WorldWideScience

Sample records for biological model systems

  1. Validation of systems biology models

    NARCIS (Netherlands)

    Hasdemir, D.

    2015-01-01

    The paradigm shift from qualitative to quantitative analysis of biological systems brought a substantial number of modeling approaches to the stage of molecular biology research. These include but certainly are not limited to nonlinear kinetic models, static network models and models obtained by the

  2. Compositional Modeling of Biological Systems

    OpenAIRE

    Zámborszky, Judit

    2010-01-01

    Molecular interactions are wired in a fascinating way resulting in complex behavior of bio-logical systems. Theoretical modeling provides us a useful framework for understanding the dynamics and the function of such networks. The complexity of the biological systems calls for conceptual tools that manage the combinatorial explosion of the set of possible interac-tions. A suitable conceptual tool to attack complexity is compositionality, already success-fully used in the process algebra field ...

  3. Statistical Model Checking for Biological Systems

    DEFF Research Database (Denmark)

    David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

    2014-01-01

    Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...... timed automata and most recently hybrid systems using the tool Uppaal SMC. In this paper we enable the application of SMC to complex biological systems, by combining Uppaal SMC with ANIMO, a plugin of the tool Cytoscape used by biologists, as well as with SimBiology®, a plugin of Matlab to simulate...

  4. Stochastic modelling of dynamical systems in biology

    NARCIS (Netherlands)

    Pellin, Danilo

    2017-01-01

    In this thesis two relevant biological problems will be addressed from a statistical modelling perspective. The first regards the study of hematopoiesis, a still not well understood biological process rarely observable in humans due to technical and ethical reasons. Hematopoiesis is responsible for

  5. 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.

  6. Mathematical Modeling of Complex Biological Systems

    OpenAIRE

    Fischer, Hans Peter

    2008-01-01

    To understand complex biological systems such as cells, tissues, or even the human body, it is not sufficient to identify and characterize the individual molecules in the system. It also is necessary to obtain a thorough understanding of the interaction between molecules and pathways. This is even truer for understanding complex diseases such as cancer, Alzheimer’s disease, or alcoholism. With recent technological advances enabling researchers to monitor complex cellular processes on the mole...

  7. Modelling and Inference Strategies for Biological Systems

    OpenAIRE

    Palmisano, Alida

    2010-01-01

    For many years, computers have played an important role in helping scientists to store, manipulate, and analyze data coming from many different disciplines. In recent years, however, new technological capabilities and new ways of thinking about the usefulness of computer science is extending the reach of computers from simple analysis of collected data to hypothesis generation. The aim of this work is to provide a contribution in the Computational Systems Biology field. The main purpose of...

  8. Modeling and Simulation Tools: From Systems Biology to Systems Medicine.

    Science.gov (United States)

    Olivier, Brett G; Swat, Maciej J; Moné, Martijn J

    2016-01-01

    Modeling is an integral component of modern biology. In this chapter we look into the role of the model, as it pertains to Systems Medicine, and the software that is required to instantiate and run it. We do this by comparing the development, implementation, and characteristics of tools that have been developed to work with two divergent methodologies: Systems Biology and Pharmacometrics. From the Systems Biology perspective we consider the concept of "Software as a Medical Device" and what this may imply for the migration of research-oriented, simulation software into the domain of human health.In our second perspective, we see how in practice hundreds of computational tools already accompany drug discovery and development at every stage of the process. Standardized exchange formats are required to streamline the model exchange between tools, which would minimize translation errors and reduce the required time. With the emergence, almost 15 years ago, of the SBML standard, a large part of the domain of interest is already covered and models can be shared and passed from software to software without recoding them. Until recently the last stage of the process, the pharmacometric analysis used in clinical studies carried out on subject populations, lacked such an exchange medium. We describe a new emerging exchange format in Pharmacometrics which covers the non-linear mixed effects models, the standard statistical model type used in this area. By interfacing these two formats the entire domain can be covered by complementary standards and subsequently the according tools.

  9. Bionic models for identification of biological systems

    Science.gov (United States)

    Gerget, O. M.

    2017-01-01

    This article proposes a clinical decision support system that processes biomedical data. For this purpose a bionic model has been designed based on neural networks, genetic algorithms and immune systems. The developed system has been tested on data from pregnant women. The paper focuses on the approach to enable selection of control actions that can minimize the risk of adverse outcome. The control actions (hyperparameters of a new type) are further used as an additional input signal. Its values are defined by a hyperparameter optimization method. A software developed with Python is briefly described.

  10. A guide to numerical modelling in systems biology

    CERN Document Server

    Deuflhard, Peter

    2015-01-01

    This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks, and identification of model parameters by means of comparisons...

  11. Modeling life the mathematics of biological systems

    CERN Document Server

    Garfinkel, Alan; Guo, Yina

    2017-01-01

    From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. This book develops the mathematical tools essential for students in the life sciences to describe these interacting systems and to understand and predict their behavior. Complex feedback relations and counter-intuitive responses are common in dynamical systems in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models ...

  12. Biochemical Space: A Framework for Systemic Annotation of Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Děd, T.; Šafránek, D.; Červený, Jan; Müller, Stefan; Steuer, Ralf

    2014-01-01

    Roč. 306, JUL (2014), s. 31-44 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * cyanobacteria Subject RIV: EH - Ecology, Behaviour

  13. Review of "Stochastic Modelling for Systems Biology" by Darren Wilkinson

    Directory of Open Access Journals (Sweden)

    Bullinger Eric

    2006-12-01

    Full Text Available Abstract "Stochastic Modelling for Systems Biology" by Darren Wilkinson introduces the peculiarities of stochastic modelling in biology. This book is particularly suited to as a textbook or for self-study, and for readers with a theoretical background.

  14. OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.

    Directory of Open Access Journals (Sweden)

    C Brandon Ogbunugafor

    Full Text Available Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL. Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features.

  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. 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.

  17. Learning (from) the errors of a systems biology model.

    Science.gov (United States)

    Engelhardt, Benjamin; Frőhlich, Holger; Kschischo, Maik

    2016-02-11

    Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open. Missed or unknown external influences as well as erroneous interactions in the model could thus lead to severely misleading results. Here we introduce the dynamic elastic-net, a data driven mathematical method which automatically detects such model errors in ordinary differential equation (ODE) models. We demonstrate for real and simulated data, how the dynamic elastic-net approach can be used to automatically (i) reconstruct the error signal, (ii) identify the target variables of model error, and (iii) reconstruct the true system state even for incomplete or preliminary models. Our work provides a systematic computational method facilitating modelling of open biological systems under uncertain knowledge.

  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. Systematic integration of experimental data and models in systems biology.

    Science.gov (United States)

    Li, Peter; Dada, Joseph O; Jameson, Daniel; Spasic, Irena; Swainston, Neil; Carroll, Kathleen; Dunn, Warwick; Khan, Farid; Malys, Naglis; Messiha, Hanan L; Simeonidis, Evangelos; Weichart, Dieter; Winder, Catherine; Wishart, Jill; Broomhead, David S; Goble, Carole A; Gaskell, Simon J; Kell, Douglas B; Westerhoff, Hans V; Mendes, Pedro; Paton, Norman W

    2010-11-29

    The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources. Taverna workflows have been developed for the automated assembly of quantitative parameterised metabolic networks in the Systems Biology Markup Language (SBML). A SBML model is built in a systematic fashion by the workflows which starts with the construction of a qualitative network using data from a MIRIAM-compliant genome-scale model of yeast metabolism. This is followed by parameterisation of the SBML model with experimental data from two repositories, the SABIO-RK enzyme kinetics database and a database of quantitative experimental results. The models are then calibrated and simulated in workflows that call out to COPASIWS, the web service interface to the COPASI software application for analysing biochemical networks. These systems biology workflows were evaluated for their ability to construct a parameterised model of yeast glycolysis. Distributed information about metabolic reactions that have been described to MIRIAM standards enables the automated assembly of quantitative systems biology models of metabolic networks based on user-defined criteria. Such data integration processes can be implemented as Taverna workflows to provide a rapid overview of the components and their relationships within a biochemical system.

  20. Computational Modeling, Formal Analysis, and Tools for Systems Biology.

    Directory of Open Access Journals (Sweden)

    Ezio Bartocci

    2016-01-01

    Full Text Available As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

  1. Modeling and simulation of biological systems using SPICE language

    Science.gov (United States)

    Lallement, Christophe; Haiech, Jacques

    2017-01-01

    The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems), an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE). BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language), a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems) have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology). PMID:28787027

  2. Systems modelling and the development of coherent cell biological knowledge

    NARCIS (Netherlands)

    Verhoeff, R.; Waarlo, A.J.; Boersma, K.T.

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing systems modelling as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of freeliving

  3. Systems Biology

    Energy Technology Data Exchange (ETDEWEB)

    Wiley, H S.

    2006-06-01

    The biology revolution over the last 50 years has been driven by the ascendancy of molecular biology. This was enthusiastically embraced by most biologists because it took us into increasingly familiar territory. It took mysterious processes, such as the replication of genetic material and assigned them parts that could be readily understood by the human mind. When we think of ''molecular machines'' as being the underlying basis of life, we are using a paradigm derived from everyday experience. However, the price that we paid was a relentless drive towards reductionism and the attendant balkanization of biology. Now along comes ''systems biology'' that promises us a solution to the problem of ''knowing more and more about less and less''. Unlike molecular biology, systems biology appears to be taking us into unfamiliar intellectual territory, such as statistics, mathematics and computer modeling. Not surprisingly, systems biology has met with widespread skepticism and resistance. Why do we need systems biology anyway and how does this new area of research promise to change the face of biology in the next couple of decades?

  4. 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).

  5. Using views of Systems Biology Cloud: application for model building.

    Science.gov (United States)

    Ruebenacker, Oliver; Blinov, Michael

    2011-03-01

    A large and growing network ("cloud") of interlinked terms and records of items of Systems Biology knowledge is available from the web. These items include pathways, reactions, substances, literature references, organisms, and anatomy, all described in different data sets. Here, we discuss how the knowledge from the cloud can be molded into representations (views) useful for data visualization and modeling. We discuss methods to create and use various views relevant for visualization, modeling, and model annotations, while hiding irrelevant details without unacceptable loss or distortion. We show that views are compatible with understanding substances and processes as sets of microscopic compounds and events respectively, which allows the representation of specializations and generalizations as subsets and supersets respectively. We explain how these methods can be implemented based on the bridging ontology Systems Biological Pathway Exchange (SBPAX) in the Systems Biology Linker (SyBiL) we have developed.

  6. 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.

  7. 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.

  8. 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

  9. A distributed approach for parameters estimation in System Biology models

    International Nuclear Information System (INIS)

    Mosca, E.; Merelli, I.; Alfieri, R.; Milanesi, L.

    2009-01-01

    Due to the lack of experimental measurements, biological variability and experimental errors, the value of many parameters of the systems biology mathematical models is yet unknown or uncertain. A possible computational solution is the parameter estimation, that is the identification of the parameter values that determine the best model fitting respect to experimental data. We have developed an environment to distribute each run of the parameter estimation algorithm on a different computational resource. The key feature of the implementation is a relational database that allows the user to swap the candidate solutions among the working nodes during the computations. The comparison of the distributed implementation with the parallel one showed that the presented approach enables a faster and better parameter estimation of systems biology models.

  10. Modeling and simulation of biological systems using SPICE language.

    Directory of Open Access Journals (Sweden)

    Morgan Madec

    Full Text Available The article deals with BB-SPICE (SPICE for Biochemical and Biological Systems, an extension of the famous Simulation Program with Integrated Circuit Emphasis (SPICE. BB-SPICE environment is composed of three modules: a new textual and compact description formalism for biological systems, a converter that handles this description and generates the SPICE netlist of the equivalent electronic circuit and NGSPICE which is an open-source SPICE simulator. In addition, the environment provides back and forth interfaces with SBML (System Biology Markup Language, a very common description language used in systems biology. BB-SPICE has been developed in order to bridge the gap between the simulation of biological systems on the one hand and electronics circuits on the other hand. Thus, it is suitable for applications at the interface between both domains, such as development of design tools for synthetic biology and for the virtual prototyping of biosensors and lab-on-chip. Simulation results obtained with BB-SPICE and COPASI (an open-source software used for the simulation of biochemical systems have been compared on a benchmark of models commonly used in systems biology. Results are in accordance from a quantitative viewpoint but BB-SPICE outclasses COPASI by 1 to 3 orders of magnitude regarding the computation time. Moreover, as our software is based on NGSPICE, it could take profit of incoming updates such as the GPU implementation, of the coupling with powerful analysis and verification tools or of the integration in design automation tools (synthetic biology.

