and (3) fish community monitoring. As required by the NPDES permit, the BMAP benthic macroinvertebrate community monitoring task includes studies to annually evaluate the receiving stream's biological integrity in comparison to TN Water Quality Criteria. BMAP monitoring is currently being conducted at five primary EFPC sites, although sites may be excluded or added depending upon the specific objectives of the various tasks. Criteria used in selecting the sites include: (1) location of sampling sites used in other studies, (2) known or suspected sources of downstream impacts, (3) proximity to U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) boundaries, (4) appropriate habitat distribution, and (5) access. The primary sampling sites include upper EFPC at kilometers (EFKs) 24.4 and 23.4 [upstream and downstream of Lake Reality (LR) respectively]; EFK 18.7 (also EFK 18.2 and 19), located

  19. Animal protein production modules in biological life support systems: Novel combined aquaculture techniques based on the closed equilibrated biological aquatic system (C.E.B.A.S.)

    Science.gov (United States)

    Blüm, V.; Andriske, M.; Kreuzberg, K.; Schreibman, M. P.

    Based on the experiences made with the Closed Equilibrated Biological Aquatic System (C.E.B.A.S.) which was primarily deveoloped for long-term and multi-generation experiments with aquatic animals and plants in a space station highly effective fresh water recycling modules were elaborated utilizing a combination of ammonia oxidizing bacteria filters and higher plants. These exhibit a high effectivity to eliminate phosphate and anorganic nitrogen compounds and arc. in addidition. able to contribute to the oxygen supply of the aquatic animals. The C.E.B.A.S. filter system is able to keep a closed artificial aquatic ecosystem containing teleost fishes and water snails biologically stable for several month and to eliminate waste products deriving from degraded dead fishes without a decrease of the oxygen concentration down to less than 3.5 mg/l at 25 °C. More advanced C.E.B.A.S. filter systems, the BIOCURE filters, were also developed for utilization in semiintensive and intensive aquaculture systems for fishes. In fact such combined animal-plant aquaculture systems represent highly effective productions sites for human food if proper plant and fish species are selected The present papers elucidates ways to novel aquaculture systems in which herbivorous fishes are raised by feeding them with plant biomass produced in the BIOCURE filters and presents the scheme of a modification which utilizes a plant species suitable also for human nutrition. Special attention is paid to the benefits of closed aquaculture system modules which may be integrated into bioregenerative life support systems of a higher complexity for, e. g.. lunar or planetary bases including some psychologiccal aspects of the introduction of animal protein production into plant-based life support systems. Moreover, the basic reproductive biological problems of aquatic animal breeding under reduced gravity are explained leading to a disposition of essential research programs in this context.

  20. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  1. Efficient Bayesian estimates for discrimination among topologically different systems biology models.

    Science.gov (United States)

    Hagen, David R; Tidor, Bruce

    2015-02-01

    A major effort in systems biology is the development of mathematical models that describe complex biological systems at multiple scales and levels of abstraction. Determining the topology-the set of interactions-of a biological system from observations of the system's behavior is an important and difficult problem. Here we present and demonstrate new methodology for efficiently computing the probability distribution over a set of topologies based on consistency with existing measurements. Key features of the new approach include derivation in a Bayesian framework, incorporation of prior probability distributions of topologies and parameters, and use of an analytically integrable linearization based on the Fisher information matrix that is responsible for large gains in efficiency. The new method was demonstrated on a collection of four biological topologies representing a kinase and phosphatase that operate in opposition to each other with either processive or distributive kinetics, giving 8-12 parameters for each topology. The linearization produced an approximate result very rapidly (CPU minutes) that was highly accurate on its own, as compared to a Monte Carlo method guaranteed to converge to the correct answer but at greater cost (CPU weeks). The Monte Carlo method developed and applied here used the linearization method as a starting point and importance sampling to approach the Bayesian answer in acceptable time. Other inexpensive methods to estimate probabilities produced poor approximations for this system, with likelihood estimation showing its well-known bias toward topologies with more parameters and the Akaike and Schwarz Information Criteria showing a strong bias toward topologies with fewer parameters. These results suggest that this linear approximation may be an effective compromise, providing an answer whose accuracy is near the true Bayesian answer, but at a cost near the common heuristics.

  2. Structural Identifiability of Dynamic Systems Biology Models.

    Science.gov (United States)

    Villaverde, Alejandro F; Barreiro, Antonio; Papachristodoulou, Antonis

    2016-10-01

    A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areas.

  3. Modeling Complex Systems

    CERN Document Server

    Boccara, Nino

    2010-01-01

    Modeling Complex Systems, 2nd Edition, explores the process of modeling complex systems, providing examples from such diverse fields as ecology, epidemiology, sociology, seismology, and economics. It illustrates how models of complex systems are built and provides indispensable mathematical tools for studying their dynamics. This vital introductory text is useful for advanced undergraduate students in various scientific disciplines, and serves as an important reference book for graduate students and young researchers. This enhanced second edition includes: . -recent research results and bibliographic references -extra footnotes which provide biographical information on cited scientists who have made significant contributions to the field -new and improved worked-out examples to aid a student’s comprehension of the content -exercises to challenge the reader and complement the material Nino Boccara is also the author of Essentials of Mathematica: With Applications to Mathematics and Physics (Springer, 2007).

  4. Impact of Thermodynamic Principles in Systems Biology

    NARCIS (Netherlands)

    Heijnen, J.J.

    2010-01-01

    It is shown that properties of biological systems which are relevant for systems biology motivated mathematical modelling are strongly shaped by general thermodynamic principles such as osmotic limit, Gibbs energy dissipation, near equilibria and thermodynamic driving force. Each of these aspects

  5. Programming Morphogenesis through Systems and Synthetic Biology.

    Science.gov (United States)

    Velazquez, Jeremy J; Su, Emily; Cahan, Patrick; Ebrahimkhani, Mo R

    2018-04-01

    Mammalian tissue development is an intricate, spatiotemporal process of self-organization that emerges from gene regulatory networks of differentiating stem cells. A major goal in stem cell biology is to gain a sufficient understanding of gene regulatory networks and cell-cell interactions to enable the reliable and robust engineering of morphogenesis. Here, we review advances in synthetic biology, single cell genomics, and multiscale modeling, which, when synthesized, provide a framework to achieve the ambitious goal of programming morphogenesis in complex tissues and organoids. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Empirical and theoretical analysis of complex systems

    Science.gov (United States)

    Zhao, Guannan

    This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group

  7. Biological significance of complex N-glycans in plants and their impact on plant physiology.

    Science.gov (United States)

    Strasser, Richard

    2014-01-01

    Asparagine (N)-linked protein glycosylation is a ubiquitous co- and post-translational modification which can alter the biological function of proteins and consequently affects the development, growth, and physiology of organisms. Despite an increasing knowledge of N-glycan biosynthesis and processing, we still understand very little about the biological function of individual N-glycan structures in plants. In particular, the N-glycan-processing steps mediated by Golgi-resident enzymes create a structurally diverse set of protein-linked carbohydrate structures. Some of these complex N-glycan modifications like the presence of β1,2-xylose, core α1,3-fucose or the Lewis a-epitope are characteristic for plants and are evolutionary highly conserved. In mammals, complex N-glycans are involved in different cellular processes including molecular recognition and signaling events. In contrast, the complex N-glycan function is still largely unknown in plants. Here, in this short review, I focus on important recent developments and discuss their implications for future research in plant glycobiology and plant biotechnology.

  8. Spatial transcriptomics: paving the way for tissue-level systems biology.

    Science.gov (United States)

    Moor, Andreas E; Itzkovitz, Shalev

    2017-08-01

    The tissues in our bodies are complex systems composed of diverse cell types that often interact in highly structured repeating anatomical units. External gradients of morphogens, directional blood flow, as well as the secretion and absorption of materials by cells generate distinct microenvironments at different tissue coordinates. Such spatial heterogeneity enables optimized function through division of labor among cells. Unraveling the design principles that govern this spatial division of labor requires techniques to quantify the entire transcriptomes of cells while accounting for their spatial coordinates. In this review we describe how recent advances in spatial transcriptomics open the way for tissue-level systems biology. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. The Systems Biology Research Tool: evolvable open-source software

    Directory of Open Access Journals (Sweden)

    Wright Jeremiah

    2008-06-01

    Full Text Available Abstract Background Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. Results We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. Conclusion The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability, to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.

  10. Systems biology: An emerging strategy for discovering novel pathogenetic mechanisms that promote cardiovascular disease

    OpenAIRE

    Maron, Bradley A.; Leopold, Jane A.

    2016-01-01

    Reductionist theory proposes that analyzing complex systems according to their most fundamental components is required for problem resolution, and has served as the cornerstone of scientific methodology for more than four centuries. However, technological gains in the current scientific era now allow for the generation of large datasets that profile the proteomic, genomic, and metabolomic signatures of biological systems across a range of conditions. The accessibility of data on such a vast s...

  11. The Origin and Evolution of Complex Enough Systems in Biology

    OpenAIRE

    Brändas, Erkki

    2017-01-01

    Recent criticisms of Neo-Darwinism are considered and disputed within the setting of recent advances in chemical physics. A related query, viz., the ontological thesis, that everything is physical, confronts a crucial test on the validity of reductionism as a fundamental approach to science.  While traditional ‘physicalism’ interprets evolution as a sequence of physical accidents governed by the second law of thermodynamics, the concepts of biology concern processes that owe their goal-direct...

  12. Systems biology approaches and tools for analysis of interactomes and multi-target drugs.

    Science.gov (United States)

    Schrattenholz, André; Groebe, Karlfried; Soskic, Vukic

    2010-01-01

    Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex

  13. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    Science.gov (United States)

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R.L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  14. Computational Modeling of Biological Systems From Molecules to Pathways

    CERN Document Server

    2012-01-01

    Computational modeling is emerging as a powerful new approach for studying and manipulating biological systems. Many diverse methods have been developed to model, visualize, and rationally alter these systems at various length scales, from atomic resolution to the level of cellular pathways. Processes taking place at larger time and length scales, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. Computational Modeling of Biological Systems: From Molecules to Pathways provides an overview of established computational methods for the modeling of biologically and medically relevant systems. It is suitable for researchers and professionals working in the fields of biophysics, computational biology, systems biology, and molecular medicine.

  15. Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

    Science.gov (United States)

    Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

    2015-03-01

    The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

  16. Metal-containing Complexes of Lactams, Imidazoles, and Benzimidazoles and Their Biological Activity

    Science.gov (United States)

    Kukalenko, S. S.; Bovykin, B. A.; Shestakova, S. I.; Omel'chenko, A. M.

    1985-07-01

    The results of the latest investigations of the problem of the synthesis of metal-containing complexes of lactams, imidazoles, and benzimidazoles, their structure, and their stability in solutions are surveyed. Some data on their biological activity (pesticide and pharmacological) and the mechanism of their physiological action are presented. The bibliography includes 190 references.

  17. Complex Systems: An Introduction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...

  18. Synthesis, spectroscopic and biological studies of transition metal complexes of novel schiff bases derived from amoxicillin and sugars

    International Nuclear Information System (INIS)

    Naz, N.

    2009-01-01

    Fe (II), Co (II) and Ni (II) metal complexes of new Schiff bases derived from amoxicillin with sugars (D-Glucose, D-Galactose and D-Mannose) have been synthesized and characterized by elemental analysis, FTIR, electronic absorption, and atomic absorption spectroscopy, magnetic moment measurements and thermal analysis. It has been found that Schiff bases behave as bi-dentate ligands forming complexes with 1:2 (metal:ligand) stoichiometry. The complexes were neutral as confirmed by their low conductance values. The biological applications of complexes have been studied on two gram negative (Escherichia coli and Pseudomonas aeruginosa) and two gram positive (Bacillus subtilis and Staphylococcus aureus) microorganisms by Agar diffusion disc method. It has been found that all the complexes have higher biological activities than the pure amoxicillin. (author)

  19. Insect-gene-activity detection system for chemical and biological warfare agents and toxic industrial chemicals

    Science.gov (United States)

    Mackie, Ryan S.; Schilling, Amanda S.; Lopez, Arturo M.; Rayms-Keller, Alfredo

    2002-02-01

    Detection of multiple chemical and biological weapons (CBW) agents and/or complex mixtures of toxic industrial chemicals (TIC) is imperative for both the commercial and military sectors. In a military scenario, a multi-CBW attack would create confusion, thereby delaying decontamination and therapeutic efforts. In the commercial sector, polluted sites invariably contain a mixture of TIC. Novel detection systems capable of detecting CBW and TIC are sorely needed. While it may be impossible to build a detector capable of discriminating all the possible combinations of CBW, a detection system capable of statistically predicting the most likely composition of a given mixture is within the reach of current emerging technologies. Aquatic insect-gene activity may prove to be a sensitive, discriminating, and elegant paradigm for the detection of CBW and TIC. We propose to systematically establish the expression patterns of selected protein markers in insects exposed to specific mixtures of chemical and biological warfare agents to generate a library of biosignatures of exposure. The predicting capabilities of an operational library of biosignatures of exposures will allow the detection of emerging novel or genetically engineered agents, as well as complex mixtures of chemical and biological weapons agents. CBW and TIC are discussed in the context of war, terrorism, and pollution.

  20. Biologic activity of porphyromonas endodontalis complex lipids.

    Science.gov (United States)

    Mirucki, Christopher S; Abedi, Mehran; Jiang, Jin; Zhu, Qiang; Wang, Yu-Hsiung; Safavi, Kamran E; Clark, Robert B; Nichols, Frank C

    2014-09-01

    Periapical infections secondary to pulpal necrosis are associated with bacterial contamination of the pulp. Porphyromonas endodontalis, a gram-negative organism, is considered to be a pulpal pathogen. P. gingivalis is phylogenetically related to P. endodontalis and synthesizes several classes of novel complex lipids that possess biological activity, including the capacity to promote osteoclastogenesis and osteoclast activation. The purpose of this study was to extract and characterize constituent lipids of P. endodontalis and evaluate their capacity to promote proinflammatory secretory responses in the macrophage cell line, RAW 264.7, as well as their capacity to promote osteoclastogenesis and inhibit osteoblast activity. Constituent lipids of both organisms were fractionated by high-performance liquid chromatography and were structurally characterized using electrospray mass spectrometry or electrospray-mass spectrometry/mass spectrometry. The virulence potential of P. endodontalis lipids was then compared with known biologically active lipids isolated from P. gingivalis. P. endodontalis total lipids were shown to promote tumor necrosis factor alpha secretion from RAW 264.7 cells, and the serine lipid fraction appeared to account for the majority of this effect. P. endodontalis lipid preparations also increased osteoclast formation from RAW 264.7 cells, but osteoblast differentiation in culture was inhibited and appeared to be dependent on Toll-like receptor 2 expression. These effects underscore the importance of P. endodontalis lipids in promoting inflammatory and bone cell activation processes that could lead to periapical pathology. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  1. Complex Systems and Dependability

    CERN Document Server

    Zamojski, Wojciech; Sugier, Jaroslaw

    2012-01-01

    Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth

  2. Decisions, dopamine, and degeneracy in complex biological systems

    Directory of Open Access Journals (Sweden)

    Regan CM

    2014-01-01

    Full Text Available Ciaran M Regan School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, Dublin, Ireland Abstract: The neurobiological and computational analysis of value-based decision-making rests within the domain of neuroeconomics which has the goal of providing a biological account of human behavior relevant to both natural and social sciences. This review proposes a framework to investigate different aspects of the theoretical and molecular neurobiology of decision-making. In order to learn how to make good decisions, the brain needs to compute a separate value signal that measures the desirability of the outcomes that were generated by its previous decisions. The framework presented here combines aspects of current ideas relating to information processing by the hippocampal formation and how these relate to the phasic midbrain dopaminergic firing that occurs in response to the spatial and motivational aspects of rewarding events in the environment. The activities of hippocampal ensembles are considered to reflect a continuous updating process for attended experiences, defining both regular and irregular stimuli, environments, and actions, that are rapidly encoded as schemas into pre-existing knowledge bases. Keywords: hippocampus, schemas, synapse assemblies, cell assemblies, synapse plasticity

  3. Optoelectronic system and apparatus for connection to biological systems

    Science.gov (United States)

    Okandan, Murat; Nielson, Gregory N.

    2018-03-06

    The present invention relates to a biological probe structure, as well as apparatuses, systems, and methods employing this structure. In particular embodiments, the structure includes a hermetically sealed unit configured to receive and transmit one or more optical signals. Furthermore, the structure can be implanted subcutaneously and interrogated externally. In this manner, a minimally invasive method can be employed to detect, treat, and/or assess the biological target. Additional methods and systems are also provided.

  4. Quantum Biology

    Directory of Open Access Journals (Sweden)

    Alessandro Sergi

    2009-06-01

    Full Text Available A critical assessment of the recent developmentsof molecular biology is presented.The thesis that they do not lead to a conceptualunderstanding of life and biological systems is defended.Maturana and Varela's concept of autopoiesis is briefly sketchedand its logical circularity avoided by postulatingthe existence of underlying living processes,entailing amplification from the microscopic to the macroscopic scale,with increasing complexity in the passage from one scale to the other.Following such a line of thought, the currently accepted model of condensed matter, which is based on electrostatics and short-ranged forces,is criticized. It is suggested that the correct interpretationof quantum dispersion forces (van der Waals, hydrogen bonding, and so onas quantum coherence effects hints at the necessity of includinglong-ranged forces (or mechanisms for them incondensed matter theories of biological processes.Some quantum effects in biology are reviewedand quantum mechanics is acknowledged as conceptually important to biology since withoutit most (if not all of the biological structuresand signalling processes would not even exist. Moreover, it is suggested that long-rangequantum coherent dynamics, including electron polarization,may be invoked to explain signal amplificationprocess in biological systems in general.

  5. A review of imaging techniques for systems biology

    Directory of Open Access Journals (Sweden)

    Po Ming J

    2008-08-01

    Full Text Available Abstract This paper presents a review of imaging techniques and of their utility in system biology. During the last decade systems biology has matured into a distinct field and imaging has been increasingly used to enable the interplay of experimental and theoretical biology. In this review, we describe and compare the roles of microscopy, ultrasound, CT (Computed Tomography, MRI (Magnetic Resonance Imaging, PET (Positron Emission Tomography, and molecular probes such as quantum dots and nanoshells in systems biology. As a unified application area among these different imaging techniques, examples in cancer targeting are highlighted.

  6. Adaptive generalized combination complex synchronization of uncertain real and complex nonlinear systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shi-bing, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xing-yuan, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xiu-you [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Zhou, Yu-fei [College of Electrical Engineering and Automation, Anhui University, Hefei 230601 (China)

    2016-04-15

    With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complexsystem, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.

  7. Management of complex dynamical systems

    Science.gov (United States)

    MacKay, R. S.

    2018-02-01

    Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

  8. General method to find the attractors of discrete dynamic models of biological systems

    Science.gov (United States)

    Gan, Xiao; Albert, Réka

    2018-04-01

    Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

  9. General method to find the attractors of discrete dynamic models of biological systems.

    Science.gov (United States)

    Gan, Xiao; Albert, Réka

    2018-04-01

    Analyzing the long-term behaviors (attractors) of dynamic models of biological networks can provide valuable insight. We propose a general method that can find the attractors of multilevel discrete dynamical systems by extending a method that finds the attractors of a Boolean network model. The previous method is based on finding stable motifs, subgraphs whose nodes' states can stabilize on their own. We extend the framework from binary states to any finite discrete levels by creating a virtual node for each level of a multilevel node, and describing each virtual node with a quasi-Boolean function. We then create an expanded representation of the multilevel network, find multilevel stable motifs and oscillating motifs, and identify attractors by successive network reduction. In this way, we find both fixed point attractors and complex attractors. We implemented an algorithm, which we test and validate on representative synthetic networks and on published multilevel models of biological networks. Despite its primary motivation to analyze biological networks, our motif-based method is general and can be applied to any finite discrete dynamical system.

  10. 1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

    International Nuclear Information System (INIS)

    Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D.

    2011-01-01

    The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in 1 H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

  11. A system for success: BMC Systems Biology, a new open access journal

    OpenAIRE

    Webb Penelope A; Hodgkinson Matt J

    2007-01-01

    Abstract BMC Systems Biology is the first open access journal spanning the growing field of systems biology from molecules up to ecosystems. The journal has launched as more and more institutes are founded that are similarly dedicated to this new approach. BMC Systems Biology builds on the ongoing success of the BMC series, providing a venue for all sound research in the systems-level analysis of biology.

  12. Systems biology of neutrophil differentiation and immune response

    DEFF Research Database (Denmark)

    Theilgaard-Mönch, Kim; Porse, Bo T; Borregaard, Niels

    2005-01-01

    Systems biology has emerged as a new scientific field, which aims at investigating biological processes at the genomic and proteomic levels. Recent studies have unravelled aspects of neutrophil differentiation and immune responses at the systems level using high-throughput technologies. These stu......Systems biology has emerged as a new scientific field, which aims at investigating biological processes at the genomic and proteomic levels. Recent studies have unravelled aspects of neutrophil differentiation and immune responses at the systems level using high-throughput technologies....... These studies have identified a plethora of novel effector proteins stored in the granules of neutrophils. In addition, these studies provide evidence that neutrophil differentiation and immune response are governed by a highly coordinated transcriptional programme that regulates cellular fate and function...

  13. Biological Potential in Serpentinizing Systems

    Science.gov (United States)

    Hoehler, Tori M.

    2016-01-01

    Generation of the microbial substrate hydrogen during serpentinization, the aqueous alteration of ultramafic rocks, has focused interest on the potential of serpentinizing systems to support biological communities or even the origin of life. However the process also generates considerable alkalinity, a challenge to life, and both pH and hydrogen concentrations vary widely across natural systems as a result of different host rock and fluid composition and differing physical and hydrogeologic conditions. Biological potential is expected to vary in concert. We examined the impact of such variability on the bioenergetics of an example metabolism, methanogenesis, using a cell-scale reactive transport model to compare rates of metabolic energy generation as a function of physicochemical environment. Potential rates vary over more than 5 orders of magnitude, including bioenergetically non-viable conditions, across the range of naturally occurring conditions. In parallel, we assayed rates of hydrogen metabolism in wells associated with the actively serpentinizing Coast Range Ophiolite, which includes conditions more alkaline and considerably less reducing than is typical of serpentinizing systems. Hydrogen metabolism is observed at pH approaching 12 but, consistent with the model predictions, biological methanogenesis is not observed.

  14. Control of complex systems

    CERN Document Server

    Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo

    2001-01-01

    The world of artificial systems is reaching complexity levels that es­ cape human understanding. Surface traffic, electricity distribution, air­ planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi­ neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re­ search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu­ ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...

  15. Synchronization in node of complex networks consist of complex chaotic system

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

    2014-07-15

    A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

  16. On the limitations of standard statistical modeling in biological systems: a full Bayesian approach for biology.

    Science.gov (United States)

    Gomez-Ramirez, Jaime; Sanz, Ricardo

    2013-09-01

    One of the most important scientific challenges today is the quantitative and predictive understanding of biological function. Classical mathematical and computational approaches have been enormously successful in modeling inert matter, but they may be inadequate to address inherent features of biological systems. We address the conceptual and methodological obstacles that lie in the inverse problem in biological systems modeling. We introduce a full Bayesian approach (FBA), a theoretical framework to study biological function, in which probability distributions are conditional on biophysical information that physically resides in the biological system that is studied by the scientist. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. BetaWB - A language for modular representation of biological systems

    DEFF Research Database (Denmark)

    Ihekwaba, Adoha; Larcher, Roberto; Mardare, Radu Iulian

    2007-01-01

    A. Ihekwaba, R. Larcher, R. Mardare, C. Priami. BetaWB - A language for modular representation of biological systems. In Proc. of International Conference on Systems Biology (ICSB), 2007......A. Ihekwaba, R. Larcher, R. Mardare, C. Priami. BetaWB - A language for modular representation of biological systems. In Proc. of International Conference on Systems Biology (ICSB), 2007...

  18. Y-12 National Security Complex Biological Monitoring And Abatement Program 2008 Calendar Year Report

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, M. J.; Greeley Jr., M. S.; Mathews, T. J.; Morris, G. W.; Roy, W. K.; Ryon, M. G.; Smith, J. G.; Southworth, G. R.

    2009-07-01

    The National Pollutant Discharge Elimination System (NPDES) permit issued for the Oak Ridge Y-12 National Security Complex (Y-12 Complex) which became effective May 1, 2006, continued a requirement for a Biological Monitoring and Abatement Program (BMAP). The BMAP was originally developed in 1985 to demonstrate that the effluent limitations established for the Y-12 Complex protected the classified uses of the receiving stream (East Fork Poplar Creek: EFPC), in particular, the growth and propagation of aquatic life (Loar et al. 1989). The objectives of the current BMAP are similar, specifically to assess stream ecological conditions relative to regulatory limits and criteria, to assess ecological impacts as well as recovery in response to Y-12 operations, and to investigate the causes of continuing impacts. The BMAP consists of three tasks that reflect complementary approaches to evaluating the effects of the Y-12 Complex discharges on the biotic integrity of EFPC. These tasks include: (1) bioaccumulation monitoring, (2) benthic macroinvertebrate community monitoring, and (3) fish community monitoring. As required by the NPDES permit, the BMAP benthic macroinvertebrate community monitoring task includes studies to annually evaluate the receiving stream's biological integrity in comparison to TN Water Quality Criteria. BMAP monitoring is currently being conducted at five primary EFPC sites, although sites may be excluded or added depending upon the specific objectives of the various tasks. Criteria used in selecting the sites include: (1) location of sampling sites used in other studies, (2) known or suspected sources of downstream impacts, (3) proximity to U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) boundaries, (4) appropriate habitat distribution, and (5) access. The primary sampling sites include upper EFPC at kilometers (EFKs) 24.4 and 23.4 [upstream and downstream of Lake Reality (LR) respectively]; EFK 18.7 (also EFK 18.2 and 19), located off

  19. Genetic coding and united-hypercomplex systems in the models of algebraic biology.

    Science.gov (United States)

    Petoukhov, Sergey V

    2017-08-01

    Structured alphabets of DNA and RNA in their matrix form of representations are connected with Walsh functions and a new type of systems of multidimensional numbers. This type generalizes systems of complex numbers and hypercomplex numbers, which serve as the basis of mathematical natural sciences and many technologies. The new systems of multi-dimensional numbers have interesting mathematical properties and are called in a general case as "systems of united-hypercomplex numbers" (or briefly "U-hypercomplex numbers"). They can be widely used in models of multi-parametrical systems in the field of algebraic biology, artificial life, devices of biological inspired artificial intelligence, etc. In particular, an application of U-hypercomplex numbers reveals hidden properties of genetic alphabets under cyclic permutations in their doublets and triplets. A special attention is devoted to the author's hypothesis about a multi-linguistic in DNA-sequences in a relation with an ensemble of U-numerical sub-alphabets. Genetic multi-linguistic is considered as an important factor to provide noise-immunity properties of the multi-channel genetic coding. Our results attest to the conformity of the algebraic properties of the U-numerical systems with phenomenological properties of the DNA-alphabets and with the complementary device of the double DNA-helix. It seems that in the modeling field of algebraic biology the genetic-informational organization of living bodies can be considered as a set of united-hypercomplex numbers in some association with the famous slogan of Pythagoras "the numbers rule the world". Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Biological Screening of Newly Synthesized BIAN N-Heterocyclic Gold Carbene Complexes in Zebrafish Embryos

    Science.gov (United States)

    Farooq, Muhammad; Abu Taha, Nael; Butorac, Rachel R.; Evans, Daniel Anthony; Elzatahry, Ahmed A.; Elsayed, Elsayed Ahmed; Wadaan, Mohammad A. M.; Al-Deyab, Salem S.; Cowley, Alan H.

    2015-01-01

    N-Heterocyclic carbene (NHC) metal complexes possess diverse biological activities but have yet to be extensively explored as potential chemotherapeutic agents. We have previously reported the synthesis of a new class of NHC metal complexes N-heterocyclic with acetate [IPr(BIAN)AuOAc] and chloride [IPr(BIAN)AuCl] ligands. In the experiments reported herein, the zebrafish embryos were exposed to serial dilutions of each of these complexes for 10–12 h. One hundred percent mortality was observed at concentrations ≥50 µM. At sub-lethal concentrations (10–30 µM), both compounds influenced zebrafish embryonic development. However, quite diverse categories of abnormalities were found in exposed embryos with each compound. Severe brain deformation and notochord degeneration were evident in the case of [IPr(BIAN)AuOAc]. The zebrafish embryos treated with [IPr(BIAN)AuCl] exhibited stunted growth and consequently had smaller body sizes. A depletion of 30%–40% glutathione was detected in the treated embryos, which could account for one of the possible mechanism of neurotoxicity. The fact that these compounds are capable of both affecting the growth and also compromising antioxidant systems by elevating intracellular ROS production implies that they could play an important role as a new breed of therapeutic molecules. PMID:26501273

  1. Multi-agent and complex systems

    CERN Document Server

    Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

    2017-01-01

    This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

  2. Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

    Science.gov (United States)

    Ewing, Tracy S.

    The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

  3. 3S - Systematic, systemic, and systems biology and toxicology.

    Science.gov (United States)

    Smirnova, Lena; Kleinstreuer, Nicole; Corvi, Raffaella; Levchenko, Andre; Fitzpatrick, Suzanne C; Hartung, Thomas

    2018-01-01

    A biological system is more than the sum of its parts - it accomplishes many functions via synergy. Deconstructing the system down to the molecular mechanism level necessitates the complement of reconstructing functions on all levels, i.e., in our conceptualization of biology and its perturbations, our experimental models and computer modelling. Toxicology contains the somewhat arbitrary subclass "systemic toxicities"; however, there is no relevant toxic insult or general disease that is not systemic. At least inflammation and repair are involved that require coordinated signaling mechanisms across the organism. However, the more body components involved, the greater the challenge to reca-pitulate such toxicities using non-animal models. Here, the shortcomings of current systemic testing and the development of alternative approaches are summarized. We argue that we need a systematic approach to integrating existing knowledge as exemplified by systematic reviews and other evidence-based approaches. Such knowledge can guide us in modelling these systems using bioengineering and virtual computer models, i.e., via systems biology or systems toxicology approaches. Experimental multi-organ-on-chip and microphysiological systems (MPS) provide a more physiological view of the organism, facilitating more comprehensive coverage of systemic toxicities, i.e., the perturbation on organism level, without using substitute organisms (animals). The next challenge is to establish disease models, i.e., micropathophysiological systems (MPPS), to expand their utility to encompass biomedicine. Combining computational and experimental systems approaches and the chal-lenges of validating them are discussed. The suggested 3S approach promises to leverage 21st century technology and systematic thinking to achieve a paradigm change in studying systemic effects.