  11. Probabilistic Model Checking of Biological Systems with Uncertain Kinetic Rates

    Science.gov (United States)

    Barbuti, Roberto; Levi, Francesca; Milazzo, Paolo; Scatena, Guido

    We present an abstraction of the probabilistic semantics of Multiset Rewriting to formally express systems of reactions with uncertain kinetic rates. This allows biological systems modelling when the exact rates are not known, but are supposed to lie in some intervals. On these (abstract) models we perform probabilistic model checking obtaining lower and upper bounds for the probabilities of reaching states satisfying given properties. These bounds are under- and over-approximations, respectively, of the probabilities one would obtain by verifying the models with exact kinetic rates belonging to the intervals.

  12. Systems Biology

    Indian Academy of Sciences (India)

    IAS Admin

    Systems biology seeks to study biological systems as a whole, contrary to the reductionist approach that has dominated biology. Such a view of biological systems emanating from strong foundations of molecular level understanding of the individual components in terms of their form, function and interactions is promising to ...

  13. Systems Biology in Immunology – A Computational Modeling Perspective

    Science.gov (United States)

    Germain, Ronald N.; Meier-Schellersheim, Martin; Nita-Lazar, Aleksandra; Fraser, Iain D. C.

    2011-01-01

    Systems biology is an emerging discipline that combines high-content, multiplexed measurements with informatic and computational modeling methods to better understand biological function at various scales. Here we present a detailed review of the methods used to create computational models and conduct simulations of immune function, We provide descriptions of the key data gathering techniques employed to generate the quantitative and qualitative data required for such modeling and simulation and summarize the progress to date in applying these tools and techniques to questions of immunological interest, including infectious disease. We include comments on what insights modeling can provide that complement information obtained from the more familiar experimental discovery methods used by most investigators and why quantitative methods are needed to eventually produce a better understanding of immune system operation in health and disease. PMID:21219182

  14. 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.

  15. Modelling the crop: from system dynamics to systems biology

    NARCIS (Netherlands)

    Yin, X.; Struik, P.C.

    2010-01-01

    There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models

  16. 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.

  17. Revision history aware repositories of computational models of biological systems.

    Science.gov (United States)

    Miller, Andrew K; Yu, Tommy; Britten, Randall; Cooling, Mike T; Lawson, James; Cowan, Dougal; Garny, Alan; Halstead, Matt D B; Hunter, Peter J; Nickerson, David P; Nunns, Geo; Wimalaratne, Sarala M; Nielsen, Poul M F

    2011-01-14

    Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs) for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. We have extended the Physiome Model Repository software to be fully revision history aware

  18. Revision history aware repositories of computational models of biological systems

    Directory of Open Access Journals (Sweden)

    Nickerson David P

    2011-01-01

    Full Text Available Abstract Background Building repositories of computational models of biological systems ensures that published models are available for both education and further research, and can provide a source of smaller, previously verified models to integrate into a larger model. One problem with earlier repositories has been the limitations in facilities to record the revision history of models. Often, these facilities are limited to a linear series of versions which were deposited in the repository. This is problematic for several reasons. Firstly, there are many instances in the history of biological systems modelling where an 'ancestral' model is modified by different groups to create many different models. With a linear series of versions, if the changes made to one model are merged into another model, the merge appears as a single item in the history. This hides useful revision history information, and also makes further merges much more difficult, as there is no record of which changes have or have not already been merged. In addition, a long series of individual changes made outside of the repository are also all merged into a single revision when they are put back into the repository, making it difficult to separate out individual changes. Furthermore, many earlier repositories only retain the revision history of individual files, rather than of a group of files. This is an important limitation to overcome, because some types of models, such as CellML 1.1 models, can be developed as a collection of modules, each in a separate file. The need for revision history is widely recognised for computer software, and a lot of work has gone into developing version control systems and distributed version control systems (DVCSs for tracking the revision history. However, to date, there has been no published research on how DVCSs can be applied to repositories of computational models of biological systems. Results We have extended the Physiome Model

  19. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  20. Mathematical modeling of the evolution of a simple biological system

    Digital Repository Service at National Institute of Oceanography (India)

    Gonsalves, M.J.B.D.; Neetu, S.; Krishnan, K.P.; Attri, K.; LokaBharathi, P.A.

    Paula, Goa 403 004, India. Phone: +91 0832 2450624, Fax: +91 0832 2450606, e-mail: mjudith@nio.org Introduction In India, classroom education in biology does not generally include an exercise in which the data can be used to develop models.... This has hampered exposure to quantitative tools in biology, much to the disadvantage of students. The purpose of this note is to report an exercise we carried out to expose traditional biologists educated in India to mathematical modelling of biological...

  1. Systemic Modeling of Biological Functions in Consideration of Physiome Project

    Science.gov (United States)

    Minamitani, Haruyuki

    Emerging of the physiome project provides various influences on the medical, biological and pharmaceutical development. In this paper, as an example of physiome research, neural network model analysis providing the conduction mechanisms of pain and tactile sensations was presented, and the functional relations between neural activities of the network cells and stimulus intensity applied on the peripheral receptive fields were described. The modeling presented here is based on the various assumptions made by the results of physiological and anatomical studies reported in the literature. The functional activities of spinothalamic and thalamocortical cells show a good agreement with the physiological and psychophysical functions of somatosensory system that are very instructive for covering the gap between physiologically and psychophysically aspects of pain and tactile sensation.

  2. Computational brain models: Advances from system biology and future challenges

    Directory of Open Access Journals (Sweden)

    George E. Barreto

    2015-02-01

    Full Text Available Computational brain models focused on the interactions between neurons and astrocytes, modeled via metabolic reconstructions, are reviewed. The large source of experimental data provided by the -omics techniques and the advance/application of computational and data-management tools are being fundamental. For instance, in the understanding of the crosstalk between these cells, the key neuroprotective mechanisms mediated by astrocytes in specific metabolic scenarios (1 and the identification of biomarkers for neurodegenerative diseases (2,3. However, the modeling of these interactions demands a clear view of the metabolic and signaling pathways implicated, but most of them are controversial and are still under evaluation (4. Hence, to gain insight into the complexity of these interactions a current view of the main pathways implicated in the neuron-astrocyte communication processes have been made from recent experimental reports and reviews. Furthermore, target problems, limitations and main conclusions have been identified from metabolic models of the brain reported from 2010. Finally, key aspects to take into account into the development of a computational model of the brain and topics that could be approached from a systems biology perspective in future research are highlighted.

  3. Micrasterias as a model system in plant cell biology

    Directory of Open Access Journals (Sweden)

    Ursula Luetz-Meindl

    2016-07-01

    Full Text Available The unicellular freshwater alga Micrasterias denticulata is an exceptional organism due to its extraordinary star-shaped, highly symmetric morphology and has thus attracted the interest of researchers for many decades. As a member of the Streptophyta, Micrasterias is not only genetically closely related to higher land plants but shares common features with them in many physiological and cell biological aspects. These facts, together with its considerable cell size of about 200 µm, its modest cultivation conditions and the uncomplicated accessibility particularly to any microscopic techniques, make Micrasterias a very well suited cell biological plant model system. The review focuses particularly on cell wall formation and composition, dictyosomal structure and function, cytoskeleton control of growth and morphogenesis as well as on ionic regulation and signal transduction. It has been also shown in the recent years that Micrasterias is a highly sensitive indicator for environmental stress impact such as heavy metals, high salinity, oxidative stress or starvation. Stress induced organelle degradation, autophagy, adaption and detoxification mechanisms have moved in the center of interest and have been investigated with modern microscopic techniques such as 3-D- and analytical electron microscopy as well as with biochemical, physiological and molecular approaches. This review is intended to summarize and discuss the most important results obtained in Micrasterias in the last 20 years and to compare the results to similar processes in higher plant cells.

  4. First Steps in Computational Systems Biology: A Practical Session in Metabolic Modeling and Simulation

    Science.gov (United States)

    Reyes-Palomares, Armando; Sanchez-Jimenez, Francisca; Medina, Miguel Angel

    2009-01-01

    A comprehensive understanding of biological functions requires new systemic perspectives, such as those provided by systems biology. Systems biology approaches are hypothesis-driven and involve iterative rounds of model building, prediction, experimentation, model refinement, and development. Developments in computer science are allowing for ever…

  5. Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.

    Science.gov (United States)

    MacLeod, Miles; Nersessian, Nancy J

    2018-01-08

    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations.

  6. Modelling biological and chemically induced precipitation of calcium phosphate in enhanced biological phosphorus removal systems.

    Science.gov (United States)

    Barat, R; Montoya, T; Seco, A; Ferrer, J

    2011-06-01

    The biologically induced precipitation processes can be important in wastewater treatment, in particular treating raw wastewater with high calcium concentration combined with Enhanced Biological Phosphorus Removal. Currently, there is little information and experience in modelling jointly biological and chemical processes. This paper presents a calcium phosphate precipitation model and its inclusion in the Activated Sludge Model No 2d (ASM2d). The proposed precipitation model considers that aqueous phase reactions quickly achieve the chemical equilibrium and that aqueous-solid change is kinetically governed. The model was calibrated using data from four experiments in a Sequencing Batch Reactor (SBR) operated for EBPR and finally validated with two experiments. The precipitation model proposed was able to reproduce the dynamics of amorphous calcium phosphate (ACP) formation and later crystallization to hydroxyapatite (HAP) under different scenarios. The model successfully characterised the EBPR performance of the SBR, including the biological, physical and chemical processes. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. An Abstraction Theory for Qualitative Models of Biological Systems

    Directory of Open Access Journals (Sweden)

    Richard Banks

    2010-10-01

    Full Text Available Multi-valued network models are an important qualitative modelling approach used widely by the biological community. In this paper we consider developing an abstraction theory for multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. This is important as it aids the analysis and comparison of multi-valued networks and in particular, helps address the well-known problem of state space explosion associated with such analysis. We also consider developing techniques for efficiently identifying abstractions and so provide a basis for the automation of this task. We illustrate the theory and techniques developed by investigating the identification of abstractions for two published MVN models of the lysis-lysogeny switch in the bacteriophage lambda.

  8. How Modeling Standards, Software, and Initiatives Support Reproducibility in Systems Biology and Systems Medicine.

    Science.gov (United States)

    Waltemath, Dagmar; Wolkenhauer, Olaf

    2016-10-01

    Only reproducible results are of significance to science. The lack of suitable standards and appropriate support of standards in software tools has led to numerous publications with irreproducible results. Our objectives are to identify the key challenges of reproducible research and to highlight existing solutions. In this paper, we summarize problems concerning reproducibility in systems biology and systems medicine. We focus on initiatives, standards, and software tools that aim to improve the reproducibility of simulation studies. The long-term success of systems biology and systems medicine depends on trustworthy models and simulations. This requires openness to ensure reusability and transparency to enable reproducibility of results in these fields.

  9. Systems Biology of Metabolism.

    Science.gov (United States)

    Nielsen, Jens

    2017-06-20

    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 described, and two different types of mathematical models used for studying metabolism are discussed: kinetic models and genome-scale metabolic models. The use of different omics technologies, including transcriptomics, proteomics, metabolomics, and fluxomics, for studying metabolism is presented. Finally, the application of systems biology for analyzing global regulatory structures, engineering the metabolism of cell factories, and analyzing human diseases is discussed.

  10. Model reduction in mathematical pharmacology : Integration, reduction and linking of PBPK and systems biology models.

    Science.gov (United States)

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

    2018-03-26

    In this paper we present a framework for the reduction and linking of physiologically based pharmacokinetic (PBPK) models with models of systems biology to describe the effects of drug administration across multiple scales. To address the issue of model complexity, we propose the reduction of each type of model separately prior to being linked. We highlight the use of balanced truncation in reducing the linear components of PBPK models, whilst proper lumping is shown to be efficient in reducing typically nonlinear systems biology type models. The overall methodology is demonstrated via two example systems; a model of bacterial chemotactic signalling in Escherichia coli and a model of extracellular regulatory kinase activation mediated via the extracellular growth factor and nerve growth factor receptor pathways. Each system is tested under the simulated administration of three hypothetical compounds; a strong base, a weak base, and an acid, mirroring the parameterisation of pindolol, midazolam, and thiopental, respectively. Our method can produce up to an 80% decrease in simulation time, allowing substantial speed-up for computationally intensive applications including parameter fitting or agent based modelling. The approach provides a straightforward means to construct simplified Quantitative Systems Pharmacology models that still provide significant insight into the mechanisms of drug action. Such a framework can potentially bridge pre-clinical and clinical modelling - providing an intermediate level of model granularity between classical, empirical approaches and mechanistic systems describing the molecular scale.

  11. Caenorhabditis elegans - A model system for space biology studies

    Science.gov (United States)

    Johnson, Thomas E.; Nelson, Gregory A.