  4. Strategies for structuring interdisciplinary education in Systems Biology

    DEFF Research Database (Denmark)

    Cvijovic, Marija; Höfer, Thomas; Aćimović, Jure

    2016-01-01

    function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material...... and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active...... performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii...

  5. Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

    Science.gov (United States)

    Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E; Conolly, Rory B

    2010-02-01

    The new paradigm envisioned for toxicity testing in the 21st century advocates shifting from the current animal-based testing process to a combination of in vitro cell-based studies, high-throughput techniques, and in silico modeling. A strategic component of the vision is the adoption of the systems biology approach to acquire, analyze, and interpret toxicity pathway data. As key toxicity pathways are identified and their wiring details elucidated using traditional and high-throughput techniques, there is a pressing need to understand their qualitative and quantitative behaviors in response to perturbation by both physiological signals and exogenous stressors. The complexity of these molecular networks makes the task of understanding cellular responses merely by human intuition challenging, if not impossible. This process can be aided by mathematical modeling and computer simulation of the networks and their dynamic behaviors. A number of theoretical frameworks were developed in the last century for understanding dynamical systems in science and engineering disciplines. These frameworks, which include metabolic control analysis, biochemical systems theory, nonlinear dynamics, and control theory, can greatly facilitate the process of organizing, analyzing, and understanding toxicity pathways. Such analysis will require a comprehensive examination of the dynamic properties of "network motifs"--the basic building blocks of molecular circuits. Network motifs like feedback and feedforward loops appear repeatedly in various molecular circuits across cell types and enable vital cellular functions like homeostasis, all-or-none response, memory, and biological rhythm. These functional motifs and associated qualitative and quantitative properties are the predominant source of nonlinearities observed in cellular dose response data. Complex response behaviors can arise from toxicity pathways built upon combinations of network motifs. While the field of computational cell

  6. Reduction of Subjective and Objective System Complexity

    Science.gov (United States)

    Watson, Michael D.

    2015-01-01

    Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached

  7. Increase of Organization in Complex Systems

    OpenAIRE

    Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder

    2013-01-01

    Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...

  8. Redefining plant systems biology: from cell to ecosystem

    NARCIS (Netherlands)

    Keurentjes, J.J.B.; Angenent, G.C.; Dicke, M.; Martins Dos Santos, V.A.P.; Molenaar, J.; Van der Putten, W.H.; de Ruiter, P.C.; Struik, P.C.; Thomma, B.P.H.J.

    2011-01-01

    Molecular biologists typically restrict systems biology to cellular levels. By contrast, ecologists define biological systems as communities of interacting individuals at different trophic levels that process energy, nutrient and information flows. Modern plant breeding needs to increase

  9. Anti-synchronization between different chaotic complex systems

    International Nuclear Information System (INIS)

    Liu Ping; Liu Shutang

    2011-01-01

    Many studies on the anti-synchronization of nonlinear real dynamic systems have been carried out, whereas the anti-synchronization of chaotic complex systems has not been studied extensively. In this work, the anti-synchronization between a new chaotic complex system and a complex Lorenz system and that between a new chaotic complex system and a complex Lue system were separately investigated by active control and nonlinear control methods, and explicit expressions were derived for the controllers that are used to achieve the anti-synchronization of chaotic complex systems. These expressions were tested numerically and excellent agreement was found. Concerning the new chaotic complex system, we discuss its dynamical properties including dissipation, chaotic behavior, fixed points, and their stability and invariance.

  10. Complexity of Economical Systems

    Directory of Open Access Journals (Sweden)

    G. P. Pavlos

    2015-01-01

    Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.

  11. A Friendly-Biological Reactor SIMulator (BioReSIM for studying biological processes in wastewater treatment processes

    Directory of Open Access Journals (Sweden)

    Raul Molina

    2014-12-01

    Full Text Available Biological processes for wastewater treatments are inherently dynamic systems because of the large variations in the influent wastewater flow rate, concentration composition and the adaptive behavior of the involved microorganisms. Moreover, the sludge retention time (SRT is a critical factor to understand the bioreactor performances when changes in the influent or in the operation conditions take place. Since SRT are usually in the range of 10-30 days, the performance of biological reactors needs a long time to be monitored in a regular laboratory demonstration, limiting the knowledge that can be obtained in the experimental lab practice. In order to overcome this lack, mathematical models and computer simulations are useful tools to describe biochemical processes and predict the overall performance of bioreactors under different working operation conditions and variations of the inlet wastewater composition. The mathematical solution of the model could be difficult as numerous biochemical processes can be considered. Additionally, biological reactors description (mass balance, etc. needs models represented by partial or/and ordinary differential equations associated to algebraic expressions, that require complex computational codes to obtain the numerical solutions. Different kind of software for mathematical modeling can be used, from large degree of freedom simulators capable of free models definition (as AQUASIM, to closed predefined model structure programs (as BIOWIN. The first ones usually require long learning curves, whereas the second ones could be excessively rigid for specific wastewater treatment systems. As alternative, we present Biological Reactor SIMulator (BioReSIM, a MATLAB code for the simulation of sequencing batch reactors (SBR and rotating biological contactors (RBC as biological systems of suspended and attached biomass for wastewater treatment, respectively. This BioReSIM allows the evaluation of simple and complex

  12. Challenges and rewards on the road to translational systems biology in acute illness: four case reports from interdisciplinary teams.

    Science.gov (United States)

    An, Gary; Hunt, C Anthony; Clermont, Gilles; Neugebauer, Edmund; Vodovotz, Yoram

    2007-06-01

    Translational systems biology approaches can be distinguished from mainstream systems biology in that their goal is to drive novel therapies and streamline clinical trials in critical illness. One systems biology approach, dynamic mathematical modeling (DMM), is increasingly used in dealing with the complexity of the inflammatory response and organ dysfunction. The use of DMM often requires a broadening of research methods and a multidisciplinary team approach that includes bioscientists, mathematicians, engineers, and computer scientists. However, the development of these groups must overcome domain-specific barriers to communication and understanding. We present 4 case studies of successful translational, interdisciplinary systems biology efforts, which differ by organizational level from an individual to an entire research community. Case 1 is a single investigator involved in DMM of the acute inflammatory response at Cook County Hospital, in which extensive translational progress was made using agent-based models of inflammation and organ damage. Case 2 is a community-level effort from the University of Witten-Herdecke in Cologne, whose efforts have led to the formation of the Society for Complexity in Acute Illness. Case 3 is an institution-based group, the Biosystems Group at the University of California, San Francisco, whose work has included a focus on a common lexicon for DMM. Case 4 is an institution-based, transdisciplinary research group (the Center for Inflammation and Regenerative Modeling at the University of Pittsburgh), whose modeling work has led to internal education efforts, grant support, and commercialization. A transdisciplinary approach, which involves team interaction in an iterative fashion to address ambiguity and is supported by educational initiatives, is likely to be necessary for DMM in acute illness. Communitywide organizations such as the Society of Complexity in Acute Illness must strive to facilitate the implementation of DMM in

  13. Electromagnetic fields in biological systems

    National Research Council Canada - National Science Library

    Lin, James C

    2012-01-01

    "Focusing on exposure, induced fields, and absorbed energy, this volume covers the interaction of electromagnetic fields and waves with biological systems, spanning static fields to terahertz waves...

  14. Tunable promoters in synthetic and systems biology

    DEFF Research Database (Denmark)

    Dehli, Tore; Solem, Christian; Jensen, Peter Ruhdal

    2012-01-01

    in synthetic biology. A number of tools exist to manipulate the steps in between gene sequence and functional protein in living cells, but out of these the most straight-forward approach is to alter the gene expression level by manipulating the promoter sequence. Some of the promoter tuning tools available......Synthetic and systems biologists need standardized, modular and orthogonal tools yielding predictable functions in vivo. In systems biology such tools are needed to quantitatively analyze the behavior of biological systems while the efficient engineering of artificial gene networks is central...... for accomplishing such altered gene expression levels are discussed here along with examples of their use, and ideas for new tools are described. The road ahead looks very promising for synthetic and systems biologists as tools to achieve just about anything in terms of tuning and timing multiple gene expression...

  15. Supporting cognition in systems biology analysis: findings on users' processes and design implications.

    Science.gov (United States)

    Mirel, Barbara

    2009-02-13

    Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

  16. Modeling Complex Systems

    International Nuclear Information System (INIS)

    Schreckenberg, M

    2004-01-01

    This book by Nino Boccara presents a compilation of model systems commonly termed as 'complex'. It starts with a definition of the systems under consideration and how to build up a model to describe the complex dynamics. The subsequent chapters are devoted to various categories of mean-field type models (differential and recurrence equations, chaos) and of agent-based models (cellular automata, networks and power-law distributions). Each chapter is supplemented by a number of exercises and their solutions. The table of contents looks a little arbitrary but the author took the most prominent model systems investigated over the years (and up until now there has been no unified theory covering the various aspects of complex dynamics). The model systems are explained by looking at a number of applications in various fields. The book is written as a textbook for interested students as well as serving as a comprehensive reference for experts. It is an ideal source for topics to be presented in a lecture on dynamics of complex systems. This is the first book on this 'wide' topic and I have long awaited such a book (in fact I planned to write it myself but this is much better than I could ever have written it!). Only section 6 on cellular automata is a little too limited to the author's point of view and one would have expected more about the famous Domany-Kinzel model (and more accurate citation!). In my opinion this is one of the best textbooks published during the last decade and even experts can learn a lot from it. Hopefully there will be an actualization after, say, five years since this field is growing so quickly. The price is too high for students but this, unfortunately, is the normal case today. Nevertheless I think it will be a great success! (book review)

  17. A data integration approach for cell cycle analysis oriented to model simulation in systems biology

    Directory of Open Access Journals (Sweden)

    Mosca Ettore

    2007-08-01

    Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

  18. Systems and complexity thinking in the general practice literature: an integrative, historical narrative review.

    Science.gov (United States)

    Sturmberg, Joachim P; Martin, Carmel M; Katerndahl, David A

    2014-01-01

    Over the past 7 decades, theories in the systems and complexity sciences have had a major influence on academic thinking and research. We assessed the impact of complexity science on general practice/family medicine. We performed a historical integrative review using the following systematic search strategy: medical subject heading [humans] combined in turn with the terms complex adaptive systems, nonlinear dynamics, systems biology, and systems theory, limited to general practice/family medicine and published before December 2010. A total of 16,242 articles were retrieved, of which 49 were published in general practice/family medicine journals. Hand searches and snowballing retrieved another 35. After a full-text review, we included 56 articles dealing specifically with systems sciences and general/family practice. General practice/family medicine engaged with the emerging systems and complexity theories in 4 stages. Before 1995, articles tended to explore common phenomenologic general practice/family medicine experiences. Between 1995 and 2000, articles described the complex adaptive nature of this discipline. Those published between 2000 and 2005 focused on describing the system dynamics of medical practice. After 2005, articles increasingly applied the breadth of complex science theories to health care, health care reform, and the future of medicine. This historical review describes the development of general practice/family medicine in relation to complex adaptive systems theories, and shows how systems sciences more accurately reflect the discipline's philosophy and identity. Analysis suggests that general practice/family medicine first embraced systems theories through conscious reorganization of its boundaries and scope, before applying empirical tools. Future research should concentrate on applying nonlinear dynamics and empirical modeling to patient care, and to organizing and developing local practices, engaging in community development, and influencing

  19. Synthetic Biology: Engineering Living Systems from Biophysical Principles.

    Science.gov (United States)

    Bartley, Bryan A; Kim, Kyung; Medley, J Kyle; Sauro, Herbert M

    2017-03-28

    Synthetic biology was founded as a biophysical discipline that sought explanations for the origins of life from chemical and physical first principles. Modern synthetic biology has been reinvented as an engineering discipline to design new organisms as well as to better understand fundamental biological mechanisms. However, success is still largely limited to the laboratory and transformative applications of synthetic biology are still in their infancy. Here, we review six principles of living systems and how they compare and contrast with engineered systems. We cite specific examples from the synthetic biology literature that illustrate these principles and speculate on their implications for further study. To fully realize the promise of synthetic biology, we must be aware of life's unique properties. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  20. Human Development V: Biochemistry Unable to Explain the Emergence of Biological Form (Morphogenesis and Therefore a New Principle as Source of Biological Information is Needed

    Directory of Open Access Journals (Sweden)

    Søren Ventegodt

    2006-01-01

    Full Text Available Today's biomedicine builds on the conviction that biochemistry can explain the creation of the body, its anatomy and physiology. Unfortunately there are still deep mysteries strangely “fighting back” when we try to define and understand the organism and its creation in the ontogenesis as emerging from biochemistry. In analysing this from a theoretical perspective using a mathematical model focusing on the noise in complex chemical systems we argue that evolving biological structure cannot in principle be a product of chemistry. In this paper we go through the chemical gradient model and argue that this is not able to explain the ontogenesis. We discuss the used gradients as information carriers in chemical self-organizing systems and argue that by use of the “Turing structures” we are only able to modelling the mostly simple biological systems. The bio-chemical model is only able to model simple organization but not to explain the complexity of biological phenomena. We conclude that we seemingly have presented a formal proof (a NO-GO theorem that the self-organizing chemical systems that are using chemical gradients are not able to explain complex biological matters as the ontogenesis. We need a fundamentally new, information-carrying principle to understand biological information and biological order.

  1. Complexity in Dynamical Systems

    Science.gov (United States)

    Moore, Cristopher David

    The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

  2. Complex logistics audit system

    Directory of Open Access Journals (Sweden)

    Zuzana Marková

    2010-02-01

    Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

  3. The aims of systems biology: between molecules and organisms.

    Science.gov (United States)

    Noble, D

    2011-05-01

    The systems approach to biology has a long history. Its recent rapid resurgence at the turn of the century reflects the problems encountered in interpreting the sequencing of the genome and the failure of that immense achievement to provide rapid and direct solutions to major multi-factorial diseases. This paper argues that systems biology is necessarily multilevel and that there is no privileged level of causality in biological systems. It is an approach rather than a separate discipline. Functionality arises from biological networks that interact with the genome, the environment and the phenotype. This view of biology is very different from the gene-centred views of neo-Darwinism and molecular biology. In neuroscience, the systems approach leads naturally to 2 important conclusions: first, that the idea of 'programs' in the brain is confusing, and second, that the self is better interpreted as a process than as an object. © Georg Thieme Verlag KG Stuttgart · New York.

  4. Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

    Science.gov (United States)

    Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

    2017-10-01

    Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

  5. Kinetics of the Dynamical Information Shannon Entropy for Complex Systems

    International Nuclear Information System (INIS)

    Yulmetyev, R.M.; Yulmetyeva, D.G.

    1999-01-01

    Kinetic behaviour of dynamical information Shannon entropy is discussed for complex systems: physical systems with non-Markovian property and memory in correlation approximation, and biological and physiological systems with sequences of the Markovian and non-Markovian random noises. For the stochastic processes, a description of the information entropy in terms of normalized time correlation functions is given. The influence and important role of two mutually dependent channels of the entropy change, correlation (creation or generation of correlations) and anti-correlation (decay or annihilation of correlation) is discussed. The method developed here is also used in analysis of the density fluctuations in liquid cesium obtained from slow neutron scattering data, fractal kinetics of the long-range fluctuation in the short-time human memory and chaotic dynamics of R-R intervals of human ECG. (author)

  6. The Physics of Proteins An Introduction to Biological Physics and Molecular Biophysics

    CERN Document Server

    Frauenfelder, Hans; Chan, Winnie S

    2010-01-01

    Physics and the life sciences have established new connections within the past few decades, resulting in biological physics as an established subfield with strong groups working in many physics departments. These interactions between physics and biology form a two-way street with physics providing new tools and concepts for understanding life, while biological systems can yield new insights into the physics of complex systems. To address the challenges of this interdisciplinary area, The Physics of Proteins: An Introduction to Biological Physics and Molecular Biophysics is divided into three interconnected sections. In Parts I and II, early chapters introduce the terminology and describe the main biological systems that physicists will encounter. Similarities between biomolecules, glasses, and solids are stressed with an emphasis on the fundamental concepts of living systems. The central section (Parts III and IV) delves into the dynamics of complex systems. A main theme is the realization that biological sys...

  7. Measuring Complexity of SAP Systems

    Directory of Open Access Journals (Sweden)

    Ilja Holub

    2016-10-01

    Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.

  8. European Conference on Complex Systems

    CERN Document Server

    Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela

    2016-01-01

    This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.

  9. Systems Biology: Impressions from a Newcomer Graduate Student in 2016

    Science.gov (United States)

    Simpson, Melanie Rae

    2016-01-01

    As a newcomer, the philosophical basis of systems biology seems intuitive and appealing, the underlying philosophy being that the whole of a living system cannot be completely understood by the study of its individual parts. Yet answers to the questions "What is systems biology?" and "What constitutes a systems biology approach in…

  10. Synthetic Biology: Putting Synthesis into Biology

    Science.gov (United States)

    Liang, Jing; Luo, Yunzi; Zhao, Huimin

    2010-01-01

    The ability to manipulate living organisms is at the heart of a range of emerging technologies that serve to address important and current problems in environment, energy, and health. However, with all its complexity and interconnectivity, biology has for many years been recalcitrant to engineering manipulations. The recent advances in synthesis, analysis, and modeling methods have finally provided the tools necessary to manipulate living systems in meaningful ways, and have led to the coining of a field named synthetic biology. The scope of synthetic biology is as complicated as life itself – encompassing many branches of science, and across many scales of application. New DNA synthesis and assembly techniques have made routine the customization of very large DNA molecules. This in turn has allowed the incorporation of multiple genes and pathways. By coupling these with techniques that allow for the modeling and design of protein functions, scientists have now gained the tools to create completely novel biological machineries. Even the ultimate biological machinery – a self-replicating organism – is being pursued at this moment. It is the purpose of this review to dissect and organize these various components of synthetic biology into a coherent picture. PMID:21064036

  11. TissueCypher™: A systems biology approach to anatomic pathology

    Directory of Open Access Journals (Sweden)

    Jeffrey W Prichard

    2015-01-01

    Full Text Available Background: Current histologic methods for diagnosis are limited by intra- and inter-observer variability. Immunohistochemistry (IHC methods are frequently used to assess biomarkers to aid diagnoses, however, IHC staining is variable and nonlinear and the manual interpretation is subjective. Furthermore, the biomarkers assessed clinically are typically biomarkers of epithelial cell processes. Tumors and premalignant tissues are not composed only of epithelial cells but are interacting systems of multiple cell types, including various stromal cell types that are involved in cancer development. The complex network of the tissue system highlights the need for a systems biology approach to anatomic pathology, in which quantification of system processes is combined with informatics tools to produce actionable scores to aid clinical decision-making. Aims: Here, we describe a quantitative, multiplexed biomarker imaging approach termed TissueCypher™ that applies systems biology to anatomic pathology. Applications of TissueCypher™ in understanding the tissue system of Barrett's esophagus (BE and the potential use as an adjunctive tool in the diagnosis of BE are described. Patients and Methods: The TissueCypher™ Image Analysis Platform was used to assess 14 epithelial and stromal biomarkers with known diagnostic significance in BE in a set of BE biopsies with nondysplastic BE with reactive atypia (RA, n = 22 and Barrett's with high-grade dysplasia (HGD, n = 17. Biomarker and morphology features were extracted and evaluated in the confirmed BE HGD cases versus the nondysplastic BE cases with RA. Results: Multiple image analysis features derived from epithelial and stromal biomarkers, including immune biomarkers and morphology, showed significant differences between HGD and RA. Conclusions: The assessment of epithelial cell abnormalities combined with an assessment of cellular changes in the lamina propria may serve as an adjunct to conventional

  12. Epidemic processes in complex networks

    OpenAIRE

    Pastor Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

    2015-01-01

    In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The t...

  13. Mathematical methods in systems biology.

    Science.gov (United States)

    Kashdan, Eugene; Duncan, Dominique; Parnell, Andrew; Schattler, Heinz

    2016-12-01

    The editors of this Special Issue of Mathematical Biosciences and Engineering were the organizers for the Third International Workshop "Mathematical Methods in System Biology" that took place on June 15-18, 2015 at the University College Dublin in Ireland. As stated in the workshop goals, we managed to attract a good mix of mathematicians and statisticians working on biological and medical applications with biologists and clinicians interested in presenting their challenging problems and looking to find mathematical and statistical tools for their solutions.

  14. Nanoscale technology in biological systems

    CERN Document Server

    Greco, Ralph S; Smith, R Lane

    2004-01-01

    Reviewing recent accomplishments in the field of nanobiology Nanoscale Technology in Biological Systems introduces the application of nanoscale matrices to human biology. It focuses on the applications of nanotechnology fabrication to biomedical devices and discusses new physical methods for cell isolation and manipulation and intracellular communication at the molecular level. It also explores the application of nanobiology to cardiovascular diseases, oncology, transplantation, and a range of related disciplines. This book build a strong background in nanotechnology and nanobiology ideal for

  15. Reversible photochromic system based on rhodamine B salicylaldehyde hydrazone metal complex.

    Science.gov (United States)

    Li, Kai; Xiang, Yu; Wang, Xiaoyan; Li, Ji; Hu, Rongrong; Tong, Aijun; Tang, Ben Zhong

    2014-01-29

    Photochromic molecules are widely applied in chemistry, physics, biology, and materials science. Although a few photochromic systems have been developed before, their applications are still limited by complicated synthesis, low fatigue resistance, or incomplete light conversion. Rhodamine is a class of dyes with excellent optical properties including long-wavelength absorption, large absorption coefficient, and high photostability in its ring-open form. It is an ideal chromophore for the development of new photochromic systems. However, known photochromic rhodamine derivatives, such as amides, exhibit only millisecond lifetimes in their colored ring-open forms, making their application very limited and difficult. In this work, rhodamine B salicylaldehyde hydrazone metal complex was found to undergo intramolecular ring-open reactions upon UV irradiation, which led to a distinct color and fluorescence change both in solution and in solid matrix. The complex showed good fatigue resistance for the reversible photochromism and long lifetime for the ring-open state. Interestingly, the thermal bleaching rate was tunable by using different metal ions, temperatures, solvents, and chemical substitutions. It was proposed that UV light promoted isomerization of the rhodamine B derivative from enol-form to keto-form, which induced ring-opening of the rhodamine spirolactam in the complex to generate color. The photochromic system was successfully applied for photoprinting and UV strength measurement in the solid state. As compared to other reported photochromic molecules, the system in this study has its advantages of facile synthesis and tunable thermal bleaching rate, and also provides new insights into the development of photochromic materials based on metal complex and spirolactam-containing dyes.

  16. Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

    Science.gov (United States)

    Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

    2018-06-06

    The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

  17. Review of Biological Network Data and Its Applications

    Directory of Open Access Journals (Sweden)

    Donghyeon Yu

    2013-12-01

    Full Text Available Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

  18. MIDAS: A Modular DNA Assembly System for Synthetic Biology.

    Science.gov (United States)

    van Dolleweerd, Craig J; Kessans, Sarah A; Van de Bittner, Kyle C; Bustamante, Leyla Y; Bundela, Rudranuj; Scott, Barry; Nicholson, Matthew J; Parker, Emily J

    2018-04-20

    A modular and hierarchical DNA assembly platform for synthetic biology based on Golden Gate (Type IIS restriction enzyme) cloning is described. This enabling technology, termed MIDAS (for Modular Idempotent DNA Assembly System), can be used to precisely assemble multiple DNA fragments in a single reaction using a standardized assembly design. It can be used to build genes from libraries of sequence-verified, reusable parts and to assemble multiple genes in a single vector, with full user control over gene order and orientation, as well as control of the direction of growth (polarity) of the multigene assembly, a feature that allows genes to be nested between other genes or genetic elements. We describe the detailed design and use of MIDAS, exemplified by the reconstruction, in the filamentous fungus Penicillium paxilli, of the metabolic pathway for production of paspaline and paxilline, key intermediates in the biosynthesis of a range of indole diterpenes-a class of secondary metabolites produced by several species of filamentous fungi. MIDAS was used to efficiently assemble a 25.2 kb plasmid from 21 different modules (seven genes, each composed of three basic parts). By using a parts library-based system for construction of complex assemblies, and a unique set of vectors, MIDAS can provide a flexible route to assembling tailored combinations of genes and other genetic elements, thereby supporting synthetic biology applications in a wide range of expression hosts.

  19. Systems biology at work

    NARCIS (Netherlands)

    Martins Dos Santos, V.A.P.; Damborsky, J.

    2010-01-01

    In his editorial overview for the 2008 Special Issue on this topic, the late Jaroslav Stark pointedly noted that systems biology is no longer a niche pursuit, but a recognized discipline in its own right “noisily” coming of age [1]. Whilst general underlying principles and basic techniques are now

  20. Scale relativity theory and integrative systems biology: 2. Macroscopic quantum-type mechanics.

    Science.gov (United States)

    Nottale, Laurent; Auffray, Charles

    2008-05-01

    In these two companion papers, we provide an overview and a brief history of the multiple roots, current developments and recent advances of integrative systems biology and identify multiscale integration as its grand challenge. Then we introduce the fundamental principles and the successive steps that have been followed in the construction of the scale relativity theory, which aims at describing the effects of a non-differentiable and fractal (i.e., explicitly scale dependent) geometry of space-time. The first paper of this series was devoted, in this new framework, to the construction from first principles of scale laws of increasing complexity, and to the discussion of some tentative applications of these laws to biological systems. In this second review and perspective paper, we describe the effects induced by the internal fractal structures of trajectories on motion in standard space. Their main consequence is the transformation of classical dynamics into a generalized, quantum-like self-organized dynamics. A Schrödinger-type equation is derived as an integral of the geodesic equation in a fractal space. We then indicate how gauge fields can be constructed from a geometric re-interpretation of gauge transformations as scale transformations in fractal space-time. Finally, we introduce a new tentative development of the theory, in which quantum laws would hold also in scale space, introducing complexergy as a measure of organizational complexity. Initial possible applications of this extended framework to the processes of morphogenesis and the emergence of prokaryotic and eukaryotic cellular structures are discussed. Having founded elements of the evolutionary, developmental, biochemical and cellular theories on the first principles of scale relativity theory, we introduce proposals for the construction of an integrative theory of life and for the design and implementation of novel macroscopic quantum-type experiments and devices, and discuss their potential

  1. Disordered Plamonics and Complex Metamaterials

    KAUST Repository

    Gongora, J. S. Totero

    2017-01-01

    Complex systems are ensembles of interconnected elements where mutual interaction and an optimized amount of disorder produce advanced functionalities. These systems are abundant in our daily experience: typical examples are the brain, biological

  2. Introduction to symposium: Arthropods and wildlife conservation: synergy in complex biological systems

    Science.gov (United States)

    The symposium will discuss the effects of arthropods and other stressors on wildlife conservation programs. Speakers with affiliations in wildlife biology, parasitology and entomology will be included in the program. Research of national and international interest will be presented....

  3. Philosophy of complex systems

    CERN Document Server

    2011-01-01

    The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...

  4. Structure, function, and behaviour of computational models in systems biology.

    Science.gov (United States)

    Knüpfer, Christian; Beckstein, Clemens; Dittrich, Peter; Le Novère, Nicolas

    2013-05-31

    Systems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such "bio-models" necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language. We present a conceptual framework - the meaning facets - which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model's components (structure), the meaning of the model's intended use (function), and the meaning of the model's dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces. The meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

  5. Structural identifiability of systems biology models: a critical comparison of methods.

    Directory of Open Access Journals (Sweden)

    Oana-Teodora Chis

    Full Text Available Analysing the properties of a biological system through in silico experimentation requires a satisfactory mathematical representation of the system including accurate values of the model parameters. Fortunately, modern experimental techniques allow obtaining time-series data of appropriate quality which may then be used to estimate unknown parameters. However, in many cases, a subset of those parameters may not be uniquely estimated, independently of the experimental data available or the numerical techniques used for estimation. This lack of identifiability is related to the structure of the model, i.e. the system dynamics plus the observation function. Despite the interest in knowing a priori whether there is any chance of uniquely estimating all model unknown parameters, the structural identifiability analysis for general non-linear dynamic models is still an open question. There is no method amenable to every model, thus at some point we have to face the selection of one of the possibilities. This work presents a critical comparison of the currently available techniques. To this end, we perform the structural identifiability analysis of a collection of biological models. The results reveal that the generating series approach, in combination with identifiability tableaus, offers the most advantageous compromise among range of applicability, computational complexity and information provided.

  6. Large-scale Complex IT Systems

    OpenAIRE

    Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

    2011-01-01

    This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

  7. Large-scale complex IT systems

    OpenAIRE

    Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

    2012-01-01

    12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

  8. Alkali Metal Ion Complexes with Phosphates, Nucleotides, Amino Acids, and Related Ligands of Biological Relevance. Their Properties in Solution.

    Science.gov (United States)

    Crea, Francesco; De Stefano, Concetta; Foti, Claudia; Lando, Gabriele; Milea, Demetrio; Sammartano, Silvio

    2016-01-01

    Alkali metal ions play very important roles in all biological systems, some of them are essential for life. Their concentration depends on several physiological factors and is very variable. For example, sodium concentrations in human fluids vary from quite low (e.g., 8.2 mmol dm(-3) in mature maternal milk) to high values (0.14 mol dm(-3) in blood plasma). While many data on the concentration of Na(+) and K(+) in various fluids are available, the information on other alkali metal cations is scarce. Since many vital functions depend on the network of interactions occurring in various biofluids, this chapter reviews their complex formation with phosphates, nucleotides, amino acids, and related ligands of biological relevance. Literature data on this topic are quite rare if compared to other cations. Generally, the stability of alkali metal ion complexes of organic and inorganic ligands is rather low (usually log K  Na(+) > K(+) > Rb(+) > Cs(+). For example, for citrate it is: log K ML = 0.88, 0.80, 0.48, 0.38, and 0.13 at 25 °C and infinite dilution. Some considerations are made on the main aspects related to the difficulties in the determination of weak complexes. The importance of the alkali metal ion complexes was also studied in the light of modelling natural fluids and in the use of these cations as probes for different processes. Some empirical relationships are proposed for the dependence of the stability constants of Na(+) complexes on the ligand charge, as well as for correlations among log K values of NaL, KL or LiL species (L = generic ligand).

  9. Advances in Structural Biology and the Application to Biological Filament Systems.

    Science.gov (United States)

    Popp, David; Koh, Fujiet; Scipion, Clement P M; Ghoshdastider, Umesh; Narita, Akihiro; Holmes, Kenneth C; Robinson, Robert C

    2018-04-01

    Structural biology has experienced several transformative technological advances in recent years. These include: development of extremely bright X-ray sources (microfocus synchrotron beamlines and free electron lasers) and the use of electrons to extend protein crystallography to ever decreasing crystal sizes; and an increase in the resolution attainable by cryo-electron microscopy. Here we discuss the use of these techniques in general terms and highlight their application for biological filament systems, an area that is severely underrepresented in atomic resolution structures. We assemble a model of a capped tropomyosin-actin minifilament to demonstrate the utility of combining structures determined by different techniques. Finally, we survey the methods that attempt to transform high resolution structural biology into more physiological environments, such as the cell. Together these techniques promise a compelling decade for structural biology and, more importantly, they will provide exciting discoveries in understanding the designs and purposes of biological machines. © 2018 The Authors. BioEssays Published by WILEY Periodicals, Inc.