    1991-01-01

    The utility of the nematode Caenorhabditis elegans in studies spanning aspects of development, aging, and radiobiology is reviewed. These topics are interrelated via cellular and DNA repair processes especially in the context of oxidative stress and free-radical metabolism. The relevance of these research topics to problems in space biology is discussed and properties of the space environment are outlined. Exposure to the space-flight environment can induce rapid changes in living systems that are similar to changes occurring during aging; manipulation of these environmental parameters may represent an experimental strategy for studies of development and senescence. The current and future opportunities for such space-flight experimentation are presented.

  12. Aspergilli: Models for systems biology in filamentous fungi

    DEFF Research Database (Denmark)

    Brandl, Julian; Andersen, Mikael Rørdam

    2017-01-01

    Aspergillus is a diverse genus of filamentous fungi including common house hold mold as well as human pathogens. More than 350 species are currently part of this genus and all their genomes are soon to be sequenced. The availability of this vast amount of data will allow for more in-depth underst......Aspergillus is a diverse genus of filamentous fungi including common house hold mold as well as human pathogens. More than 350 species are currently part of this genus and all their genomes are soon to be sequenced. The availability of this vast amount of data will allow for more in......-depth understanding of genetic traits governing desirable properties like enzyme production as well as the pathogenic potency of the organisms. In this review we give an overview of the systems biology research conducted in Aspergilli. This research has covered omics technologies like genomics, transcriptomics...... and proteomics where outstanding contributions are highlighted. From past developments it becomes apparent that CRISPR technology will speed up genetic research in the Aspergillus field. This speed up will allow for an increase in systems biology targeted research by accelerating data generation. The increase...

  13. Introducing Systems Biology to Bioscience students through mathematical modelling. A practical module

    Directory of Open Access Journals (Sweden)

    Néstor V. Torres Darias

    2013-11-01

    Full Text Available Systems Biology, one of the current approaches to the understanding of living things, aims to understand the behaviour of living systems through the creation of mathematical models that integrate the available knowledge of the system’s component parts and the relations among them. Accordingly, model building should play a central part in any biology degree program. One difficulty that we face when confronted with this task, however, is that the mathematical background of undergraduate students is very often deficient in essential concepts required for dynamic mathematical modelling. In this practical module, students are introduced to the basic techniques of mathematical modelling and computer simulation from a Systems Biology perspective.

  14. Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System

    Science.gov (United States)

    2016-10-12

    stratification (i.e., caste system ) that characterizes both and leads to some actors in the groups being more susceptible to disease and other risks. The RFID...Social Foraging Behavior in a Biological Model System " The views, opinions and/or findings contained in this report are those of the author(s) and...reviewed journals: Final Report: "Social and Behavioral Science: Monitoring Social Foraging Behavior in a Biological Model System " Report Title The

  15. Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters.

    Science.gov (United States)

    Liu, Fei; Heiner, Monika; Yang, Ming

    2016-01-01

    Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information.

  16. Systems Modelling and the Development of Coherent Understanding of Cell Biology

    Science.gov (United States)

    Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.

    2008-01-01

    This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…

  17. 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...

  18. Use of genome-scale metabolic models in evolutionary systems biology.

    Science.gov (United States)

    Papp, Balázs; Szappanos, Balázs; Notebaart, Richard A

    2011-01-01

    One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for hundreds of genes, genome-scale systems biology models of metabolic networks have already provided valuable insights into the evolution of metabolic gene contents and phenotypes of yeast and other microbial species. Here we review the recent use of these computational models to predict the fitness effect of mutations, genetic interactions, evolutionary outcomes, and to decipher the mechanisms of mutational robustness. While these studies have demonstrated that even simplified models of biochemical reaction networks can be highly informative for evolutionary analyses, they have also revealed the weakness of this modeling framework to quantitatively predict mutational effects, a challenge that needs to be addressed for future progress in evolutionary systems biology.

  19. 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.

  20. 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

  1. 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.

  2. Modelling, abstraction, and computation in systems biology: A view from computer science.

    Science.gov (United States)

    Melham, Tom

    2013-04-01

    Systems biology is centrally engaged with computational modelling across multiple scales and at many levels of abstraction. Formal modelling, precise and formalised abstraction relationships, and computation also lie at the heart of computer science--and over the past decade a growing number of computer scientists have been bringing their discipline's core intellectual and computational tools to bear on biology in fascinating new ways. This paper explores some of the apparent points of contact between the two fields, in the context of a multi-disciplinary discussion on conceptual foundations of systems biology. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Evaluation and modeling of HIV based on communication theory in biological systems.

    Science.gov (United States)

    Dong, Miaowu; Li, Wenrong; Xu, Xi

    2016-12-01

    Some forms of communication are used in biological systems such as HIV transmission in human beings. In this paper, we plan to get a unique insight into biological communication systems generally through the analogy between HIV infection and electrical communication system. The model established in this paper can be used to test and simulate various communication systems since it provides researchers with an opportunity. We interpret biological communication systems by using telecommunications exemplification from a layered communication protocol developed before and use the model to indicate HIV spreading. We also implement a simulation of HIV infection based on the layered communication protocol to predict the development of this disease and the results prove the validity of the model. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Thomas, Marcus; Schwartz, Russell

    2017-06-01

    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.

  5. 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.

  6. QNS measurements on water in biological and model systems

    Energy Technology Data Exchange (ETDEWEB)

    Trantham, E.C.; Rorschach, H.E.; Clegg, J.C.; Hazlewood, C.F.; Nicklow, R.M.

    1981-01-01

    Results are presented on the quasi-elastic spectra of 0.95 THz neutrons scattered from pure water, a 20% agarose gel and cysts of the brine shrimp (Artemia) of hydration 1.2 gms H/sub 2/O per gm of dry solids. The lines are interpreted with a two-component model in which the hydration water scatters elastically and the free water is described by a jump-diffusion correlation function. The results for the line widths GAMMA(Q/sup 2/) are in good agreement with previous measurements for the water sample but show deviations from pure water at large Q for agarose and the Artemia cysts that suggest an increased value of the residence time in the jump-diffusion model.

  7. QNS measurements of water in biological and model systems

    Energy Technology Data Exchange (ETDEWEB)

    Trantham, E.C.; Rorschach, H.E.; Clegg, J.C.; Hazlewood, C.F.; Nicklow, R.M.

    1982-01-01

    Results are presented on the quasi-elastic spectra of 0.95 THz neutrons scattered from pure water, a 20% agarose gel and cysts of the brine shrimp (Artemia) of hydration 1.2 gms H/sub 2/O per gm of dry solids. The lines are interpreted with a two-component model in which the hydration water scatters elastically and the free water is described by a jump-diffusion correlation function. The results for the line widths GAMMA(Q/sup 2/) are in good agreement with previous measurements for the water sample but show deviations from pure water at large Q for agarose and the Artemia cysts that suggest an increased value of the residence time in the jump-diffusion model.

  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. A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

    Science.gov (United States)

    Gilbert, David

    2016-01-01

    Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour

  10. Pseudorandom numbers: evolutionary models in image processing, biology, and nonlinear dynamic systems

    Science.gov (United States)

    Yaroslavsky, Leonid P.

    1996-11-01

    We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.

  11. Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study

    Directory of Open Access Journals (Sweden)

    King John R

    2010-03-01

    Full Text Available Abstract Background Stochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks. Results In this case study, we solve an auxin-transport model using analytical methods, deterministic numerical simulations and stochastic numerical simulations. Although the three approaches in general predict the same behaviour, the approaches provide different information that we use to gain distinct insights into the modelled biological system. We show in particular that the analytical approach readily provides straightforward mathematical expressions for the concentrations and transport speeds, while the stochastic simulations naturally provide information on the variability of the system. Conclusions Our study provides a constructive comparison which highlights the advantages and disadvantages of each of the considered modelling approaches. This will prove helpful to researchers when weighing up which modelling approach to select. In addition, the paper goes some way to bridging the gap between these approaches, which in the future we hope will lead to integrative hybrid models.

  12. A model of heavy ion detection in physical and biological systems

    International Nuclear Information System (INIS)

    Waligorski, M.P.R.

    1988-01-01

    Track structure theory (the Katz model) and its application to the detection of heavy ions in physical and biological systems are reviewed. Following the use of a new corrected formula describing the radial distribution of average dose around the path of a heavy ion, based on results of Monte Carlo calculations and on results of experimental measurements, better agreement is achieved between model calculations and experimentally measured relative effectiveness, for enzymatic and viral systems, for the Fricke dosemeter and for alanine and thermoluminescent (TDL-700) dosemeters irradiated with beams of heavy charged particles. From experimentally measured RBE dependences for survival and frequency of neoplastic transformations in a mammalian cell culture irradiated with beams of energetic heavy ions, values of model parameters for these biological endpoints have been extracted, and a model extrapolation to the low-dose region performed. Results of model calculations are then compared with evaluations of the lung cancer hazard in populations exposed to radon and its progeny. The model can be applied to practical phenomenological analysis of radiation damage in solid-state systems and to dosimetry of charged particle and fast neutron beams using a variety of detectors. The model can also serve as a guide in building more basic models of the action of ionizing radiation with physical and biological systems and guide of development of models of radiation risk more relevant than that used presently. 185 refs., 31 figs., 3 tabs. (author)

  13. Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.

    Science.gov (United States)

    Tsigkinopoulou, Areti; Baker, Syed Murtuza; Breitling, Rainer

    2017-06-01

    Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. CEBS object model for systems biology data, SysBio-OM.

    Science.gov (United States)

    Xirasagar, Sandhya; Gustafson, Scott; Merrick, B Alex; Tomer, Kenneth B; Stasiewicz, Stanley; Chan, Denny D; Yost, Kenneth J; Yates, John R; Sumner, Susan; Xiao, Nianqing; Waters, Michael D

    2004-09-01

    To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http

  15. The SEEK: a platform for sharing data and models in systems biology.

    Science.gov (United States)

    Wolstencroft, Katy; Owen, Stuart; du Preez, Franco; Krebs, Olga; Mueller, Wolfgang; Goble, Carole; Snoep, Jacky L

    2011-01-01

    Systems biology research is typically performed by multidisciplinary groups of scientists, often in large consortia and in distributed locations. The data generated in these projects tend to be heterogeneous and often involves high-throughput "omics" analyses. Models are developed iteratively from data generated in the projects and from the literature. Consequently, there is a growing requirement for exchanging experimental data, mathematical models, and scientific protocols between consortium members and a necessity to record and share the outcomes of experiments and the links between data and models. The overall output of a research consortium is also a valuable commodity in its own right. The research and associated data and models should eventually be available to the whole community for reuse and future analysis. The SEEK is an open-source, Web-based platform designed for the management and exchange of systems biology data and models. The SEEK was originally developed for the SysMO (systems biology of microorganisms) consortia, but the principles and objectives are applicable to any systems biology project. The SEEK provides an index of consortium resources and acts as gateway to other tools and services commonly used in the community. For example, the model simulation tool, JWS Online, has been integrated into the SEEK, and a plug-in to PubMed allows publications to be linked to supporting data and author profiles in the SEEK. The SEEK is a pragmatic solution to data management which encourages, but does not force, researchers to share and disseminate their data to community standard formats. It provides tools to assist with management and annotation as well as incentives and added value for following these recommendations. Data exchange and reuse rely on sufficient annotation, consistent metadata descriptions, and the use of standard exchange formats for models, data, and the experiments they are derived from. In this chapter, we present the SEEK platform

  16. Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level

    Science.gov (United States)

    Thakar, Juilee; Albert, Réka

    The following sections are included: * Introduction * Boolean Network Concepts and History * Extensions of the Classical Boolean Framework * Boolean Inference Methods and Examples in Biology * Dynamic Boolean Models: Examples in Plant Biology, Developmental Biology and Immunology * Conclusions * References

  17. 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.

  18. Multilevel systems biology modeling characterized the atheroprotective efficiencies of modified dairy fats in a hamster model.

    Science.gov (United States)

    Martin, Jean-Charles; Berton, Amélie; Ginies, Christian; Bott, Romain; Scheercousse, Pierre; Saddi, Alessandra; Gripois, Daniel; Landrier, Jean-François; Dalemans, Daniel; Alessi, Marie-Christine; Delplanque, Bernadette

    2015-09-01

    We assessed the atheroprotective efficiency of modified dairy fats in hyperlipidemic hamsters. A systems biology approach was implemented to reveal and quantify the dietary fat-related components of the disease. Three modified dairy fats (40% energy) were prepared from regular butter by mixing with a plant oil mixture, by removing cholesterol alone, or by removing cholesterol in combination with reducing saturated fatty acids. A plant oil mixture and a regular butter were used as control diets. The atherosclerosis severity (aortic cholesteryl-ester level) was higher in the regular butter-fed hamsters than in the other four groups (P metabolism" appeared central to atherogenic development relative to diets. The "vitamin E metabolism" cluster was the main driver of atheroprotection with the best performing transformed dairy fat. Under conditions that promote atherosclerosis, the impact of dairy fats on atherogenesis could be greatly ameliorated by technological modifications. Our modeling approach allowed for identifying and quantifying the contribution of complex factors to atherogenic development in each dietary setup. Copyright © 2015 the American Physiological Society.