  10. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    Science.gov (United States)

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

  11. Systems biology for molecular life sciences and its impact in biomedicine.

    Science.gov (United States)

    Medina, Miguel Ángel

    2013-03-01

    Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.

  12. Spectroscopic, thermal, catalytic and biological studies of Cu(II) azo dye complexes

    Science.gov (United States)

    El-Sonbati, A. Z.; Diab, M. A.; El-Bindary, A. A.; Shoair, A. F.; Hussein, M. A.; El-Boz, R. A.

    2017-08-01

    New complexes of copper(II) with azo compounds of 5-amino-2-(aryl diazenyl)phenol (HLn) are prepared and investigated by elemental analyses, molar conductance, IR, 1H NMR, UV-Visible, mass, ESR spectra, magnetic susceptibility measurements and thermal analyses. The complexes have a square planar structure and general formula [Cu(Ln)(OAc)]H2O. Study the catalytic activities of Cu(II) complexes toward oxidation of benzyl alcohol derivatives to carbonyl compounds were tested using H2O2 as the oxidant. The intrinsic binding constants (Kb) of the ligands (HLn) and Cu(II) complexes (1-4) with CT-DNA are determined. The formed compounds have been tested for biological activity of antioxidants, antibacterial against Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria and yeast Candida albicans. Antibiotic (Ampicillin) and antifungal against (Colitrimazole) and cytotoxic compounds HL1, HL2, HL3 and complex (1) showed moderate to good activity against S. aureus, E. coli and Candida albicans, and also to be moderate on antioxidants and toxic substances. Molecular docking is used to predict the binding between the ligands with the receptor of breast cancer (2a91).

  13. Treatment of complex biological mixtures with pulsed electric fields An energy transfer characterization

    International Nuclear Information System (INIS)

    Schrive, Luc

    2004-01-01

    Sewage sludge from waste water treatment plants is a complex biological mixture and a problematic by-product because of valorisation restrictions. In order to limit its production, pulsed electric fields (PEF) were studied because of their biological effects and their potentially physico-chemical action. This work demonstrated a paradoxical phenomenon: cell lysis triggered a respirometric activation followed by a delayed lethality. This phenomenon was related to the leakage of internal compounds which were immediately bio-assimilated. At high energy expense, the plasmic membrane permeabilization led to cell death. Practically, with the technical configuration of the equipment, no hydrolysis was detected. This limitation decreases the interest for excess sludge reduction, but for the same reason, PEF cold sterilization technique can be assessed as a promising process. The representation of the electric energy transfer from electrodes to cell was exchanged by the study of mass transfer from the biological cell to the surrounding media under an electromotive force. Thus, the survival rate was modelled by a Sherwood number taking account of electrical, biological and hydraulic parameters. (author) [fr

  14. 5th International Conference on Complex Systems

    CERN Document Server

    Braha, Dan; Bar-Yam, Yaneer

    2011-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

  15. 7th International Conference on Complex Systems

    CERN Document Server

    Braha, Dan; Bar-Yam, Yaneer

    2012-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

  16. Agent-based modelling in synthetic biology.

    Science.gov (United States)

    Gorochowski, Thomas E

    2016-11-30

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. © 2016 The Author(s).

  17. Plant Systems Biology (editorial)

    Science.gov (United States)

    In June 2003, Plant Physiology published an Arabidopsis special issue devoted to plant systems biology. The intention of Natasha Raikhel and Gloria Coruzzi, the two editors of this first-of-its-kind issue, was ‘‘to help nucleate this new effort within the plant community’’ as they considered that ‘‘...

  18. Synthesis, characterization, and biological activity of a new palladium(II) complex with deoxyalliin

    Energy Technology Data Exchange (ETDEWEB)

    Corbi, P.P.; Massabni, A.C. [Inst. de Quimica - UNESP, Dept., Dept. de Quimica Geral e Inoganica, Araraquara (Brazil)]. E-mail: pedrocorbi@yahoo.com; Moreira, A.G. [Inst. de Quimica - UNESP, Dept. de Quimica Geral e Inoganica, Araraquara (Brazil); Faculdade de Medicina de Ribeirao Preto - USP, Dept. de Bioquimica e Imunologia, Ribeirao Preto (Brazil); Medrano, F.J. [Laboratorio Nacional de Luz Sincrotron - LNLS, Campinas (Brazil); Jasiulionis, M.G. [Escola Paulista de Medicina - UNIFESP, Dept. de Micro-Imuno-Parasitologia, Sao Paulo (Brazil); Costa-Neto, C.M. [Faculdade de Medicina de Ribeirao Preto - USP, Dept. de Bioquimica e Imunologia, Ribeirao Preto (Brazil)

    2005-02-15

    Synthesis, characterization, and biological activity of a new water-soluble Pd(II)-deoxyalliin (S-allyl-L-cysteine) complex are described in this article. Elemental and thermal analysis for the complex are consistent with the formula [Pd(C{sub 6}H{sub 10}NO{sub 2}S){sub 2}]. {sup 13}C NMR, {sup 1}H NMR, and IR spectroscopy show coordination of the ligand to Pd(II) through S and N atoms in a square planar geometry. Final residue of the thermal treatment was identified as a mixture of PdO and metallic Pd. Antiproliferative assays using aqueous solutions of the complex against HeLa and TM5 tumor cells showed a pronounced activity of the complex even at low concentrations. After incubation for 24 h, the complex induced cytotoxic effect over HeLa cells when used at concentrations higher than 0.40 mmol/L. At lower concentrations, the complex was nontoxic, indicating its action is probably due to cell cycle arrest, rather than cell death. In agreement with these results, the flow cytometric analysis indicated that after incubation for 24 h at low concentrations of the complex cells are arrested in G0/G1. (author)

  19. Frontiers in mathematical biology

    CERN Document Server

    1994-01-01

    Volume 100, which is the final volume of the LNBM series serves to commemorate the acievements in two decades of this influential collection of books in mathematical biology. The contributions, by the leading mathematical biologists, survey the state of the art in the subject, and offer speculative, philosophical and critical analyses of the key issues confronting the field. The papers address fundamental issues in cell and molecular biology, organismal biology, evolutionary biology, population ecology, community and ecosystem ecology, and applied biology, plus the explicit and implicit mathematical challenges. Cross-cuttting issues involve the problem of variation among units in nonlinear systems, and the related problems of the interactions among phenomena across scales of space, time and organizational complexity.

  20. GPSR: A Resource for Genomics Proteomics and Systems Biology

    Indian Academy of Sciences (India)

    GPSR: A Resource for Genomics Proteomics and Systems Biology · Simple Calculation Programs for Biology Immunological Methods · Simple Calculation Programs for Biology Methods in Molecular Biology · Simple Calculation Programs for Biology Other Methods · PowerPoint Presentation · Slide 6 · Slide 7 · Prediction of ...

  1. Reduction theories elucidate the origins of complex biological rhythms generated by interacting delay-induced oscillations.

    Directory of Open Access Journals (Sweden)

    Ikuhiro Yamaguchi

    Full Text Available Time delay is known to induce sustained oscillations in many biological systems such as electroencephalogram (EEG activities and gene regulations. Furthermore, interactions among delay-induced oscillations can generate complex collective rhythms, which play important functional roles. However, due to their intrinsic infinite dimensionality, theoretical analysis of interacting delay-induced oscillations has been limited. Here, we show that the two primary methods for finite-dimensional limit cycles, namely, the center manifold reduction in the vicinity of the Hopf bifurcation and the phase reduction for weak interactions, can successfully be applied to interacting infinite-dimensional delay-induced oscillations. We systematically derive the complex Ginzburg-Landau equation and the phase equation without delay for general interaction networks. Based on the reduced low-dimensional equations, we demonstrate that diffusive (linearly attractive coupling between a pair of delay-induced oscillations can exhibit nontrivial amplitude death and multimodal phase locking. Our analysis provides unique insights into experimentally observed EEG activities such as sudden transitions among different phase-locked states and occurrence of epileptic seizures.

  2. Advancing metabolic engineering through systems biology of industrial microorganisms

    DEFF Research Database (Denmark)

    Dai, Zongjie; Nielsen, Jens

    2015-01-01

    resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review......Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable...... the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further....

  3. Reliability of large and complex systems

    CERN Document Server

    Kolowrocki, Krzysztof

    2014-01-01

    Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt

  4. A complex, nonlinear dynamic systems perspective on Ayurveda and Ayurvedic research.

    Science.gov (United States)

    Rioux, Jennifer

    2012-07-01

    The fields of complexity theory and nonlinear dynamic systems (NDS) are relevant for analyzing the theory and practice of Ayurvedic medicine from a Western scientific perspective. Ayurvedic definitions of health map clearly onto the tenets of both systems and complexity theory and focus primarily on the preservation of organismic equanimity. Health care research informed by NDS and complexity theory would prioritize (1) ascertaining patterns reflected in whole systems as opposed to isolating components; (2) relationships and dynamic interaction rather than static end-points; (3) transitions, change and cumulative effects, consistent with delivery of therapeutic packages in the reality of the clinical setting; and (4) simultaneously exploring both local and global levels of healing phenomena. NDS and complexity theory are useful in examining nonlinear transitions between states of health and illness; the qualitative nature of shifts in health status; and looking at emergent properties and behaviors stemming from interactions between organismic and environmental systems. Complexity and NDS theory also demonstrate promise for enhancing the suitability of research strategies applied to Ayurvedic medicine through utilizing core concepts such as initial conditions, emergent properties, fractal patterns, and critical fluctuations. In the Ayurvedic paradigm, multiple scales and their interactions are addressed simultaneously, necessitating data collection on change patterns that occur on continuums of both time and space, and are viewed as complementary rather than isolated and discrete. Serious consideration of Ayurvedic clinical understandings will necessitate new measurement options that can account for the relevance of both context and environmental factors, in terms of local biology and the processual features of the clinical encounter. Relevant research design issues will need to address clinical tailoring strategies and provide mechanisms for mapping patterns of

  5. Dietary antioxidant synergy in chemical and biological systems.

    Science.gov (United States)

    Wang, Sunan; Zhu, Fan

    2017-07-24

    Antioxidant (AOX) synergies have been much reported in chemical ("test-tube" based assays focusing on pure chemicals), biological (tissue culture, animal and clinical models), and food systems during the past decade. Tentative synergies differ from each other due to the composition of AOX and the quantification methods. Regeneration mechanism responsible for synergy in chemical systems has been discussed. Solvent effects could contribute to the artifacts of synergy observed in the chemical models. Synergy in chemical models may hardly be relevant to biological systems that have been much less studied. Apparent discrepancies exist in understanding the molecular mechanisms in both chemical and biological systems. This review discusses diverse variables associated with AOX synergy and molecular scenarios for explanation. Future research to better utilize the synergy is suggested.

  6. Geographical National Condition and Complex System

    Directory of Open Access Journals (Sweden)

    WANG Jiayao

    2016-01-01

    Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish

  7. It's the System, Stupid: How Systems Biology Is Transforming.

    Science.gov (United States)

    2010-01-01

    So far, little is known about systems biology and its potential for changing how we diagnose and treat disease. That will change soon, say the systems experts, who advise payers to begin learning now about how it could make healthcare efficient.

  8. Interactive analysis of systems biology molecular expression data

    Directory of Open Access Journals (Sweden)

    Prabhakar Sunil

    2008-02-01

    Full Text Available Abstract Background Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. Results Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. Conclusion The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe in growth media (an ionomics dataset. This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.

  9. Tracing organizing principles: Learning from the history of systems biology

    DEFF Research Database (Denmark)

    Green, Sara; Wolkenhauer, Olaf

    2014-01-01

    on this historical background in order to increase the understanding of the motivation behind the search for general principles and to clarify different epistemic aims within systems biology. We pinpoint key aspects of earlier approaches that also underlie the current practice. These are i) the focus on relational......With the emergence of systems biology, the identification of organizing principles is being highlighted as a key research aim. Researchers attempt to “reverse engineer” the functional organization of biological systems using methodologies from mathematics, engineering and computer science while...... taking advantage of data produced by new experimental techniques. While systems biology is a relatively new approach, the quest for general principles of biological organization dates back to systems theoretic approaches in early and mid-twentieth century. The aim of this paper is to draw...

  10. {sup 1}H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

    Energy Technology Data Exchange (ETDEWEB)

    Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D., E-mail: bernard.lemire@ualberta.ca [University of Alberta, Department of Biochemistry, School of Molecular and Systems Medicine (Canada)

    2011-04-15

    The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in {sup 1}H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

  11. Trans-algorithmic nature of learning in biological systems.

    Science.gov (United States)

    Shimansky, Yury P

    2018-05-02

    Learning ability is a vitally important, distinctive property of biological systems, which provides dynamic stability in non-stationary environments. Although several different types of learning have been successfully modeled using a universal computer, in general, learning cannot be described by an algorithm. In other words, algorithmic approach to describing the functioning of biological systems is not sufficient for adequate grasping of what is life. Since biosystems are parts of the physical world, one might hope that adding some physical mechanisms and principles to the concept of algorithm could provide extra possibilities for describing learning in its full generality. However, a straightforward approach to that through the so-called physical hypercomputation so far has not been successful. Here an alternative approach is proposed. Biosystems are described as achieving enumeration of possible physical compositions though random incremental modifications inflicted on them by active operating resources (AORs) in the environment. Biosystems learn through algorithmic regulation of the intensity of the above modifications according to a specific optimality criterion. From the perspective of external observers, biosystems move in the space of different algorithms driven by random modifications imposed by the environmental AORs. A particular algorithm is only a snapshot of that motion, while the motion itself is essentially trans-algorithmic. In this conceptual framework, death of unfit members of a population, for example, is viewed as a trans-algorithmic modification made in the population as a biosystem by environmental AORs. Numerous examples of AOR utilization in biosystems of different complexity, from viruses to multicellular organisms, are provided.

  12. Integrating biological redesign: where synthetic biology came from and where it needs to go.

    Science.gov (United States)

    Way, Jeffrey C; Collins, James J; Keasling, Jay D; Silver, Pamela A

    2014-03-27

    Synthetic biology seeks to extend approaches from engineering and computation to redesign of biology, with goals such as generating new chemicals, improving human health, and addressing environmental issues. Early on, several guiding principles of synthetic biology were articulated, including design according to specification, separation of design from fabrication, use of standardized biological parts and organisms, and abstraction. We review the utility of these principles over the past decade in light of the field's accomplishments in building complex systems based on microbial transcription and metabolism and describe the progress in mammalian cell engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. Analysis of complex networks from biology to linguistics

    CERN Document Server

    Dehmer, Matthias

    2009-01-01

    Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.

  14. ChemProt: A disease chemical biology database

    DEFF Research Database (Denmark)

    Taboureau, Olivier; Oprea, Tudor I.

    2013-01-01

    The integration of chemistry, biology, and informatics to study drug actions across multiple biological targets, pathways, and biological systems is an emerging paradigm in drug discovery. Rather than reducing a complex system to simplistic models, fields such as chemogenomics and translational...... informatics are seeking to build a holistic model for a better understanding of the drug pharmacology and clinical effects. Here we will present a webserver called ChemProt that can assist, in silico, the drug actions in the context of cellular and disease networks and contribute in the field of disease...... chemical biology, drug repurposing, and off-target effects prediction....