  19. How causal analysis can reveal autonomy in models of biological systems

    Science.gov (United States)

    Marshall, William; Kim, Hyunju; Walker, Sara I.; Tononi, Giulio; Albantakis, Larissa

    2017-11-01

    Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system-whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause-effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause-effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (Schizosaccharomyces pombe) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem. This article is part of the themed issue 'Reconceptualizing the origins of life'.

  20. MODELLING OF RADIONUCLIDE MIGRATION IN THE SYSTEM OF NUCLEAR POWER PLANT BIOLOGICAL PONDS

    Directory of Open Access Journals (Sweden)

    Ю. Кутлахмедов

    2011-04-01

    Full Text Available Migration of radionuclide coming from nuclear power plant into the system of biological pondsand then into the water reservoir-cooler is considered in the article. The theme of the work ismodeling of radionuclide migration process in the system of biological ponds on the example of thePivdennoukrainska nuclear power plant using chamber models method. Typical water ecosystemconsisting of three chambers (chamber-water, chamber-biota and chamber-bed silt was the basistaken by the authors. Application of chamber models method allowed authors to develop thedynamic chamber model of radionuclide migration in nuclear power plant biological ponds. Thismodel allows to forecast values and dynamics of radioactive water pollution based on limitedecosystem monitoring data. Thus, parameters of radioactive capacity of nuclear power plantbiological ponds system and water reservoir-cooler were modeled by authors, the estimation andprognosis of radionuclide distribution and accumulation in the system of nuclear power plantbiological ponds were done. Authors also explain the roles of basin water, biomass and bed silt inradionuclide deposition

  1. mlegp: statistical analysis for computer models of biological systems using R.

    Science.gov (United States)

    Dancik, Garrett M; Dorman, Karin S

    2008-09-01

    Gaussian processes (GPs) are flexible statistical models commonly used for predicting output from complex computer codes. As such, GPs are well suited for the analysis of computer models of biological systems, which have been traditionally difficult to analyze due to their high-dimensional, non-linear and resource-intensive nature. We describe an R package, mlegp, that fits GPs to computer model outputs and performs sensitivity analysis to identify and characterize the effects of important model inputs. http://www.biomath.org/mlegp

  2. 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

  3. 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.

  4. Exploring behaviors of stochastic differential equation models of biological systems using change of measures

    Directory of Open Access Journals (Sweden)

    Jha Sumit

    2012-04-01

    Full Text Available Abstract Stochastic Differential Equations (SDE are often used to model the stochastic dynamics of biological systems. Unfortunately, rare but biologically interesting behaviors (e.g., oncogenesis can be difficult to observe in stochastic models. Consequently, the analysis of behaviors of SDE models using numerical simulations can be challenging. We introduce a method for solving the following problem: given a SDE model and a high-level behavioral specification about the dynamics of the model, algorithmically decide whether the model satisfies the specification. While there are a number of techniques for addressing this problem for discrete-state stochastic models, the analysis of SDE and other continuous-state models has received less attention. Our proposed solution uses a combination of Bayesian sequential hypothesis testing, non-identically distributed samples, and Girsanov's theorem for change of measures to examine rare behaviors. We use our algorithm to analyze two SDE models of tumor dynamics. Our use of non-identically distributed samples sampling contributes to the state of the art in statistical verification and model checking of stochastic models by providing an effective means for exposing rare events in SDEs, while retaining the ability to compute bounds on the probability that those events occur.

  5. Exploring behaviors of stochastic differential equation models of biological systems using change of measures.

    Science.gov (United States)

    Jha, Sumit Kumar; Langmead, Christopher James

    2012-04-12

    Stochastic Differential Equations (SDE) are often used to model the stochastic dynamics of biological systems. Unfortunately, rare but biologically interesting behaviors (e.g., oncogenesis) can be difficult to observe in stochastic models. Consequently, the analysis of behaviors of SDE models using numerical simulations can be challenging. We introduce a method for solving the following problem: given a SDE model and a high-level behavioral specification about the dynamics of the model, algorithmically decide whether the model satisfies the specification. While there are a number of techniques for addressing this problem for discrete-state stochastic models, the analysis of SDE and other continuous-state models has received less attention. Our proposed solution uses a combination of Bayesian sequential hypothesis testing, non-identically distributed samples, and Girsanov's theorem for change of measures to examine rare behaviors. We use our algorithm to analyze two SDE models of tumor dynamics. Our use of non-identically distributed samples sampling contributes to the state of the art in statistical verification and model checking of stochastic models by providing an effective means for exposing rare events in SDEs, while retaining the ability to compute bounds on the probability that those events occur.

  6. Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System

    Energy Technology Data Exchange (ETDEWEB)

    Stenner, Robert D.; Hadley, Donald L.; Armstrong, Peter R.; Buck, John W.; Hoopes, Bonnie L.; Janus, Michael C.

    2001-03-01

    Indoor air quality effects on human health are of increasing concern to public health agencies and building owners. The prevention and treatment of 'sick building' syndrome and the spread of air-borne diseases in hospitals, for example, are well known priorities. However, increasing attention is being directed to the vulnerability of our public buildings/places, public security and national defense facilities to terrorist attack or the accidental release of air-borne biological pathogens, harmful chemicals, or radioactive contaminants. The Indoor Air Nuclear, Biological, and Chemical Health Modeling and Assessment System (IA-NBC-HMAS) was developed to serve as a health impact analysis tool for use in addressing these concerns. The overall goal was to develop a user-friendly fully functional prototype Health Modeling and Assessment system, which will operate under the PNNL FRAMES system for ease of use and to maximize its integration with other modeling and assessment capabilities accessible within the FRAMES system (e.g., ambient air fate and transport models, water borne fate and transport models, Physiologically Based Pharmacokinetic models, etc.). The prototype IA-NBC-HMAS is designed to serve as a functional Health Modeling and Assessment system that can be easily tailored to meet specific building analysis needs of a customer. The prototype system was developed and tested using an actual building (i.e., the Churchville Building located at the Aberdeen Proving Ground) and release scenario (i.e., the release and measurement of tracer materials within the building) to ensure realism and practicality in the design and development of the prototype system. A user-friendly "demo" accompanies this report to allow the reader the opportunity for a "hands on" review of the prototype system's capability.

  7. 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.

  8. Applications of Systems Genetics and Biology for Obesity Using Pig Models

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Kadarmideen, Haja N.

    2016-01-01

    approach, a branch of systems biology. In this chapter, we will describe the state of the art of genetic studies on human obesity, using pig populations. We will describe the features of using the pig as a model for human obesity and briefly discuss the genetics of obesity, and we will focus on systems......In many biomedical research areas, animals have been used as a model to increase the understanding of molecular mechanisms involved in human diseases. One of those areas is human obesity, where porcine models are increasingly used. The pig shows genetic and physiological features that are very...... similar to humans and have shown to be an excellent model for human obesity. Using pig populations, many genetic studies have been performed to unravel the genetic architecture of human obesity. Most of them are pinpointing toward single genes, but more and more studies focus on a systems genetics...

  9. Biologically inspired control and modeling of (biorobotic systems and some applications of fractional calculus in mechanics

    Directory of Open Access Journals (Sweden)

    Lazarević Mihailo P.

    2013-01-01

    Full Text Available In this paper, the applications of biologically inspired modeling and control of (biomechanical (nonredundant mechanisms are presented, as well as newly obtained results of author in mechanics which are based on using fractional calculus. First, it is proposed to use biological analog-synergy due to existence of invariant features in the execution of functional motion. Second, the model of (biomechanical system may be obtained using another biological concept called distributed positioning (DP, which is based on the inertial properties and actuation of joints of considered mechanical system. In addition, it is proposed to use other biological principles such as: principle of minimum interaction, which takes a main role in hierarchical structure of control and self-adjusting principle (introduce local positive/negative feedback on control with great amplifying, which allows efficiently realization of control based on iterative natural learning. Also, new, recently obtained results of the author in the fields of stability, electroviscoelasticity, and control theory are presented which are based on using fractional calculus (FC. [Projekat Ministarstva nauke Republike Srbije, br. 35006

  10. 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.

  11. The Physics behind Systems Biology

    Directory of Open Access Journals (Sweden)

    Radde Nicole E.

    2016-12-01

    Full Text Available Systems Biology is a young and rapidly evolving research field, which combines experimental techniques and mathematical modeling in order to achieve a mechanistic understanding of processes underlying the regulation and evolution of living systems. Systems Biology is often associated with an Engineering approach: The purpose is to formulate a data-rich, detailed simulation model that allows to perform numerical (‘in silico’ experiments and then draw conclusions about the biological system. While methods from Engineering may be an appropriate approach to extending the scope of biological investigations to experimentally inaccessible realms and to supporting data-rich experimental work, it may not be the best strategy in a search for design principles of biological systems and the fundamental laws underlying Biology. Physics has a long tradition of characterizing and understanding emergent collective behaviors in systems of interacting units and searching for universal laws. Therefore, it is natural that many concepts used in Systems Biology have their roots in Physics. With an emphasis on Theoretical Physics, we will here review the ‘Physics core’ of Systems Biology, show how some success stories in Systems Biology can be traced back to concepts developed in Physics, and discuss how Systems Biology can further benefit from its Theoretical Physics foundation.

  12. Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

    International Nuclear Information System (INIS)

    Eschrich, Steven; Zhang Hongling; Zhao Haiyan; Boulware, David; Lee, Ji-Hyun; Bloom, Gregory; Torres-Roca, Javier F.

    2009-01-01

    Purpose: The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials: Radiosensitivity, as represented by the survival fraction at 2 Gy was modeled in 48 human cancer cell lines. We applied a linear regression algorithm that integrates gene expression with biological variables, including ras status (mut/wt), tissue of origin and p53 status (mut/wt). Results: The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression analysis. This network was reduced to a 10-hub network that includes c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1, and IRF1. Nine targets associated with radiosensitization drugs are linked to the network, demonstrating clinical relevance. Furthermore, the model identified four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis, as was the tissue of origin, and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included DNA repair, cell cycle, apoptosis, and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon, and breast cancers. Conclusion: We have developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We believe this platform will play a central role in the integration of biology into clinical radiation oncology practice.

  13. Modeling of the bacterial mechanism of methicillin-resistance by a systems biology approach.

    Directory of Open Access Journals (Sweden)

    Ida Autiero

    Full Text Available BACKGROUND: A microorganism is a complex biological system able to preserve its functional features against external perturbations and the ability of the living systems to oppose to these external perturbations is defined "robustness". The antibiotic resistance, developed by different bacteria strains, is a clear example of robustness and of ability of the bacterial system to acquire a particular functional behaviour in response to environmental changes. In this work we have modeled the whole mechanism essential to the methicillin-resistance through a systems biology approach. The methicillin is a beta-lactamic antibiotic that act by inhibiting the penicillin-binding proteins (PBPs. These PBPs are involved in the synthesis of peptidoglycans, essential mesh-like polymers that surround cellular enzymes and are crucial for the bacterium survival. METHODOLOGY: The network of genes, mRNA, proteins and metabolites was created using CellDesigner program and the data of molecular interactions are stored in Systems Biology Markup Language (SBML. To simulate the dynamic behaviour of this biochemical network, the kinetic equations were associated with each reaction. CONCLUSIONS: Our model simulates the mechanism of the inactivation of the PBP by methicillin, as well as the expression of PBP2a isoform, the regulation of the SCCmec elements (SCC: staphylococcal cassette chromosome and the synthesis of peptidoglycan by PBP2a. The obtained results by our integrated approach show that the model describes correctly the whole phenomenon of the methicillin resistance and is able to respond to the external perturbations in the same way of the real cell. Therefore, this model can be useful to develop new therapeutic approaches for the methicillin control and to understand the general mechanism regarding the cellular resistance to some antibiotics.

  14. 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.

  15. JSBML 1.0: providing a smorgasbord of options to encode systems biology models.

    Science.gov (United States)

    Rodriguez, Nicolas; Thomas, Alex; Watanabe, Leandro; Vazirabad, Ibrahim Y; Kofia, Victor; Gómez, Harold F; Mittag, Florian; Matthes, Jakob; Rudolph, Jan; Wrzodek, Finja; Netz, Eugen; Diamantikos, Alexander; Eichner, Johannes; Keller, Roland; Wrzodek, Clemens; Fröhlich, Sebastian; Lewis, Nathan E; Myers, Chris J; Le Novère, Nicolas; Palsson, Bernhard Ø; Hucka, Michael; Dräger, Andreas

    2015-10-15

    JSBML, the official pure Java programming library for the Systems Biology Markup Language (SBML) format, has evolved with the advent of different modeling formalisms in systems biology and their ability to be exchanged and represented via extensions of SBML. JSBML has matured into a major, active open-source project with contributions from a growing, international team of developers who not only maintain compatibility with SBML, but also drive steady improvements to the Java interface and promote ease-of-use with end users. Source code, binaries and documentation for JSBML can be freely obtained under the terms of the LGPL 2.1 from the website http://sbml.org/Software/JSBML. More information about JSBML can be found in the user guide at http://sbml.org/Software/JSBML/docs/. jsbml-development@googlegroups.com or andraeger@eng.ucsd.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  16. Proteomics-based systems biology modeling of bovine germinal vesicle stage oocyte and cumulus cell interaction.