  15. SEEK: a systems biology data and model management platform.

    Science.gov (United States)

    Wolstencroft, Katherine; Owen, Stuart; Krebs, Olga; Nguyen, Quyen; Stanford, Natalie J; Golebiewski, Martin; Weidemann, Andreas; Bittkowski, Meik; An, Lihua; Shockley, David; Snoep, Jacky L; Mueller, Wolfgang; Goble, Carole

    2015-07-11

    Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and

  16. Network-based discovery through mechanistic systems biology. Implications for applications--SMEs and drug discovery: where the action is.

    Science.gov (United States)

    Benson, Neil

    2015-08-01

    Phase II attrition remains the most important challenge for drug discovery. Tackling the problem requires improved understanding of the complexity of disease biology. Systems biology approaches to this problem can, in principle, deliver this. This article reviews the reports of the application of mechanistic systems models to drug discovery questions and discusses the added value. Although we are on the journey to the virtual human, the length, path and rate of learning from this remain an open question. Success will be dependent on the will to invest and make the most of the insight generated along the way. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Advancing metabolic engineering through systems biology of industrial microorganisms.

    Science.gov (United States)

    Dai, Zongjie; Nielsen, Jens

    2015-12-01

    Development of sustainable processes to produce bio-based compounds is necessary due to the severe environmental problems caused by the use of fossil resources. Metabolic engineering can facilitate the development of highly efficient cell factories to produce these compounds from renewable resources. The objective of systems biology is to gain a comprehensive and quantitative understanding of living cells and can hereby enhance our ability to characterize and predict cellular behavior. Systems biology of industrial microorganisms is therefore valuable for metabolic engineering. Here we review the application of systems biology tools for the identification of metabolic engineering targets which may lead to reduced development time for efficient cell factories. Finally, we present some perspectives of systems biology for advancing metabolic engineering further. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Reconstruction of biological networks based on life science data integration.

    Science.gov (United States)

    Kormeier, Benjamin; Hippe, Klaus; Arrigo, Patrizio; Töpel, Thoralf; Janowski, Sebastian; Hofestädt, Ralf

    2010-10-27

    For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH--an integration toolkit for building life science data warehouses, CardioVINEdb--a information system for biological data in cardiovascular-disease and VANESA--a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  19. Exploring lipids with nonlinear optical microscopy in multiple biological systems

    Science.gov (United States)

    Alfonso-Garcia, Alba

    Lipids are crucial biomolecules for the well being of humans. Altered lipid metabolism may give rise to a variety of diseases that affect organs from the cardiovascular to the central nervous system. A deeper understanding of lipid metabolic processes would spur medical research towards developing precise diagnostic tools, treatment methods, and preventive strategies for reducing the impact of lipid diseases. Lipid visualization remains a complex task because of the perturbative effect exerted by traditional biochemical assays and most fluorescence markers. Coherent Raman scattering (CRS) microscopy enables interrogation of biological samples with minimum disturbance, and is particularly well suited for label-free visualization of lipids, providing chemical specificity without compromising on spatial resolution. Hyperspectral imaging yields large datasets that benefit from tailored multivariate analysis. In this thesis, CRS microscopy was combined with Raman spectroscopy and other label-free nonlinear optical techniques to analyze lipid metabolism in multiple biological systems. We used nonlinear Raman techniques to characterize Meibum secretions in the progression of dry eye disease, where the lipid and protein contributions change in ratio and phase segregation. We employed similar tools to examine lipid droplets in mice livers aboard a spaceflight mission, which lose their retinol content contributing to the onset of nonalcoholic fatty-liver disease. We also focused on atherosclerosis, a disease that revolves around lipid-rich plaques in arterial walls. We examined the lipid content of macrophages, whose variable phenotype gives rise to contrasting healing and inflammatory activities. We also proposed new label-free markers, based on lifetime imaging, for macrophage phenotype, and to detect products of lipid oxidation. Cholesterol was also detected in hepatitis C virus infected cells, and in specific strains of age-related macular degeneration diseased cells by

  20. Biology and Mechanics of Blood Flows Part I: Biology

    CERN Document Server

    Thiriet, Marc

    2008-01-01

    Biology and Mechanics of Blood Flows presents the basic knowledge and state-of-the-art techniques necessary to carry out investigations of the cardiovascular system using modeling and simulation. Part I of this two-volume sequence, Biology, addresses the nanoscopic and microscopic scales. The nanoscale corresponds to the scale of biochemical reaction cascades involved in cell adaptation to mechanical stresses among other stimuli. The microscale is the scale of stress-induced tissue remodeling associated with acute or chronic loadings. The cardiovascular system, like any physiological system, has a complicated three-dimensional structure and composition. Its time dependent behavior is regulated, and this complex system has many components. In this authoritative work, the author provides a survey of relevant cell components and processes, with detailed coverage of the electrical and mechanical behaviors of vascular cells, tissues, and organs. Because the behaviors of vascular cells and tissues are tightly coupl...

  1. Multilayer network modeling creates opportunities for novel network statistics. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

    Science.gov (United States)

    Muldoon, Sarah Feldt

    2018-03-01

    As described in the review by Gosak et al., the field of network science has had enormous success in providing new insights into the structure and function of biological systems [1]. In the complex networks framework, system elements are network nodes, and connections between nodes represent some form of interaction between system elements [2]. The flexibility to define network nodes and edges to represent different aspects of biological systems has been employed to model numerous diverse systems at multiple scales.

  2. MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

    Science.gov (United States)

    Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

    2016-01-01

    Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

  3. Invited review: gravitational biology of the neuromotor systems: a perspective to the next era

    Science.gov (United States)

    Edgerton, V. R.; Roy, R. R.

    2000-01-01

    Earth's gravity has had a significant impact on the designs of the neuromotor systems that have evolved. Early indications are that gravity also plays a key role in the ontogenesis of some of these design features. The purpose of the present review is not to assess and interpret a body of knowledge in the usual sense of a review but to look ahead, given some of the general concepts that have evolved and observations made to date, which can guide our future approach to gravitational biology. We are now approaching an era in gravitational biology during which well-controlled experiments can be conducted for sustained periods in a microgravity environment. Thus it is now possible to study in greater detail the role of gravity in phylogenesis and ontogenesis. Experiments can range from those conducted on the simplest levels of organization of the components that comprise the neuromotor system to those conducted on the whole organism. Generally, the impact of Earth's gravitational environment on living systems becomes more complex as the level of integration of the biological phenomenon of interest increases. Studies of the effects of gravitational vectors on neuromotor systems have and should continue to provide unique insight into these mechanisms that control and maintain neural control systems designed to function in Earth's gravitational environment. A number of examples are given of how a gravitational biology perspective can lead to a clearer understanding of neuromotor disorders. Furthermore, the technologies developed for spaceflight studies have contributed and should continue to contribute to studies of motor dysfunctions, such as spinal cord injury and stroke. Disorders associated with energy support and delivery systems and how these functions are altered by sedentary life styles at 1 G and by space travel in a microgravity environment are also discussed.

  4. MORE: mixed optimization for reverse engineering--an application to modeling biological networks response via sparse systems of nonlinear differential equations.

    Science.gov (United States)

    Sambo, Francesco; de Oca, Marco A Montes; Di Camillo, Barbara; Toffolo, Gianna; Stützle, Thomas

    2012-01-01

    Reverse engineering is the problem of inferring the structure of a network of interactions between biological variables from a set of observations. In this paper, we propose an optimization algorithm, called MORE, for the reverse engineering of biological networks from time series data. The model inferred by MORE is a sparse system of nonlinear differential equations, complex enough to realistically describe the dynamics of a biological system. MORE tackles separately the discrete component of the problem, the determination of the biological network topology, and the continuous component of the problem, the strength of the interactions. This approach allows us both to enforce system sparsity, by globally constraining the number of edges, and to integrate a priori information about the structure of the underlying interaction network. Experimental results on simulated and real-world networks show that the mixed discrete/continuous optimization approach of MORE significantly outperforms standard continuous optimization and that MORE is competitive with the state of the art in terms of accuracy of the inferred networks.

  5. PREFACE: 3rd International Workshop on Statistical Physics and Mathematics for Complex Systems (SPMCS 2012)

    Science.gov (United States)

    Tayurskii, Dmitrii; Abe, Sumiyoshi; Alexandre Wang, Q.

    2012-11-01

    The 3rd International Workshop on Statistical Physics and Mathematics for Complex Systems (SPMCS2012) was held between 25-30 August at Kazan (Volga Region) Federal University, Kazan, Russian Federation. This workshop was jointly organized by Kazan Federal University and Institut Supérieur des Matériaux et Mécaniques Avancées (ISMANS), France. The series of SPMCS workshops was created in 2008 with the aim to be an interdisciplinary incubator for the worldwide exchange of innovative ideas and information about the latest results. The first workshop was held at ISMANS, Le Mans (France) in 2008, and the third at Huazhong Normal University, Wuhan (China) in 2010. At SPMCS2012, we wished to bring together a broad community of researchers from the different branches of the rapidly developing complexity science to discuss the fundamental theoretical challenges (geometry/topology, number theory, statistical physics, dynamical systems, etc) as well as experimental and applied aspects of many practical problems (condensed matter, disordered systems, financial markets, chemistry, biology, geoscience, etc). The program of SPMCS2012 was prepared based on three categories: (i) physical and mathematical studies (quantum mechanics, generalized nonequilibrium thermodynamics, nonlinear dynamics, condensed matter physics, nanoscience); (ii) natural complex systems (physical, geophysical, chemical and biological); (iii) social, economical, political agent systems and man-made complex systems. The conference attracted 64 participants from 10 countries. There were 10 invited lectures, 12 invited talks and 28 regular oral talks in the morning and afternoon sessions. The book of Abstracts is available from the conference website (http://www.ksu.ru/conf/spmcs2012/?id=3). A round table was also held, the topic of which was 'Recent and Anticipated Future Progress in Science of Complexity', discussing a variety of questions and opinions important for the understanding of the concept of

  6. Exploring Synthetic and Systems Biology at the University of Edinburgh.

    Science.gov (United States)

    Fletcher, Liz; Rosser, Susan; Elfick, Alistair

    2016-06-15

    The Centre for Synthetic and Systems Biology ('SynthSys') was originally established in 2007 as the Centre for Integrative Systems Biology, funded by the Biotechnology and Biological Sciences Research Council (BBSRC) and the Engineering and Physical Sciences Research Council (EPSRC). Today, SynthSys embraces an extensive multidisciplinary community of more than 200 researchers from across the University with a common interest in synthetic and systems biology. Our research is broad and deep, addressing a diversity of scientific questions, with wide ranging impact. We bring together the power of synthetic biology and systems approaches to focus on three core thematic areas: industrial biotechnology, agriculture and the environment, and medicine and healthcare. In October 2015, we opened a newly refurbished building as a physical hub for our new U.K. Centre for Mammalian Synthetic Biology funded by the BBSRC/EPSRC/MRC as part of the U.K. Research Councils' Synthetic Biology for Growth programme. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

  7. Modular analysis of biological networks.

    Science.gov (United States)

    Kaltenbach, Hans-Michael; Stelling, Jörg

    2012-01-01

    The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

  8. Hemoglobin and Myoglobin as Reducing Agents in Biological Systems. Redox Reactions of Globins with Copper and Iron Salts and Complexes.

    Science.gov (United States)

    Postnikova, G B; Shekhovtsova, E A

    2016-12-01

    In addition to reversible O2 binding, respiratory proteins of the globin family, hemoglobin (Hb) and myoglobin (Mb), participate in redox reactions with various metal complexes, including biologically significant ones, such as those of copper and iron. HbO 2 and MbO 2 are present in cells in large amounts and, as redox agents, can contribute to maintaining cell redox state and resisting oxidative stress. Divalent copper complexes with high redox potentials (E 0 , 200-600 mV) and high stability constants, such as [Cu(phen) 2 ] 2+ , [Cu(dmphen) 2 ] 2+ , and CuDTA oxidize ferrous heme proteins by the simple outer-sphere electron transfer mechanism through overlapping π-orbitals of the heme and the copper complex. Weaker oxidants, such as Cu2+, CuEDTA, CuNTA, CuCit, CuATP, and CuHis (E 0 ≤ 100-150 mV) react with HbO 2 and MbO 2 through preliminary binding to the protein with substitution of the metal ligands with protein groups and subsequent intramolecular electron transfer in the complex (the site-specific outer-sphere electron transfer mechanism). Oxidation of HbO 2 and MbO 2 by potassium ferricyanide and Fe(3) complexes with NTA, EDTA, CDTA, ATP, 2,3-DPG, citrate, and pyrophosphate PP i proceeds mainly through the simple outer-sphere electron transfer mechanism via the exposed heme edge. According to Marcus theory, the rate of this reaction correlates with the difference in redox potentials of the reagents and their self-exchange rates. For charged reagents, the reaction may be preceded by their nonspecific binding to the protein due to electrostatic interactions. The reactions of LbO 2 with carboxylate Fe complexes, unlike its reactions with ferricyanide, occur via the site-specific outer-sphere electron transfer mechanism, even though the same reagents oxidize structurally similar MbO 2 and cytochrome b 5 via the simple outer-sphere electron transfer mechanism. Of particular biological interest is HbO 2 and MbO 2 transformation into met-forms in the presence

  9. Generating Systems Biology Markup Language Models from the Synthetic Biology Open Language.

    Science.gov (United States)

    Roehner, Nicholas; Zhang, Zhen; Nguyen, Tramy; Myers, Chris J

    2015-08-21

    In the context of synthetic biology, model generation is the automated process of constructing biochemical models based on genetic designs. This paper discusses the use cases for model generation in genetic design automation (GDA) software tools and introduces the foundational concepts of standards and model annotation that make this process useful. Finally, this paper presents an implementation of model generation in the GDA software tool iBioSim and provides an example of generating a Systems Biology Markup Language (SBML) model from a design of a 4-input AND sensor written in the Synthetic Biology Open Language (SBOL).

  10. Noninvasive biological sensor system for detection of drunk driving.

    Science.gov (United States)

    Murata, Kohji; Fujita, Etsunori; Kojima, Shigeyuki; Maeda, Shinitirou; Ogura, Yumi; Kamei, Tsutomu; Tsuji, Toshio; Kaneko, Shigehiko; Yoshizumi, Masao; Suzuki, Nobutaka

    2011-01-01

    Systems capable of monitoring the biological condition of a driver and issuing warnings during instances of drowsiness have recently been studied. Moreover, many researchers have reported that biological signals, such as brain waves, pulsation waves, and heart rate, are different between people who have and have not consumed alcohol. Currently, we are developing a noninvasive system to detect individuals driving under the influence of alcohol by measuring biological signals. We used the frequency time series analysis to attempt to distinguish between normal and intoxicated states of a person as the basis of the sensing system.

  11. Complex formation of blueberry (Vaccinium angustifolium) anthocyanins during freeze-drying and its influence on their biological activity.

    Science.gov (United States)

    Correa-Betanzo, Julieta; Padmanabhan, Priya; Corredig, Milena; Subramanian, Jayasankar; Paliyath, Gopinadhan

    2015-03-25

    Biological activity of polyphenols is influenced by their uptake and is highly influenced by their interactions with the food matrix. This study evaluated the complex formation of blueberry polyphenols with fruit matrixes such as pectin and cellulose and their effect on the biological and antiproliferative properties of human colon cell lines HT-29 and CRL 1790. Free or complexed polyphenols were isolated by dialyzing aqueous or methanolic blueberry homogenates. Seven phenolic compounds and thirteen anthocyanins were identified in blueberry extracts. Blueberry extracts showed varying degrees of antioxidant and antiproliferative activities, as well as α-glucosidase activity. Fruit matrix containing cellulose and pectin, or purified polygalacturonic acid and cellulose, did not retain polyphenols and showed very low antioxidant or antiproliferative activities. These findings suggest that interactions between polyphenols and the food matrix may be more complex than a simple association and may play an important role in the bioefficacy of blueberry polyphenols.

  12. Automatic compilation from high-level biologically-oriented programming language to genetic regulatory networks.

    Science.gov (United States)

    Beal, Jacob; Lu, Ting; Weiss, Ron

    2011-01-01

    The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes (~ 50%) and latency of the optimized engineered gene networks. Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.

  13. Systems biology and p4 medicine: past, present, and future.

    Science.gov (United States)

    Hood, Leroy

    2013-04-01

    Studying complex biological systems in a holistic rather than a "one gene or one protein" at a time approach requires the concerted effort of scientists from a wide variety of disciplines. The Institute for Systems Biology (ISB) has seamlessly integrated these disparate fields to create a cross-disciplinary platform and culture in which "biology drives technology drives computation." To achieve this platform/culture, it has been necessary for cross-disciplinary ISB scientists to learn one another's languages and work together effectively in teams. The focus of this "systems" approach on disease has led to a discipline denoted systems medicine. The advent of technological breakthroughs in the fields of genomics, proteomics, and, indeed, the other "omics" is catalyzing striking advances in systems medicine that have and are transforming diagnostic and therapeutic strategies. Systems medicine has united genomics and genetics through family genomics to more readily identify disease genes. It has made blood a window into health and disease. It is leading to the stratification of diseases (division into discrete subtypes) for proper impedance match against drugs and the stratification of patients into subgroups that respond to environmental challenges in a similar manner (e.g. response to drugs, response to toxins, etc.). The convergence of patient-activated social networks, big data and their analytics, and systems medicine has led to a P4 medicine that is predictive, preventive, personalized, and participatory. Medicine will focus on each individual. It will become proactive in nature. It will increasingly focus on wellness rather than disease. For example, in 10 years each patient will be surrounded by a virtual cloud of billions of data points, and we will have the tools to reduce this enormous data dimensionality into simple hypotheses about how to optimize wellness and avoid disease for each individual. P4 medicine will be able to detect and treat perturbations in

  14. Physical approach to complex systems

    Science.gov (United States)

    Kwapień, Jarosław; Drożdż, Stanisław

    2012-06-01

    Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. As a result, they are flexible and easily adapt to variable external conditions. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence-consolidated also in the present review-that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. Physics methodology proves helpful in addressing many of the related issues. In this review, we advocate some of the computational methods which in our opinion are especially fruitful in extracting information on selected-but at the same time most representative-complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems. The properties we focus on comprise the collective effects and their coexistence with noise, long-range interactions, the interplay between determinism and flexibility in evolution, scale invariance, criticality, multifractality and hierarchical structure. The methods described either originate from “hard” physics-like the random matrix theory-and then were transmitted to other fields of science via the field of complex systems research, or they originated elsewhere but

  15. Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture.

    Science.gov (United States)

    Jasper, Micah N; Martin, Sheppard A; Oshiro, Wendy M; Ford, Jermaine; Bushnell, Philip J; El-Masri, Hisham

    2016-03-15

    People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

  16. Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

    Science.gov (United States)

    Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

    2015-05-01

    Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

  17. Biological properties of novel ruthenium- and osmium-nitrosyl complexes with azole heterocycles

    KAUST Repository

    Novak, Maria S.; Bü chel, Gabriel E.; Keppler, Bernhard K.; Jakupec, Michael A.

    2016-01-01

    Since the discovery that nitric oxide (NO) is a physiologically relevant molecule, there has been great interest in the use of metal nitrosyl compounds as antitumor pharmaceuticals. Particularly interesting are those complexes which can deliver NO to biological targets. Ruthenium- and osmium-based compounds offer lower toxicity compared to other metals and show different mechanisms of action as well as different spectra of activity compared to platinum-based drugs. Novel ruthenium- and osmium-nitrosyl complexes with azole heterocycles were studied to elucidate their cytotoxicity and possible interactions with DNA. Apoptosis induction, changes of mitochondrial transmembrane potential and possible formation of reactive oxygen species were investigated as indicators of NO-mediated damage by flow cytometry. Results suggest that ruthenium- and osmium-nitrosyl complexes with the general formula (indazolium)[cis/trans-MCl4(NO)(1H-indazole)] have pronounced cytotoxic potency in cancer cell lines. Especially the more potent ruthenium complexes strongly induce apoptosis associated with depolarization of mitochondrial membranes, and elevated reactive oxygen species levels. Furthermore, a slight yet not unequivocal trend to accumulation of intracellular cyclic guanosine monophosphate attributable to NO-mediated effects was observed.

  18. Biological properties of novel ruthenium- and osmium-nitrosyl complexes with azole heterocycles

    KAUST Repository

    Novak, Maria S.

    2016-03-09

    Since the discovery that nitric oxide (NO) is a physiologically relevant molecule, there has been great interest in the use of metal nitrosyl compounds as antitumor pharmaceuticals. Particularly interesting are those complexes which can deliver NO to biological targets. Ruthenium- and osmium-based compounds offer lower toxicity compared to other metals and show different mechanisms of action as well as different spectra of activity compared to platinum-based drugs. Novel ruthenium- and osmium-nitrosyl complexes with azole heterocycles were studied to elucidate their cytotoxicity and possible interactions with DNA. Apoptosis induction, changes of mitochondrial transmembrane potential and possible formation of reactive oxygen species were investigated as indicators of NO-mediated damage by flow cytometry. Results suggest that ruthenium- and osmium-nitrosyl complexes with the general formula (indazolium)[cis/trans-MCl4(NO)(1H-indazole)] have pronounced cytotoxic potency in cancer cell lines. Especially the more potent ruthenium complexes strongly induce apoptosis associated with depolarization of mitochondrial membranes, and elevated reactive oxygen species levels. Furthermore, a slight yet not unequivocal trend to accumulation of intracellular cyclic guanosine monophosphate attributable to NO-mediated effects was observed.

  19. Set membership experimental design for biological systems

    Directory of Open Access Journals (Sweden)

    Marvel Skylar W

    2012-03-01

    Full Text Available Abstract Background Experimental design approaches for biological systems are needed to help conserve the limited resources that are allocated for performing experiments. The assumptions used when assigning probability density functions to characterize uncertainty in biological systems are unwarranted when only a small number of measurements can be obtained. In these situations, the uncertainty in biological systems is more appropriately characterized in a bounded-error context. Additionally, effort must be made to improve the connection between modelers and experimentalists by relating design metrics to biologically relevant information. Bounded-error experimental design approaches that can assess the impact of additional measurements on model uncertainty are needed to identify the most appropriate balance between the collection of data and the availability of resources. Results In this work we develop a bounded-error experimental design framework for nonlinear continuous-time systems when few data measurements are available. This approach leverages many of the recent advances in bounded-error parameter and state estimation methods that use interval analysis to generate parameter sets and state bounds consistent with uncertain data measurements. We devise a novel approach using set-based uncertainty propagation to estimate measurement ranges at candidate time points. We then use these estimated measurements at the candidate time points to evaluate which candidate measurements furthest reduce model uncertainty. A method for quickly combining multiple candidate time points is presented and allows for determining the effect of adding multiple measurements. Biologically relevant metrics are developed and used to predict when new data measurements should be acquired, which system components should be measured and how many additional measurements should be obtained. Conclusions The practicability of our approach is illustrated with a case study. This

  20. BlenX-based compositional modeling of complex reaction mechanisms

    Directory of Open Access Journals (Sweden)

    Judit Zámborszky

    2010-02-01

    Full Text Available Molecular interactions are wired in a fascinating way resulting in complex behavior of biological systems. Theoretical modeling provides a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological networks calls for conceptual tools that manage the combinatorial explosion of the set of possible interactions. A suitable conceptual tool to attack complexity is compositionality, already successfully used in the process algebra field to model computer systems. We rely on the BlenX programming language, originated by the beta-binders process calculus, to specify and simulate high-level descriptions of biological circuits. The Gillespie's stochastic framework of BlenX requires the decomposition of phenomenological functions into basic elementary reactions. Systematic unpacking of complex reaction mechanisms into BlenX templates is shown in this study. The estimation/derivation of missing parameters and the challenges emerging from compositional model building in stochastic process algebras are discussed. A biological example on circadian clock is presented as a case study of BlenX compositionality.

  1. Beyond disease susceptibility-Leveraging genome-wide association studies for new insights into complex disease biology.

    Science.gov (United States)

    Lee, J C

    2017-12-01

    Genetic studies in complex diseases have been highly successful, but have also been largely one-dimensional: predominantly focusing on the genetic contribution to disease susceptibility. While this is undoubtedly important-indeed it is a pre-requisite for understanding the mechanisms underlying disease development-there are many other important aspects of disease biology that have received comparatively little attention. In this review, I will discuss how existing genetic data can be leveraged to provide new insights into other aspects of disease biology, why such insights could change the way we think about complex disease, and how this could provide opportunities for better therapies and/or facilitate personalised medicine. To do this, I will use the example of Crohn's disease-a chronic form of inflammatory bowel disease that has been one of the main success stories in complex disease genetics. Indeed, thanks to genetic studies, we now have a much more detailed understanding of the processes involved in Crohn's disease development, but still know relatively little about what determines the subsequent disease course (prognosis) and why this differs so considerably between individuals. I will discuss how we came to realise that genetic variation plays an important role in determining disease prognosis and how this has changed the way we think about Crohn's disease genetics. This will illustrate how phenotypic data can be used to leverage new insights from genetic data and will provide a broadly applicable framework that could yield new insights into the biology of multiple diseases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. What Is a Complex Innovation System?

    Science.gov (United States)

    Katz, J. Sylvan

    2016-01-01

    Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too. PMID:27258040

  3. What Is a Complex Innovation System?

    Directory of Open Access Journals (Sweden)

    J Sylvan Katz

    Full Text Available Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.

  4. SEEK: a systems biology data and model management platform.

    NARCIS (Netherlands)

    Wolstencroft, K.J.; Owen, S.; Krebs, O.; Nguyen, Q.; Stanford, N.J.; Golebiewski, M.; Weidemann, A.; Bittkowski, M.; An, L.; Shockley, D.; Snoep, J.L.; Mueller, W.; Goble, C.

    2015-01-01

    Background: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems

  5. Magnetic biosensor system to detect biological targets

    KAUST Repository

    Li, Fuquan

    2012-09-01

    Magneto-resistive sensors in combination with magnetic beads provide sensing platforms, which are small in size and highly sensitive. These platforms can be fully integrated with microchannels and electronics to enable devices capable of performing complex tasks. Commonly, a sandwich method is used that requires a specific coating of the sensor\\'s surface to immobilize magnetic beads and biological targets on top of the sensor. This paper concerns a micro device to detect biological targets using magnetic concentration, magnetic as well as mechanical trapping and magnetic sensing. Target detection is based on the size difference between bare magnetic beads and magnetic beads with targets attached. This method remedies the need for a coating layer and reduces the number of steps required to run an experiment. © 2012 IEEE.

  6. Reconstruction of biological networks based on life science data integration

    Directory of Open Access Journals (Sweden)

    Kormeier Benjamin

    2010-06-01

    Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  7. Synchronization and emergence in complex systems

    Indian Academy of Sciences (India)

    ... complex systems. Fatihcan M Atay. Synchronization, Coupled Systems and Networks Volume 77 Issue 5 November 2011 pp 855-863 ... We show how novel behaviour can emerge in complex systems at the global level through synchronization of the activities of their constituent units. Two mechanisms are suggested for ...

  8. Infinite Particle Systems: Complex Systems III

    Directory of Open Access Journals (Sweden)

    Editorial Board

    2008-06-01

    Full Text Available In the years 2002-2005, a group of German and Polish mathematicians worked under a DFG research project No 436 POL 113/98/0-1 entitled "Methods of stochastic analysis in the theory of collective phenomena: Gibbs states and statistical hydrodynamics". The results of their study were summarized at the German-Polish conference, which took place in Poland in October 2005. The venue of the conference was Kazimierz Dolny upon Vistula - a lovely town and a popular place for various cultural, scientific, and even political events of an international significance. The conference was also attended by scientists from France, Italy, Portugal, UK, Ukraine, and USA, which predetermined its international character. Since that time, the conference, entitled "Infinite Particle Systems: Complex Systems" has become an annual international event, attended by leading scientists from Germany, Poland and many other countries. The present volume of the "Condensed Matter Physics" contains proceedings of the conference "Infinite Particle Systems: Complex Systems III", which took place in June 2007.

  9. Integration of Principles of Systems Biology and Radiation Biology: Toward Development of in silico Models to Optimize IUdR-Mediated Radiosensitization of DNA Mismatch Repair Deficient (Damage Tolerant) Human Cancers

    International Nuclear Information System (INIS)

    Kinsella, Timothy J.; Gurkan-Cavusoglu, Evren; Du, Weinan; Loparo, Kenneth A.

    2011-01-01

    Over the last 7 years, we have focused our experimental and computational research efforts on improving our understanding of the biochemical, molecular, and cellular processing of iododeoxyuridine (IUdR) and ionizing radiation (IR) induced DNA base damage by DNA mismatch repair (MMR). These coordinated research efforts, sponsored by the National Cancer Institute Integrative Cancer Biology Program (ICBP), brought together system scientists with expertise in engineering, mathematics, and complex systems theory and translational cancer researchers with expertise in radiation biology. Our overall goal was to begin to develop computational models of IUdR- and/or IR-induced base damage processing by MMR that may provide new clinical strategies to optimize IUdR-mediated radiosensitization in MMR deficient (MMR − ) “damage tolerant” human cancers. Using multiple scales of experimental testing, ranging from purified protein systems to in vitro (cellular) and to in vivo (human tumor xenografts in athymic mice) models, we have begun to integrate and interpolate these experimental data with hybrid stochastic biochemical models of MMR damage processing and probabilistic cell cycle regulation models through a systems biology approach. In this article, we highlight the results and current status of our integration of radiation biology approaches and computational modeling to enhance IUdR-mediated radiosensitization in MMR − damage tolerant cancers.

  10. Identifying novel glioma associated pathways based on systems biology level meta-analysis.

    Science.gov (United States)

    Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

    2013-01-01

    With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

  11. Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.

    Science.gov (United States)

    Watanabe, Leandro; Myers, Chris J

    2016-08-19

    The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime.

  12. From System Complexity to Emergent Properties

    CERN Document Server

    Aziz-Alaoui, M. A

    2009-01-01

    Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

  13. Complex Systems Design & Management : Proceedings of the Third International Conference on Complex Systems Design & Management

    CERN Document Server

    Caseau, Yves; Krob, Daniel; Rauzy, Antoine

    2013-01-01

    This book contains all refereed papers that were accepted to the third edition of the « Complex Systems Design & Management » (CSD&M 2012) international conference that took place in Paris (France) from December 12-14, 2012. (Website: http://www.csdm2012.csdm.fr)  These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic  tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems). The CSD&M 2012 conference is organized under the guidance of the CESAMES non-profit organization (http://www.cesames.net).

  14. Logic-based models in systems biology: a predictive and parameter-free network analysis method.

    Science.gov (United States)

    Wynn, Michelle L; Consul, Nikita; Merajver, Sofia D; Schnell, Santiago

    2012-11-01

    Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network's dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples.