    Directory of Open Access Journals (Sweden)

    Divyaswetha Peddinti

    Full Text Available BACKGROUND: Oocytes are the female gametes which establish the program of life after fertilization. Interactions between oocyte and the surrounding cumulus cells at germinal vesicle (GV stage are considered essential for proper maturation or 'programming' of oocytes, which is crucial for normal fertilization and embryonic development. However, despite its importance, little is known about the molecular events and pathways involved in this bidirectional communication. METHODOLOGY/PRINCIPAL FINDINGS: We used differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT on bovine GV oocyte and cumulus cells and identified 811 and 1247 proteins in GV oocyte and cumulus cells, respectively; 371 proteins were significantly differentially expressed between each cell type. Systems biology modeling, which included Gene Ontology (GO and canonical genetic pathway analysis, showed that cumulus cells have higher expression of proteins involved in cell communication, generation of precursor metabolites and energy, as well as transport than GV oocytes. Our data also suggests a hypothesis that oocytes may depend on the presence of cumulus cells to generate specific cellular signals to coordinate their growth and maturation. CONCLUSIONS/SIGNIFICANCE: Systems biology modeling of bovine oocytes and cumulus cells in the context of GO and protein interaction networks identified the signaling pathways associated with the proteins involved in cell-to-cell signaling biological process that may have implications in oocyte competence and maturation. This first comprehensive systems biology modeling of bovine oocytes and cumulus cell proteomes not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level.

  17. Simulation, Characterization, and Optimization of Metabolic Models with the High Performance Systems Biology Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Lunacek, M.; Nag, A.; Alber, D. M.; Gruchalla, K.; Chang, C. H.; Graf, P. A.

    2011-01-01

    The High Performance Systems Biology Toolkit (HiPer SBTK) is a collection of simulation and optimization components for metabolic modeling and the means to assemble these components into large parallel processing hierarchies suiting a particular simulation and optimization need. The components come in a variety of different categories: model translation, model simulation, parameter sampling, sensitivity analysis, parameter estimation, and optimization. They can be configured at runtime into hierarchically parallel arrangements to perform nested combinations of simulation characterization tasks with excellent parallel scaling to thousands of processors. We describe the observations that led to the system, the components, and how one can arrange them. We show nearly 90% efficient scaling to over 13,000 processors, and we demonstrate three complex yet typical examples that have run on {approx}1000 processors and accomplished billions of stiff ordinary differential equation simulations. This work opens the door for the systems biology metabolic modeling community to take effective advantage of large scale high performance computing resources for the first time.

  18. Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

    Science.gov (United States)

    Pusuluri, Sai Teja

    Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

  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. BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

    Directory of Open Access Journals (Sweden)

    Thomas E Gorochowski

    Full Text Available Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

  1. Biologically inspired information theory: Adaptation through construction of external reality models by living systems.

    Science.gov (United States)

    Nakajima, Toshiyuki

    2015-12-01

    Higher animals act in the world using their external reality models to cope with the uncertain environment. Organisms that have not developed such information-processing organs may also have external reality models built in the form of their biochemical, physiological, and behavioral structures, acquired by natural selection through successful models constructed internally. Organisms subject to illusions would fail to survive in the material universe. How can organisms, or living systems in general, determine the external reality from within? This paper starts with a phenomenological model, in which the self constitutes a reality model developed through the mental processing of phenomena. Then, the it-from-bit concept is formalized using a simple mathematical model. For this formalization, my previous work on an algorithmic process is employed to constitute symbols referring to the external reality, called the inverse causality, with additional improvements to the previous work. Finally, as an extension of this model, the cognizers system model is employed to describe the self as one of many material entities in a world, each of which acts as a subject by responding to the surrounding entities. This model is used to propose a conceptual framework of information theory that can deal with both the qualitative (semantic) and quantitative aspects of the information involved in biological processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. 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

  3. A cooperative strategy for parameter estimation in large scale systems biology models.

    Science.gov (United States)

    Villaverde, Alejandro F; Egea, Jose A; Banga, Julio R

    2012-06-22

    Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and

  4. A cooperative strategy for parameter estimation in large scale systems biology models

    Directory of Open Access Journals (Sweden)

    Villaverde Alejandro F

    2012-06-01

    Full Text Available Abstract Background Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently. Results A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS, is presented. Its key feature is the cooperation between different programs (“threads” that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS. Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results. Conclusions The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here

  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. Laboratory of Biological Modeling

    Data.gov (United States)

    Federal Laboratory Consortium — The Laboratory of Biological Modeling is defined by both its methodologies and its areas of application. We use mathematical modeling in many forms and apply it to a...

  7. Genome to Phenome: A Systems Biology Approach to PTSD Using an Animal Model.

    Science.gov (United States)

    Chakraborty, Nabarun; Meyerhoff, James; Jett, Marti; Hammamieh, Rasha

    2017-01-01

    Post-traumatic stress disorder (PTSD) is a debilitating illness that imposes significant emotional and financial burdens on military families. The understanding of PTSD etiology remains elusive; nonetheless, it is clear that PTSD is manifested by a cluster of symptoms including hyperarousal, reexperiencing of traumatic events, and avoidance of trauma reminders. With these characteristics in mind, several rodent models have been developed eliciting PTSD-like features. Animal models with social dimensions are of particular interest, since the social context plays a major role in the development and manifestation of PTSD.For civilians, a core trauma that elicits PTSD might be characterized by a singular life-threatening event such as a car accident. In contrast, among war veterans, PTSD might be triggered by repeated threats and a cumulative psychological burden that coalesced in the combat zone. In capturing this fundamental difference, the aggressor-exposed social stress (Agg-E SS) model imposes highly threatening conspecific trauma on naïve mice repeatedly and randomly.There is abundant evidence that suggests the potential role of genetic contributions to risk factors for PTSD. Specific observations include putatively heritable attributes of the disorder, the cited cases of atypical brain morphology, and the observed neuroendocrine shifts away from normative. Taken together, these features underscore the importance of multi-omics investigations to develop a comprehensive picture. More daunting will be the task of downstream analysis with integration of these heterogeneous genotypic and phenotypic data types to deliver putative clinical biomarkers. Researchers are advocating for a systems biology approach, which has demonstrated an increasingly robust potential for integrating multidisciplinary data. By applying a systems biology approach here, we have connected the tissue-specific molecular perturbations to the behaviors displayed by mice subjected to Agg-E SS. A

  8. Experiment design through dynamical characterisation of non-linear systems biology models utilising sparse grids.

    Science.gov (United States)

    Donahue, M M; Buzzard, G T; Rundell, A E

    2010-07-01

    The sparse grid-based experiment design algorithm sequentially selects an experimental design point to discriminate between hypotheses for given experimental conditions. Sparse grids efficiently screen the global uncertain parameter space to identify acceptable parameter subspaces. Clustering the located acceptable parameter vectors by the similarity of the simulated model trajectories characterises the data-compatible model dynamics. The experiment design algorithm capitalizes on the diversity of the experimentally distinguishable system output dynamics to select the design point that best discerns between competing model-structure and parameter-encoded hypotheses. As opposed to designing the experiments to explicitly reduce uncertainty in the model parameters, this approach selects design points to differentiate between dynamical behaviours. This approach further differs from other experimental design methods in that it simultaneously addresses both parameter- and structural-based uncertainty that is applicable to some ill-posed problems where the number of uncertain parameters exceeds the amount of data, places very few requirements on the model type, available data and a priori parameter estimates, and is performed over the global uncertain parameter space. The experiment design algorithm is demonstrated on a mitogen-activated protein kinase cascade model. The results show that system dynamics are highly uncertain with limited experimental data. Nevertheless, the algorithm requires only three additional experimental data points to simultaneously discriminate between possible model structures and acceptable parameter values. This sparse grid-based experiment design process provides a systematic and computationally efficient exploration over the entire uncertain parameter space of potential model structures to resolve the uncertainty in the non-linear systems biology model dynamics.

  9. Biological channel modeling and implantable UWB antenna design for neural recording systems.

    Science.gov (United States)

    Bahrami, Hadi; Mirbozorgi, S Abdollah; Rusch, Leslie A; Gosselin, Benoit

    2015-01-01

    Ultrawideband (UWB) short-range communication systems have proved to be valuable in medical technology, particularly for implanted devices, due to their low-power consumption, low cost, small size, and high data rates. Neural activity monitoring in the brain requires high data rate (800 kb/s per neural sensor), and we target a system supporting a large number of sensors, in particular, aggregate transmission above 430 Mb/s (∼512 sensors). Knowledge of channel behavior is required to determine the maximum allowable power to 1) respect ANSI guidelines for avoiding tissue damage, and 2) respect FCC guidelines on unlicensed transmissions. We utilize a realistic model of the biological channel to inform the design of antennas for the implanted transmitter and the external receiver under these requirements. Antennas placement is examined under two scenarios having contrasting power constraints. Performance of the system within the biological tissues is examined via simulation and experiment. Our miniaturized antennas, 12 mm ×12 mm, need worst-case receiver sensitivities of -38 and -30.5 dBm for the first and second scenarios, respectively. These sensitivities allow us to successfully detect signals transmitted through tissues in the 3.1-10.6-GHz UWB band.

  10. Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets

    Directory of Open Access Journals (Sweden)

    Raed I. Hamed

    2018-01-01

    Full Text Available Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks.

  11. Integration of multiscale dendritic spine structure and function data into systems biology models

    Directory of Open Access Journals (Sweden)

    James J Mancuso

    2014-11-01

    Full Text Available Comprising 1011 neurons with 1014 synaptic connections the human brain is the ultimate systems biology puzzle. An increasing body of evidence highlights the observation that changes in brain function, both normal and pathological, consistently correlate with dynamic changes in neuronal anatomy. Anatomical changes occur on a full range of scales from the trafficking of individual proteins, to alterations in synaptic morphology both individually and on a systems level, to reductions in long distance connectivity and brain volume. The major sites of contact for synapsing neurons are dendritic spines, which provide an excellent metric for the number and strength of signaling connections between elements of functional neuronal circuits. A comprehensive model of anatomical changes and their functional consequences would be a holy grail for the field of systems neuroscience but its realization appears far on the horizon. Various imaging technologies have advanced to allow for multi-scale visualization of brain plasticity and pathology, but computational analysis of the massive big data sets involved forms the bottleneck toward the creation of multiscale models of brain structure and function. While a full accounting of techniques and progress toward a comprehensive model of brain anatomy and function is beyond the scope of this or any other single paper, this review serves to highlight the opportunities for analysis of neuronal spine anatomy and function provided by new imaging technologies and the high-throughput application of older technologies while surveying the strengths and weaknesses of currently available computational analytical tools and room for future improvement.

  12. Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology

    Science.gov (United States)

    Bowker, Matthew A.; Maestre, Fernando T.; Eldridge, David; Belnap, Jayne; Castillo-Monroy, Andrea; Escolar, Cristina; Soliveres, Santiago

    2014-01-01

    Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.

  13. Use of genome-scale metabolic models in evolutionary systems biology.

    NARCIS (Netherlands)

    Papp, B.; Szappanos, B.; Notebaart, R.A.

    2011-01-01

    One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for

  14. A Unique Model Platform for C4 Plant Systems and Synthetic Biology

    Science.gov (United States)

    2015-12-10

    mediated transformation of Setaria viridis. Agrobacterium tumefaciens strain GV3101 was transformed by electroporation with pBI 121. Agrobacterium ... agrobacterium mediated transformation 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF...successful agrobacterium mediated transformation 15. SUBJECT TERMS synthetic biology, Systems Biology 16. SECURITY CLASSIFICATION OF

  15. 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),...

  16. Teaching systems biology.

    Science.gov (United States)

    Alves, R; Vilaprinyo, E; Sorribas, A

    2011-03-01

    Advances in systems biology are increasingly dependent upon the integration of various types of data and different methodologies to reconstruct how cells work at the systemic level. Thus, teams with a varied array of expertise and people with interdisciplinary training are needed. So far this training was thought to be more productive if aimed at the Masters or PhD level. At this level, multiple specialised and in-depth courses on the different subject matters of systems biology are taught to already well-prepared students. This approach is mostly based on the recognition that systems biology requires a wide background that is hard to find in undergraduate students. Nevertheless, and given the importance of the field, the authors argue that exposition of undergraduate students to the methods and paradigms of systems biology would be advantageous. Here they present and discuss a successful experiment in teaching systems biology to third year undergraduate biotechnology students at the University of Lleida in Spain. The authors' experience, together with that from others, argues for the adequateness of teaching systems biology at the undergraduate level. [Includes supplementary material].