  15. Tunable promoters in systems biology

    DEFF Research Database (Denmark)

    Mijakovic, Ivan; Petranovic, Dina; Jensen, Peter Ruhdal

    2005-01-01

    The construction of synthetic promoter libraries has represented a major breakthrough in systems biology, enabling the subtle tuning of enzyme activities. A number of tools are now available that allow the modulation of gene expression and the detection of changes in expression patterns. But, how...

  16. Comprehension of complex biological processes by analytical methods: how far can we go using mass spectrometry?

    International Nuclear Information System (INIS)

    Gerner, C.

    2013-01-01

    Comprehensive understanding of complex biological processes is the basis for many biomedical issues of great relevance for modern society including risk assessment, drug development, quality control of industrial products and many more. Screening methods provide means for investigating biological samples without research hypothesis. However, the first boom of analytical screening efforts has passed and we again need to ask whether and how to apply screening methods. Mass spectrometry is a modern tool with unrivalled analytical capacities. This applies to all relevant characteristics of analytical methods such as specificity, sensitivity, accuracy, multiplicity and diversity of applications. Indeed, mass spectrometry qualifies to deal with complexity. Chronic inflammation is a common feature of almost all relevant diseases challenging our modern society; these diseases are apparently highly diverse and include arteriosclerosis, cancer, back pain, neurodegenerative diseases, depression and other. The complexity of mechanisms regulating chronic inflammation is the reason for the practical challenge to deal with it. The presentation shall give an overview of capabilities and limitations of the application of this analytical tool to solve critical questions with great relevance for our society. (author)

  17. The role of mechanics in biological and bio-inspired systems.

    Science.gov (United States)

    Egan, Paul; Sinko, Robert; LeDuc, Philip R; Keten, Sinan

    2015-07-06

    Natural systems frequently exploit intricate multiscale and multiphasic structures to achieve functionalities beyond those of man-made systems. Although understanding the chemical make-up of these systems is essential, the passive and active mechanics within biological systems are crucial when considering the many natural systems that achieve advanced properties, such as high strength-to-weight ratios and stimuli-responsive adaptability. Discovering how and why biological systems attain these desirable mechanical functionalities often reveals principles that inform new synthetic designs based on biological systems. Such approaches have traditionally found success in medical applications, and are now informing breakthroughs in diverse frontiers of science and engineering.

  18. The Meaning of System: Towards a Complexity Orientation in Systems Thinking

    DEFF Research Database (Denmark)

    Leleur, Steen

    2014-01-01

    for systems practice. It is argued that complexity theory and thinking with reference to Luhmann a.o. ought to be recognised and paid attention to by the systems community. Overall, it is found that a complexity orientation may contribute to extend and enrich the explanatory power of current systems theory......This article reviews the generic meaning of ‘system’ and complements more conventional system notions with a system perception based on recent complexity theory. With system as the core concept of systems theory, its actual meaning is not just of theoretical interest but is highly relevant also...... when used to complex real-world problems. As regards systems practice it is found that selective use and combination of five presented research approaches (functionalist, interpretive, emancipatory, postmodern and complexity) which function as different but complementing ‘epistemic lenses’ in a process...

  19. Systems Biology and P4 Medicine: Past, Present, and Future

    Directory of Open Access Journals (Sweden)

    Leroy Hood

    2013-04-01

    Full Text Available Studying complex biological systems in a holistic rather than a “one gene or one protein” at a time approach requires the concerted effort of scientists from a wide variety of disciplines. The Institute for Systems Biology (ISB has seamlessly integrated these disparate fields to create a cross-disciplinary platform and culture in which “biology drives technology drives computation.” To achieve this platform/culture, it has been necessary for cross-disciplinary ISB scientists to learn one another’s languages and work together effectively in teams. The focus of this “systems” approach on disease has led to a discipline denoted systems medicine. The advent of technological breakthroughs in the fields of genomics, proteomics, and, indeed, the other “omics” is catalyzing striking advances in systems medicine that have and are transforming diagnostic and therapeutic strategies. Systems medicine has united genomics and genetics through family genomics to more readily identify disease genes. It has made blood a window into health and disease. It is leading to the stratification of diseases (division into discrete subtypes for proper impedance match against drugs and the stratification of patients into subgroups that respond to environmental challenges in a similar manner (e.g. response to drugs, response to toxins, etc.. The convergence of patient-activated social networks, big data and their analytics, and systems medicine has led to a P4 medicine that is predictive, preventive, personalized, and participatory. Medicine will focus on each individual. It will become proactive in nature. It will increasingly focus on wellness rather than disease. For example, in 10 years each patient will be surrounded by a virtual cloud of billions of data points, and we will have the tools to reduce this enormous data dimensionality into simple hypotheses about how to optimize wellness and avoid disease for each individual. P4 medicine will be able to

  20. Heavy-ion microbeam system at JAEA-Takasaki for microbeam biology

    International Nuclear Information System (INIS)

    Funayama, Tomoo; Wada, Seiichi; Yokota, Yuichiro

    2008-01-01

    Research concerning cellular responses to low dose irradiation, radiation-induced bystander effects, and the biological track structure of charged particles has recently received particular attention in the field of radiation biology. Target irradiation employing a microbeam represents a useful means of advancing this research by obviating some of the disadvantages associated with the conventional irradiation strategies. The heavy-ion microbeam system at Japan Atomic Energy Agency (JAEA)-Takasaki, which was planned in 1987 and started in the early 1990's, can provide target irradiation of heavy charged particles to biological material at atmospheric pressure using a minimum beam size 5 μm in diameter. A variety of biological material has been irradiated using this microbeam system including cultured mammalian and higher plant cells, isolated fibers of mouse skeletal muscle, silkworm (Bombyx mori) embryos and larvae, Arabidopsis thaliana roots, and the nematode Caenorhabditis elegans. The system can be applied to the investigation of mechanisms within biological organisms not only in the context of radiation biology, but also in the fields of general biology such as physiology, developmental biology and neurobiology, and should help to establish and contribute to the field of 'microbeam biology'. (author)

  1. Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

    Science.gov (United States)

    Ippolito, Corey; Plice, Laura; Pisanich, Greg

    2003-01-01

    The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

  2. Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

    Directory of Open Access Journals (Sweden)

    Sudin eBhattacharya

    2012-12-01

    Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

  3. Using chemistry and microfluidics to understand the spatial dynamics of complex biological networks.

    Science.gov (United States)

    Kastrup, Christian J; Runyon, Matthew K; Lucchetta, Elena M; Price, Jessica M; Ismagilov, Rustem F

    2008-04-01

    Understanding the spatial dynamics of biochemical networks is both fundamentally important for understanding life at the systems level and also has practical implications for medicine, engineering, biology, and chemistry. Studies at the level of individual reactions provide essential information about the function, interactions, and localization of individual molecular species and reactions in a network. However, analyzing the spatial dynamics of complex biochemical networks at this level is difficult. Biochemical networks are nonequilibrium systems containing dozens to hundreds of reactions with nonlinear and time-dependent interactions, and these interactions are influenced by diffusion, flow, and the relative values of state-dependent kinetic parameters. To achieve an overall understanding of the spatial dynamics of a network and the global mechanisms that drive its function, networks must be analyzed as a whole, where all of the components and influential parameters of a network are simultaneously considered. Here, we describe chemical concepts and microfluidic tools developed for network-level investigations of the spatial dynamics of these networks. Modular approaches can be used to simplify these networks by separating them into modules, and simple experimental or computational models can be created by replacing each module with a single reaction. Microfluidics can be used to implement these models as well as to analyze and perturb the complex network itself with spatial control on the micrometer scale. We also describe the application of these network-level approaches to elucidate the mechanisms governing the spatial dynamics of two networkshemostasis (blood clotting) and early patterning of the Drosophila embryo. To investigate the dynamics of the complex network of hemostasis, we simplified the network by using a modular mechanism and created a chemical model based on this mechanism by using microfluidics. Then, we used the mechanism and the model to

  4. Sandpile model for relaxation in complex systems

    International Nuclear Information System (INIS)

    Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.

    1997-10-01

    The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)

  5. Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2

    Directory of Open Access Journals (Sweden)

    Sorokin Anatoly

    2015-06-01

    Full Text Available The Systems Biological Graphical Notation (SBGN is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD, Entity Relationship (ER and Activity Flow (AF, allow for the representation of different aspects of biological and biochemical systems at different levels of detail.

  6. Biological Soft Robotics.

    Science.gov (United States)

    Feinberg, Adam W

    2015-01-01

    In nature, nanometer-scale molecular motors are used to generate force within cells for diverse processes from transcription and transport to muscle contraction. This adaptability and scalability across wide temporal, spatial, and force regimes have spurred the development of biological soft robotic systems that seek to mimic and extend these capabilities. This review describes how molecular motors are hierarchically organized into larger-scale structures in order to provide a basic understanding of how these systems work in nature and the complexity and functionality we hope to replicate in biological soft robotics. These span the subcellular scale to macroscale, and this article focuses on the integration of biological components with synthetic materials, coupled with bioinspired robotic design. Key examples include nanoscale molecular motor-powered actuators, microscale bacteria-controlled devices, and macroscale muscle-powered robots that grasp, walk, and swim. Finally, the current challenges and future opportunities in the field are addressed.

  7. Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nielsen, Jens; Jewett, Michael Christopher

    2008-01-01

    in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development...... programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given....

  8. EURASIP journal on bioinformatics & systems biology

    National Research Council Canada - National Science Library

    2006-01-01

    "The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...

  9. Embracing uncertainty, managing complexity: applying complexity thinking principles to transformation efforts in healthcare systems.

    Science.gov (United States)

    Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney

    2018-03-21

    Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By

  10. Marine biological data and information management system

    Digital Repository Service at National Institute of Oceanography (India)

    Sarupria, J.S.

    Indian National Oceanographic Data Centre (INODC) is engaged in developing a marine biological data and information management system (BIODIMS). This system will contain the information on zooplankton in the water column, zoobenthic biomass...

  11. Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.

    Directory of Open Access Journals (Sweden)

    Judith Somekh

    2012-12-01

    Full Text Available We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM, a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure-the objects that comprise the system, and behavior-how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point-the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model.

  12. Chinese Herbal Medicine Meets Biological Networks of Complex Diseases: A Computational Perspective

    OpenAIRE

    Shuo Gu; Jianfeng Pei

    2017-01-01

    With the rapid development of cheminformatics, computational biology, and systems biology, great progress has been made recently in the computational research of Chinese herbal medicine with in-depth understanding towards pharmacognosy. This paper summarized these studies in the aspects of computational methods, traditional Chinese medicine (TCM) compound databases, and TCM network pharmacology. Furthermore, we chose arachidonic acid metabolic network as a case study to demonstrate the regula...

  13. SBMLeditor: effective creation of models in the Systems Biology Markup language (SBML).

    Science.gov (United States)

    Rodriguez, Nicolas; Donizelli, Marco; Le Novère, Nicolas

    2007-03-06

    The need to build a tool to facilitate the quick creation and editing of models encoded in the Systems Biology Markup language (SBML) has been growing with the number of users and the increased complexity of the language. SBMLeditor tries to answer this need by providing a very simple, low level editor of SBML files. Users can create and remove all the necessary bits and pieces of SBML in a controlled way, that maintains the validity of the final SBML file. SBMLeditor is written in JAVA using JCompneur, a library providing interfaces to easily display an XML document as a tree. This decreases dramatically the development time for a new XML editor. The possibility to include custom dialogs for different tags allows a lot of freedom for the editing and validation of the document. In addition to Xerces, SBMLeditor uses libSBML to check the validity and consistency of SBML files. A graphical equation editor allows an easy manipulation of MathML. SBMLeditor can be used as a module of the Systems Biology Workbench. SBMLeditor contains many improvements compared to a generic XML editor, and allow users to create an SBML model quickly and without syntactic errors.

  14. Does constructive neutral evolution play an important role in the origin of cellular complexity? Making sense of the origins and uses of biological complexity.

    Science.gov (United States)

    Speijer, Dave

    2011-05-01

    Recently, constructive neutral evolution has been touted as an important concept for the understanding of the emergence of cellular complexity. It has been invoked to help explain the development and retention of, amongst others, RNA splicing, RNA editing and ribosomal and mitochondrial respiratory chain complexity. The theory originated as a welcome explanation of isolated small scale cellular idiosyncrasies and as a reaction to 'overselectionism'. Here I contend, that in its extended form, it has major conceptual problems, can not explain observed patterns of complex processes, is too easily dismissive of alternative selectionist models, underestimates the creative force of complexity as such, and--if seen as a major evolutionary mechanism for all organisms--could stifle further thought regarding the evolution of highly complex biological processes. Copyright © 2011 WILEY Periodicals, Inc.

  15. Systems Approach to Tourism: A Methodology for Defining Complex Tourism System

    Directory of Open Access Journals (Sweden)

    Jere Jakulin Tadeja

    2017-08-01

    Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.

  16. Metasynthetic computing and engineering of complex systems

    CERN Document Server

    Cao, Longbing

    2015-01-01

    Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy thro

  17. Cu(II AND Zn(II COMPLEX COMPOUNDS WITH BIGUANIDES AROMATIC DERIVATIVES. SYNTHESIS, CHARACTERIZATION, BIOLOGICAL ACTIVITY

    Directory of Open Access Journals (Sweden)

    Ticuţa Negreanu-Pîrjol

    2011-05-01

    Full Text Available In this paper we report the synthesis, physical-chemical characterization and antimicrobial activity of some new complex compounds of hetero-aromatic biguanides ligands, chlorhexidine base (CHX and chlorhexidine diacetate (CHXac2 with metallic ions Cu(II and Zn(II, in different molar ratio. The synthesized complexes were characterized by elemental chemical analysis and differential thermal analysis. The stereochemistry of the metallic ions was determined by infrared spectra, UV-Vis, EPR spectroscopy and magnetic susceptibility in the aim to establish the complexes structures. The biological activity of the new complex compounds was identified in solid technique by measuring minimum inhibition diameter of bacterial and fungal culture, against three standard pathogen strains, Escherichia coli ATCC 25922, Staphilococcus aureus ATCC 25923 and Candida albicans ATCC 10231. The results show an increased specific antimicrobial activity for the complexes chlorhexidine:Cu(II 1:1 and 1:2 compared with the one of the Zn(II complexes.

  18. Complexity: Outline of the NWO strategic theme Dynamics of complex systems

    NARCIS (Netherlands)

    Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; van der Maas, H.; Mulder, B.; Stam, K.; van Steen, M.; Zandee, L.

    2008-01-01

    Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

  19. Complexity : outline of the NWO strategic theme dynamics of complex systems

    NARCIS (Netherlands)

    Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; Maas, van der H.; Mulder, B.; Stam, K.; Steen, van M.; Zandee, L.

    2008-01-01

    Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

  20. Vibrational resonances in biological systems at microwave frequencies.

    Science.gov (United States)

    Adair, Robert K

    2002-03-01

    Many biological systems can be expected to exhibit resonance behavior involving the mechanical vibration of system elements. The natural frequencies of such resonances will, generally, be in the microwave frequency range. Some of these systems will be coupled to the electromagnetic field by the charge distributions they carry, thus admitting the possibility that microwave exposures may generate physiological effects in man and other species. However, such microwave excitable resonances are expected to be strongly damped by interaction with their aqueous biological environment. Although those dissipation mechanisms have been studied, the limitations on energy transfers that follow from the limited coupling of these resonances to the electromagnetic field have not generally been considered. We show that this coupling must generally be very small and thus the absorbed energy is so strongly limited that such resonances cannot affect biology significantly even if the systems are much less strongly damped than expected from basic dissipation models.