  17. Genome-scale modeling of human metabolism - a systems biology approach.

    Science.gov (United States)

    Mardinoglu, Adil; Gatto, Francesco; Nielsen, Jens

    2013-09-01

    Altered metabolism is linked to the appearance of various human diseases and a better understanding of disease-associated metabolic changes may lead to the identification of novel prognostic biomarkers and the development of new therapies. Genome-scale metabolic models (GEMs) have been employed for studying human metabolism in a systematic manner, as well as for understanding complex human diseases. In the past decade, such metabolic models - one of the fundamental aspects of systems biology - have started contributing to the understanding of the mechanistic relationship between genotype and phenotype. In this review, we focus on the construction of the Human Metabolic Reaction database, the generation of healthy cell type- and cancer-specific GEMs using different procedures, and the potential applications of these developments in the study of human metabolism and in the identification of metabolic changes associated with various disorders. We further examine how in silico genome-scale reconstructions can be employed to simulate metabolic flux distributions and how high-throughput omics data can be analyzed in a context-dependent fashion. Insights yielded from this mechanistic modeling approach can be used for identifying new therapeutic agents and drug targets as well as for the discovery of novel biomarkers. Finally, recent advancements in genome-scale modeling and the future challenge of developing a model of whole-body metabolism are presented. The emergent contribution of GEMs to personalized and translational medicine is also discussed. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. The application of Biological-Hydraulic coupled model for Tubificidae-microorganism interaction system

    Science.gov (United States)

    Zhong, Xiao; Sun, Peide; Song, Yingqi; Wang, Ruyi; Fang, Zhiguo

    2010-11-01

    Based on the fully coupled activated sludge model (FCASM), the novel model Tubificidae -Fully Coupled Activated Sludge Model-hydraulic (T-FCASM-Hydro), has been developed in our previous work. T-FCASM-Hydro not only describe the interactive system between Tubificidae and functional microorganisms for the sludge reduction and nutrient removal simultaneously, but also considere the interaction between biological and hydraulic field, After calibration and validation of T-FCASM-Hydro at Zhuji Feida-hongyu Wastewater treatment plant (WWTP) in Zhejiang province, T-FCASM-Hydro was applied for determining optimal operating condition in the WWTP. Simulation results showed that nitrogen and phosphorus could be removed efficiently, and the efficiency of NH4+-N removal enhanced with increase of DO concentration. At a certain low level of DO concentration in the aerobic stage, shortcut nitrification-denitrification dominated in the process of denitrification in the novel system. However, overhigh agitation (>6 mgṡL-1) could result in the unfavorable feeding behavior of Tubificidae because of the strong flow disturbance, which might lead to low rate of sludge reduction. High sludge reduction rate and high removal rate of nitrogen and phosphorus could be obtained in the new-style oxidation ditch when DO concentration at the aerobic stage with Tubificidae was maintained at 3.6 gṡm-3.

  19. 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

  20. 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)

  1. What controls biological production in coastal upwelling systems? Insights from a comparative modeling study

    Directory of Open Access Journals (Sweden)

    Z. Lachkar

    2011-10-01

    Full Text Available The magnitude of net primary production (NPP in Eastern Boundary Upwelling Systems (EBUS is traditionally viewed as directly reflecting the wind-driven upwelling intensity. Yet, different EBUS show different sensitivities of NPP to upwelling-favorable winds (Carr and Kearns, 2003. Here, using a comparative modeling study of the California Current System (California CS and Canary Current System (Canary CS, we show how physical and environmental factors, such as light, temperature and cross-shore circulation modulate the response of NPP to upwelling strength. To this end, we made a series of eddy-resolving simulations of the two upwelling systems using the Regional Oceanic Modeling System (ROMS, coupled to a nitrogen-based Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD ecosystem model. Using identical ecological/biogeochemical parameters, our coupled model simulates a level of NPP in the California CS that is 50 % smaller than that in the Canary CS, in agreement with observationally based estimates. We find this much lower NPP in the California CS despite phytoplankton in this system having nearly 20 % higher nutrient concentrations available to fuel their growth. This conundrum can be explained by: (1 phytoplankton having a faster nutrient-replete growth in the Canary CS relative to the California CS; a consequence of more favorable light and temperature conditions in the Canary CS, and (2 the longer nearshore water residence times in the Canary CS, which permit a larger buildup of biomass in the upwelling zone, thereby enhancing NPP. The longer residence times in the Canary CS appear to be a result of the wider continental shelves and the lower mesoscale activity characterizing this upwelling system. This results in a weaker offshore export of nutrients and organic matter, thereby increasing local nutrient recycling and reducing the spatial decoupling between new and export production in the Canary CS. Our results suggest that climate change

  2. A framework for modeling information propagation of biological systems at critical states.

    Science.gov (United States)

    Hu, Feng; Yang, Fang

    2016-03-01

    We explore the dynamics of information propagation at the critical state of a biologically inspired system by an individual-based computer model. "Quorum response", a type of social interaction which has been recognized taxonomically in animal groups, is applied as the sole interaction rule among individuals. In the model, we assume a truncated Gaussian distribution to depict the distribution of the individuals' vigilance level. Each individual can assume either a naïve state or an alarmed one and only switches from the former state to the latter one. If an individual has turned into an alarmed state, it stays in the state during the process of information propagation. Initially, each individual is set to be at the naïve state and information is tapped into the system by perturbing an individual at the boundaries (alerting it to the alarmed state). The system evolves as individuals turn into the alarmed state, according to the quorum response rules, consecutively. We find that by fine-tuning the parameters of the mean and the standard deviation of the Gaussian distribution, the system is poised at a critical state. We present the phase diagrams to exhibit that the parameter space is divided into a super-critical and a sub-critical zone, in which the dynamics of information propagation varies largely. We then investigate the effects of the individuals' mobility on the critical state, and allow a proportion of randomly chosen individuals to exchange their positions at each time step. We find that mobility breaks down criticality of the system. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. 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

  4. 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...

  5. Evolutionary transition from biological to social systems via generation of reflexive models of externality.

    Science.gov (United States)

    Igamberdiev, Abir U

    2017-12-01

    Evolutionary transition from biological to social systems corresponds to the emergence of the structure of subject that incorporates the internal image of the external world. This structure, established on the basis of referral of the subject (self) to its symbolic image, acquires a potential to rationally describe the external world through the semiotic structure of human language. It has been modelled in reflexive psychology using the algebra of simple relations (Lefebvre, V.A., J. Soc. Biol. Struct. 10, 129-175, 1987). The model introduces a substantial opposition of the two basic complementary types of reflexion defined as Western (W) and Eastern (E). These types generate opposite models of behavior and opposite organizations of societies. Development of human societies involves the interactions of W and E types not only between the societies but also within one society underlying its homeostasis and dynamics. Invention of new ideas and implementation of new technologies shift the probability pattern of reflexive choices, appearing as internal assessments of the individual agents within a society, and direct changes in the preference of reflexive types. The dynamics of societies and of interactions between societies is based on the interference of opposite reflexive structures and on the establishment of different patterns during such interference. At different times in the history of human civilization these changing patterns resulted in the formation and splitting of large empires, the development and spreading of new technologies, the consecutive periods of wellness and decline. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Text mining for systems biology.

    Science.gov (United States)

    Fluck, Juliane; Hofmann-Apitius, Martin

    2014-02-01

    Scientific communication in biomedicine is, by and large, still text based. Text mining technologies for the automated extraction of useful biomedical information from unstructured text that can be directly used for systems biology modelling have been substantially improved over the past few years. In this review, we underline the importance of named entity recognition and relationship extraction as fundamental approaches that are relevant to systems biology. Furthermore, we emphasize the role of publicly organized scientific benchmarking challenges that reflect the current status of text-mining technology and are important in moving the entire field forward. Given further interdisciplinary development of systems biology-orientated ontologies and training corpora, we expect a steadily increasing impact of text-mining technology on systems biology in the future. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems.

    Science.gov (United States)

    Cilfone, Nicholas A; Kirschner, Denise E; Linderman, Jennifer J

    2015-03-01

    Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level.

  8. Multiple Representations in Modeling Strategies for the Development of Systems Thinking in Biology Education

    NARCIS (Netherlands)

    Verhoeff, R.P.|info:eu-repo/dai/nl/165575581; Boersma, K.T.|info:eu-repo/dai/nl/073043141; Waarlo, A.J.|info:eu-repo/dai/nl/074372246

    2013-01-01

    For biological researchers, systems thinking is a basic conceptual framework, and many educationalists consider systems thinking as a metacognitive skill that enables students to understand and cope with the new scientific advancements that reach our society. With this in mind, we investigated the

  9. 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.

  10. 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.

  11. Biological neural networks as model systems for designing future parallel processing computers

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

  12. Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

    Science.gov (United States)

    Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

    2017-09-01

    In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to

  13. A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

    Directory of Open Access Journals (Sweden)

    Thomas eEissing

    2011-02-01

    Full Text Available Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.

  14. Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

    Science.gov (United States)

    Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

    2014-12-06

    Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  15. Mathematical modeling of the circadian rhythm of key neuroendocrine-immune system players in rheumatoid arthritis: a systems biology approach.

    Science.gov (United States)

    Meyer-Hermann, Michael; Figge, Marc Thilo; Straub, Rainer H

    2009-09-01

    Healthy subjects and patients with rheumatoid arthritis (RA) exhibit circadian rhythms of the neuroendocrine-immune system. Understanding circadian dynamics is complex due to the nonlinear behavior of the neuroendocrine-immune network. This study was undertaken to seek and test a mathematical model for studying this network. We established a quantitative computational model to simulate nonlinear interactions between key factors in the neuroendocrine-immune system, such as plasma tumor necrosis factor (TNF), plasma cortisol (and adrenal cholesterol store), and plasma noradrenaline (NA) (and presynaptic NA store). The model was nicely fitted with measured reference data on healthy subjects and RA patients. Although the individual circadian pacemakers of cortisol, NA, and TNF were installed without a phase shift, the relative phase shift between these factors evolved as a consequence of the modeled network interactions. Combined long-term and short-term TNF increase (the "RA model") increased cortisol plasma levels for only a few days, and cholesterol stores started to become markedly depleted. This nicely demonstrated the phenomenon of inadequate cortisol secretion relative to plasma TNF levels, as a consequence of adrenal deficiency. Using the RA model, treatment with glucocorticoids between midnight and 2:00 AM was found to have the strongest inhibitory effect on TNF secretion, which supports recent studies on RA therapy. Long-term reduction of TNF levels by simulation of anti-TNF therapy normalized cholesterol stores under "RA" conditions. These first in silico studies of the neuroendocrine-immune system in rheumatology demonstrate that computational biology in medicine, making use of large collections of experimental data, supports understanding of the pathophysiology of complex nonlinear systems.

  16. 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 ‘‘...

  17. 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

  18. [Method of Entirely Parallel Differential Evolution for Model Adaptation in Systems Biology].

    Science.gov (United States)

    Kozlov, K N; Samsonov, A M; Samsonova, M G

    2015-01-01

    We developed a method of entirely parallel differential evolution for identification of unknown parameters of mathematical models by minimization of the objective function that describes the discrepancy of the model solution and the experimental data. The method is implemented in the free and open source software available on the Internet. The method demonstrated a good performance comparable to the top three methods from CEC-2014 and was successfully applied to several biological problems.

  19. Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

    Science.gov (United States)

    Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

    2017-03-01

    Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  20. The quest for a new modelling framework in mathematical biology. Comment on "On the interplay between mathematics and biology: Hallmarks towards a new systems biology" by N. Bellomo et al.

    Science.gov (United States)

    Eftimie, Raluca

    2015-03-01

    One of the main unsolved problems of modern physics is finding a "theory of everything" - a theory that can explain, with the help of mathematics, all physical aspects of the universe. While the laws of physics could explain some aspects of the biology of living systems (e.g., the phenomenological interpretation of movement of cells and animals), there are other aspects specific to biology that cannot be captured by physics models. For example, it is generally accepted that the evolution of a cell-based system is influenced by the activation state of cells (e.g., only activated and functional immune cells can fight diseases); on the other hand, the evolution of an animal-based system can be influenced by the psychological state (e.g., distress) of animals. Therefore, the last 10-20 years have seen also a quest for a "theory of everything"-approach extended to biology, with researchers trying to propose mathematical modelling frameworks that can explain various biological phenomena ranging from ecology to developmental biology and medicine [1,2,6]. The basic idea behind this approach can be found in a few reviews on ecology and cell biology [6,7,9-11], where researchers suggested that due to the parallel between the micro-scale dynamics and the emerging macro-scale phenomena in both cell biology and in ecology, many mathematical methods used for ecological processes could be adapted to cancer modelling [7,9] or to modelling in immunology [11]. However, this approach generally involved the use of different models to describe different biological aspects (e.g., models for cell and animal movement, models for competition between cells or animals, etc.).

  1. KiMoSys: a web-based repository of experimental data for KInetic MOdels of biological SYStems.

    Science.gov (United States)

    Costa, Rafael S; Veríssimo, André; Vinga, Susana

    2014-08-13

    The kinetic modeling of biological systems is mainly composed of three steps that proceed iteratively: model building, simulation and analysis. In the first step, it is usually required to set initial metabolite concentrations, and to assign kinetic rate laws, along with estimating parameter values using kinetic data through optimization when these are not known. Although the rapid development of high-throughput methods has generated much omics data, experimentalists present only a summary of obtained results for publication, the experimental data files are not usually submitted to any public repository, or simply not available at all. In order to automatize as much as possible the steps of building kinetic models, there is a growing requirement in the systems biology community for easily exchanging data in combination with models, which represents the main motivation of KiMoSys development. KiMoSys is a user-friendly platform that includes a public data repository of published experimental data, containing concentration data of metabolites and enzymes and flux data. It was designed to ensure data management, storage and sharing for a wider systems biology community. This community repository offers a web-based interface and upload facility to turn available data into publicly accessible, centralized and structured-format data files. Moreover, it compiles and integrates available kinetic models associated with the data.KiMoSys also integrates some tools to facilitate the kinetic model construction process of large-scale metabolic networks, especially when the systems biologists perform computational research. KiMoSys is a web-based system that integrates a public data and associated model(s) repository with computational tools, providing the systems biology community with a novel application facilitating data storage and sharing, thus supporting construction of ODE-based kinetic models and collaborative research projects.The web application implemented using Ruby

  2. 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."

  3. Zebrafish as a visual and dynamic model to study the transport of nanosized drug delivery systems across the biological barriers.

    Science.gov (United States)

    Li, Ye; Miao, Xiaoqing; Chen, Tongkai; Yi, Xiang; Wang, Ruibing; Zhao, Haitao; Lee, Simon Ming-Yuen; Wang, Xueqing; Zheng, Ying

    2017-08-01

    With the wide application of nanotechnology to drug delivery systems, a simple, dynamic and visual in vivo model for high-throughput screening of novel formulations with fluorescence markers across biological barriers is desperately needed. In vitro cell culture models have been widely used, although they are far from a complimentary in vivo system. Mammalian animal models are common predictive models to study transport, but they are costly and time consuming. Zebrafish (Danio rerio), a small vertebrate model, have the potential to be developed as an "intermediate" model for quick evaluations. Based on our previously established coumarin 6 nanocrystals (C6-NCs), which have two different sizes, the present study investigates the transportation of C6-NCs across four biological barriers, including the chorion, blood brain barrier (BBB), blood retinal barrier (BRB) and gastrointestinal (GI) barrier, using zebrafish embryos and larvae as in vivo models. The biodistribution and elimination of C6 from different organs were quantified in adult zebrafish. The results showed that compared to 200nm C6-NCs, 70nm C6-NCs showed better permeability across these biological barriers. A FRET study suggested that intact C6-NCs together with the free dissolved form of C6 were absorbed into the larval zebrafish. More C6 was accumulated in different organs after incubation with small sized NCs via lipid raft-mediated endocytosis in adult zebrafish, which is consistent with the findings from in vitro cell monolayers and the zebrafish larvae model. C6-NCs could be gradually eliminated in each organ over time. This study demonstrated the successful application of zebrafish as a simple and dynamic model to simultaneously assess the transport of nanosized drug delivery systems across several biological barriers and biodistribution in different organs, especially in the brain, which could be used for central nervous system (CNS) drug and delivery system screening. Copyright © 2017 Elsevier B

  4. Prediction uncertainty assessment of a systems biology model requires a sample of the full probability distribution of its parameters

    NARCIS (Netherlands)

    Mourik, van S.; Braak, ter C.J.F.; Stigter, J.D.; Molenaar, J.

    2014-01-01

    Multi-parameter models in systems biology are typically ‘sloppy’: some parameters or combinations of parameters may be hard to estimate from data, whereas others are not. One might expect that parameter uncertainty automatically leads to uncertain predictions, but this is not the case. We illustrate

  5. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

    Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

    2006-01-01

    Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations......, as model systems to understand the fundamental properties of biomembranes. The properties of lipid bilayers can be studied at different time and length scales. For some properties it is sufficient to envision a membrane as an elastic sheet, while for others it is important to take into account the details...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

  6. 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’.

  7. The planarian flatworm: an in vivo model for stem cell biology and nervous system regeneration

    Directory of Open Access Journals (Sweden)

    Luca Gentile

    2011-01-01

    Full Text Available Planarian flatworms are an exception among bilaterians in that they possess a large pool of adult stem cells that enables them to promptly regenerate any part of their body, including the brain. Although known for two centuries for their remarkable regenerative capabilities, planarians have only recently emerged as an attractive model for studying regeneration and stem cell biology. This revival is due in part to the availability of a sequenced genome and the development of new technologies, such as RNA interference and next-generation sequencing, which facilitate studies of planarian regeneration at the molecular level. Here, we highlight why planarians are an exciting tool in the study of regeneration and its underlying stem cell biology in vivo, and discuss the potential promises and current limitations of this model organism for stem cell research and regenerative medicine.

  8. CHOmine: an integrated data warehouse for CHO systems biology and modeling.

    Science.gov (United States)

    Gerstl, Matthias P; Hanscho, Michael; Ruckerbauer, David E; Zanghellini, Jürgen; Borth, Nicole

    2017-01-01

    The last decade has seen a surge in published genome-scale information for Chinese hamster ovary (CHO) cells, which are the main production vehicles for therapeutic proteins. While a single access point is available at www.CHOgenome.org, the primary data is distributed over several databases at different institutions. Currently research is frequently hampered by a plethora of gene names and IDs that vary between published draft genomes and databases making systems biology analyses cumbersome and elaborate. Here we present CHOmine, an integrative data warehouse connecting data from various databases and links to other ones. Furthermore, we introduce CHOmodel, a web based resource that provides access to recently published CHO cell line specific metabolic reconstructions. Both resources allow to query CHO relevant data, find interconnections between different types of data and thus provides a simple, standardized entry point to the world of CHO systems biology. http://www.chogenome.org. © The Author(s) 2017. Published by Oxford University Press.

  9. 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).

  10. 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.

  11. Systems biology in animal sciences

    NARCIS (Netherlands)

    Woelders, H.; Pas, te M.F.W.; Bannink, A.; Veerkamp, R.F.; Smits, M.A.

    2011-01-01

    Systems biology is a rapidly expanding field of research and is applied in a number of biological disciplines. In animal sciences, omics approaches are increasingly used, yielding vast amounts of data, but systems biology approaches to extract understanding from these data of biological processes

  12. Telomere Lengths and Telomerase Activity in Dog Tissues: A Potential Model System to Study Human Telomere and Telomerase Biology

    Directory of Open Access Journals (Sweden)

    Lubna Nasir

    2001-01-01

    Full Text Available Studies on telomere and telomerase biology are fundamental to the understanding of aging and age-related diseases such as cancer. However, human studies have been hindered by differences in telomere biology between humans and the classical murine animal model system. In this paper, we describe basic studies of telomere length and telomerase activity in canine normal and neoplastic tissues and propose the dog as an alternative model system. Briefly, telomere lengths were measured in normal canine peripheral blood mononuclear cells (PBMCs, a range of normal canine tissues, and in a panel of naturally occurring soft tissue tumours by terminal restriction fragment (TRF analysis. Further, telomerase activity was measured in canine cell lines and multiple canine tissues using a combined polymerase chain reaction/enzyme-linked immunosorbent assay method. TRF analysis in canine PBMCs and tissues demonstrated mean TRF lengths to range between 12 and 23 kbp with heterogeneity in telomere lengths being observed in a range of normal somatic tissues. In soft tissue sarcomas, two subgroups were identified with mean TRFs of 22.2 and 18.2 kbp. Telomerase activity in canine tissue was present in tumour tissue and testis with little or no activity in normal somatic tissues. These results suggest that the dog telomere biology is similar to that in humans and may represent an alternative model system for studying telomere biology and telomerase-targeted anticancer therapies.

  13. [Circadian rhythms and systems biology].

    Science.gov (United States)

    Goldbeter, Albert; Gérard, Claude; Leloup, Jean-Christophe

    2010-01-01

    Cellular rhythms represent a field of choice for studies in system biology. The examples of circadian rhythms and of the cell cycle show how the experimental and modeling approaches contribute to clarify the conditions in which periodic behavior spontaneously arises in regulatory networks at the cellular level. Circadian rhythms originate from intertwined positive and negative feedback loops controlling the expression of several clock genes. Models can be used to address the dynamical bases of physiological disorders related to dysfunctions of the mammalian circadian clock. The cell cycle is driven by a network of cyclin-dependent kinases (Cdks). Modeled in the form of four modules coupled through multiple regulatory interactions, the Cdk network operates in an oscillatory manner in the presence of sufficient amounts of growth factor. For circadian rhythms and the cell cycle, as for other recently observed cellular rhythms, periodic behavior represents an emergent property of biological systems related to their regulatory structure.

  14. Systems biology of cellular rhythms.

    Science.gov (United States)

    Goldbeter, A; Gérard, C; Gonze, D; Leloup, J-C; Dupont, G

    2012-08-31

    Rhythms abound in biological systems, particularly at the cellular level where they originate from the feedback loops present in regulatory networks. Cellular rhythms can be investigated both by experimental and modeling approaches, and thus represent a prototypic field of research for systems biology. They have also become a major topic in synthetic biology. We review advances in the study of cellular rhythms of biochemical rather than electrical origin by considering a variety of oscillatory processes such as Ca++ oscillations, circadian rhythms, the segmentation clock, oscillations in p53 and NF-κB, synthetic oscillators, and the oscillatory dynamics of cyclin-dependent kinases driving the cell cycle. Finally we discuss the coupling between cellular rhythms and their robustness with respect to molecular noise.

  15. Realistic modeling of the biological channel for the design of implantable wireless UWB communication systems.

    Science.gov (United States)

    Bahrami, Hadi; Gosselin, Benoit; Rusch, Leslie A

    2012-01-01

    Several emerging medical applications require that a miniature data acquisition device be implanted into the head to extract and wirelessly communicate brain activity to other devices. Designing a reliable communication link for such an application requires a realistic model of the surrounding biological tissues. This paper exploits a realistic model of the biological channel to design a suitable wireless ultra wideband communication link in a brain monitoring application. Two scenarios for positioning the implanted transmitting antenna are considered. The 1(st) scenario places the antenna under the skull, whereas the 2(nd) scenario places the antenna under the skin, above the skull. The propagation characteristics of the signal through the tissues of the human head have been determined with full-wave electromagnetic simulation based on Finite Element Method. The implantable antenna and the external antenna are key components to establish an electromagnetic link between an implanted transmitter and an external receiver. The average specific absorption rate (ASAR) of the implantable antennas are evaluated and compared for the two proposed scenarios. Moreover, the maximum available power from the implanted antenna is evaluated to characterize the performance of the communication link established between the implantable antenna and the external antenna, with respect to spectrum and safety regulations. We show how sensitive the receiver must be in order to implement a reliable telemetry link based on the proposed model of the channel.

  16. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

    Science.gov (United States)

    Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

    2015-01-01

    A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

  17. Understanding XPO1 target networks using systems biology and mathematical modeling.

    Science.gov (United States)

    Muqbil, Irfana; Kauffman, Michael; Shacham, Sharon; Mohammad, Ramzi M; Azmi, Asfar S

    2014-01-01

    The nuclear transport protein Exportin 1 (XPO1), also called chromosome region maintenance 1 (CRM1), is over-expressed 2- 4 fold in cancer. XPO1 is one of seven nuclear exporter proteins, and is solely responsible for the transport of the major tumor suppressor proteins (TSPs) from the nucleus to the cytoplasm. XPO1 exports any protein that carries a leucine-rich, hydrophobic nuclear export sequence (NES). A number of inhibitors have been discovered that block XPO1 function and thereby restore TSPs to the nucleus of both malignant and normal cells. However, natural product, irreversible XPO1 antagonists such as leptomycin B (LMB) have proven toxic in both preclinical models and in the clinic. Recently, orally bioavailable, drug-like small molecule, potent and selective inhibitors of XPO1 mediated nuclear export ("SINE") have been designed and are undergoing clinical evaluations in both humans and canines with cancer. The breadth of clinical applicability and long-term viability of an XPO1 inhibition strategy requires a deeper evaluation of the consequence of global re-organization of proteins in cancer and normal cells. Unfortunately, most of the studies on XPO1 inhibitors have focused on evaluating a limited number of TSPs or other proteins. Because XPO1 carries ~220 mammalian proteins out of the nucleus, such reductionism has not permitted a global understanding of cellular behavior upon drug-induced disruption of XPO1 function. The consequence of XPO1 inhibition requires holistic investigations that consider the entire set of XPO1 targets and their respective pathways modulated without losing key details. Systems biology is one such holistic approach that can be applied to understand XPO1 regulated proteins along with the downstream players involved. This review provides comprehensive evaluations of the different computational tools that can be utilized in the better understanding of XPO1 and its target. We anticipate that such holistic approaches can allow for

  18. 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....

  19. 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.

  20. Mathematical Modeling of Hollow-Fiber Membrane System in Biological Wastewater Treatment

    Directory of Open Access Journals (Sweden)

    Jian PENG

    2006-02-01

    Full Text Available A set of mathematical models were derived based on the bio-kinetics and material balance principles to describe the performance of membrane system in this research. A synthetic wastewater and a meat packing wastewater were processed through a lab-scale membrane bioreactor system to generate experimental data for calibration and verification of the derived models. For the synthetic wastewater treatment, a high and stable Total Organic Carbon (TOC removal was achieved with volumetric organic loading from 0.2 to 24.2 kg TOC/m3ƒ(d. It was found that the derived system models fit the experimental data well. The bio-kinetic coefficients of k, Ks, Y and kd in the models were found to be 0.16 d-1, 1.0 mg/L, 1.75 mg Mixed Liquor Volatile Suspended Solids (MLVSS/mg TOC and 0.11 d-1, respectively. For the meat packing wastewater treatment, the bio-kinetic coefficients of k, Ks, Y and kd were found to be 0.48 d-1, 56.3 mg/L, 0.53 mg MLVSS/mg COD and 0.04 d-1, respectively. F/M ratio of 0.08 was found to be the proper operating condition for the system. Based on the proposed system models, the optimum MLSS concentration and F/M ratio can be computed to yield minimum cost of a membrane bioreactor system without excess biomass production.

  1. 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.

  2. A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2009-09-01

    Full Text Available Abstract Background Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention. Results We developed a mathematical framework to simulate the effects on the growth of a pathogen when enzymes in its metabolic pathways are inhibited. Combining detailed models of enzyme kinetics, a complete metabolic network description as modeled by flux balance analysis, and a dynamic cell population growth model, we quantitatively modeled and predicted the dose-response of the 3-nitropropionate inhibitor on the growth of M. tuberculosis in a medium whose carbon source was restricted to fatty acids, and that of the 5'-O-(N-salicylsulfamoyl adenosine inhibitor in a medium with low-iron concentration. Conclusion The predicted results quantitatively reproduced the experimentally measured dose-response curves, ranging over three orders of magnitude in inhibitor concentration. Thus, by allowing for detailed specifications of the underlying enzymatic kinetics, metabolic reactions/constraints, and growth media, our model captured the essential chemical and biological factors that determine the effects of drug inhibition on in vitro growth of M. tuberculosis cells.

  3. Mass exchange in an experimental new-generation life support system model based on biological regeneration of environment

    Science.gov (United States)

    Tikhomirov, A. A.; Ushakova, S. A.; Manukovsky, N. S.; Lisovsky, G. M.; Kudenko, Yu. A.; Kovalev, V. S.; Gubanov, V. G.; Barkhatov, Yu. V.; Gribovskaya, I. V.; Zolotukhin, I. G.; Gros, J. B.; Lasseur, Ch.

    An experimental model of a biological life support system was used to evaluate qualitative and quantitative parameters of the internal mass exchange. The photosynthesizing unit included the higher plant component (wheat and radish), and the heterotrophic unit consisted of a soil-like substrate, California warms, mushrooms and microbial microflora. The gas mass exchange involved evolution of oxygen by the photosynthesizing component and its uptake by the heterotroph component along with the formation and maintaining of the SLS structure, growth of mushrooms and California worms, human respiration, and some other processes. Human presence in the system in the form of "virtual human" that at regular intervals took part in the respirative gas exchange during the experiment. Experimental data demonstrated good oxygen/carbon dioxide balance, and the closure of the cycles of these gases was almost complete. The water cycle was nearly 100% closed. The main components in the water mass exchange were transpiration water and the watering solution with mineral elements. Human consumption of the edible plant biomass (grains and roots) was simulated by processing these products by a unique physicochemical method of oxidizing them to inorganic mineral compounds, which were then returned into the system and fully assimilated by the plants. The oxidation was achieved by "wet combustion" of organic biomass, using hydrogen peroxide following a special procedure, which does not require high temperature and pressure. Hydrogen peroxide is produced from the water inside the system. The closure of the cycle was estimated for individual elements and compounds. Stoichiometric proportions are given for the main components included in the experimental model of the system. Approaches to the mathematical modeling of the cycling processes are discussed, using the data of the experimental model. Nitrogen, as a representative of biogmic elements, shows an almost 100% closure of the cycle inside

  4. Multiple-quantum nuclear magnetic resonance studies of sodium-23 in model and biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Pekar, J.J.

    1988-01-01

    Time-domain multiple-quantum nuclear magnetic resonance spectroscopy is applied to sodium-23 in gels, liquid crystals, cell suspensions, and intact human limbs. In many biological systems, interactions between the nuclear electric quadrupole moment and fluctuating electric field gradients cause the outer transitions, which contribute 60% of the nuclear magnetic resonance signal from the spin-3/2 nuclei, to relax faster than the central transition, which contributes the remains in 40% of the signal. New multiple-quantum experiments, designed specifically for quadrupolar spin-3/2 nuclei, reveal much information not usually available from conventional nuclear magnetic resonance spectroscopy, because they allow indirect measurement of the rapid relaxation rate of the outer transitions, and may highlight the distribution of sodium ions among microscopic physiological compartments such as intracellular space, the interstitium, and the vasculature. The use of venous occlusion plethysmography to alter this distribution is discussed.

  5. 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.

  6. Systems biology of Microbial Communities

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Ghim, C; Fenley, A; Yoon, S; Lee, S; Almaas, E

    2008-04-11

    Microbes exist naturally in a wide range of environments, spanning the extremes of high acidity and high temperature to soil and the ocean, in communities where their interactions are significant. We present a practical discussion of three different approaches for modeling microbial communities: rate equations, individual-based modeling, and population dynamics. We illustrate the approaches with detailed examples. Each approach is best fit to different levels of system representation, and they have different needs for detailed biological input. Thus, this set of approaches is able to address the operation and function of microbial communities on a wide range of organizational levels.

  7. Meta-stochastic simulation of biochemical models for systems and synthetic biology.

    Science.gov (United States)

    Sanassy, Daven; Widera, Paweł; Krasnogor, Natalio

    2015-01-16

    Stochastic simulation algorithms (SSAs) are used to trace realistic trajectories of biochemical systems at low species concentrations. As the complexity of modeled biosystems increases, it is important to select the best performing SSA. Numerous improvements to SSAs have been introduced but they each only tend to apply to a certain class of models. This makes it difficult for a systems or synthetic biologist to decide which algorithm to employ when confronted with a new model that requires simulation. In this paper, we demonstrate that it is possible to determine which algorithm is best suited to simulate a particular model and that this can be predicted a priori to algorithm execution. We present a Web based tool ssapredict that allows scientists to upload a biochemical model and obtain a prediction of the best performing SSA. Furthermore, ssapredict gives the user the option to download our high performance simulator ngss preconfigured to perform the simulation of the queried biochemical model with the predicted fastest algorithm as the simulation engine. The ssapredict Web application is available at http://ssapredict.ico2s.org. It is free software and its source code is distributed under the terms of the GNU Affero General Public License.

  8. Augmenting Surgery via Multi-scale Modeling and Translational Systems Biology in the Era of Precision Medicine: A Multidisciplinary Perspective.

    Science.gov (United States)

    Kassab, Ghassan S; An, Gary; Sander, Edward A; Miga, Michael I; Guccione, Julius M; Ji, Songbai; Vodovotz, Yoram

    2016-09-01

    In this era of tremendous technological capabilities and increased focus on improving clinical outcomes, decreasing costs, and increasing precision, there is a need for a more quantitative approach to the field of surgery. Multiscale computational modeling has the potential to bridge the gap to the emerging paradigms of Precision Medicine and Translational Systems Biology, in which quantitative metrics and data guide patient care through improved stratification, diagnosis, and therapy. Achievements by multiple groups have demonstrated the potential for (1) multiscale computational modeling, at a biological level, of diseases treated with surgery and the surgical procedure process at the level of the individual and the population; along with (2) patient-specific, computationally-enabled surgical planning, delivery, and guidance and robotically-augmented manipulation. In this perspective article, we discuss these concepts, and cite emerging examples from the fields of trauma, wound healing, and cardiac surgery.

  9. 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.

  10. Metagenomic systems biology and metabolic modeling of the human microbiome: from species composition to community assembly rules.

    Science.gov (United States)

    Levy, Roie; Borenstein, Elhanan

    2014-01-01

    The human microbiome is a key contributor to health and development. Yet little is known about the ecological forces that are at play in defining the composition of such host-associated communities. Metagenomics-based studies have uncovered clear patterns of community structure but are often incapable of distinguishing alternative structuring paradigms. In a recent study, we integrated metagenomic analysis with a systems biology approach, using a reverse ecology framework to model numerous human microbiota species and to infer metabolic interactions between species. Comparing predicted interactions with species composition data revealed that the assembly of the human microbiome is dominated at the community level by habitat filtering. Furthermore, we demonstrated that this habitat filtering cannot be accounted for by known host phenotypes or by the metabolic versatility of the various species. Here we provide a summary of our findings and offer a brief perspective on related studies and on future approaches utilizing this metagenomic systems biology framework.

  11. A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

    Directory of Open Access Journals (Sweden)

    Hvidsten Torgeir R

    2011-01-01

    Full Text Available Abstract Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions

  12. Issues in Biological Shape Modelling

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen

    This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape or appear......This talk reflects parts of the current research at informatics and Mathematical Modelling at the Technical University of Denmark within biological shape modelling. We illustrate a series of generalizations, modifications, and applications of the elements of constructing models of shape...

  13. Unbiased Rare Event Sampling in Spatial Stochastic Systems Biology Models Using a Weighted Ensemble of Trajectories.

    Directory of Open Access Journals (Sweden)

    Rory M Donovan

    2016-02-01

    Full Text Available The long-term goal of connecting scales in biological simulation can be facilitated by scale-agnostic methods. We demonstrate that the weighted ensemble (WE strategy, initially developed for molecular simulations, applies effectively to spatially resolved cell-scale simulations. The WE approach runs an ensemble of parallel trajectories with assigned weights and uses a statistical resampling strategy of replicating and pruning trajectories to focus computational effort on difficult-to-sample regions. The method can also generate unbiased estimates of non-equilibrium and equilibrium observables, sometimes with significantly less aggregate computing time than would be possible using standard parallelization. Here, we use WE to orchestrate particle-based kinetic Monte Carlo simulations, which include spatial geometry (e.g., of organelles, plasma membrane and biochemical interactions among mobile molecular species. We study a series of models exhibiting spatial, temporal and biochemical complexity and show that although WE has important limitations, it can achieve performance significantly exceeding standard parallel simulation--by orders of magnitude for some observables.

  14. 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...

  15. 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

  16. 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.

  17. 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.

  18. Introduction to Network Analysis in Systems Biology

    OpenAIRE

    Ma’ayan, Avi

    2011-01-01

    This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled “Systems Biology: Biomedical Modeling.” The materials are from three separate lectures introducing applications of graph theory and network analysis in systems biology. The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks. The ...

  19. Nonlinear dynamics in biological systems

    CERN Document Server

    Carballido-Landeira, Jorge

    2016-01-01

    This book presents recent research results relating to applications of nonlinear dynamics, focusing specifically on four topics of wide interest: heart dynamics, DNA/RNA, cell mobility, and proteins. The book derives from the First BCAM Workshop on Nonlinear Dynamics in Biological Systems, held in June 2014 at the Basque Center of Applied Mathematics (BCAM). At this international meeting, researchers from different but complementary backgrounds, including molecular dynamics, physical chemistry, bio-informatics and biophysics, presented their most recent results and discussed the future direction of their studies using theoretical, mathematical modeling and experimental approaches. Such was the level of interest stimulated that the decision was taken to produce this publication, with the organizers of the event acting as editors. All of the contributing authors are researchers working on diverse biological problems that can be approached using nonlinear dynamics. The book will appeal especially to applied math...

  20. 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...

  1. From classical genetics to quantitative genetics to systems biology: modeling epistasis.

    Directory of Open Access Journals (Sweden)

    David L Aylor

    2008-03-01

    Full Text Available Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which is the interaction between alleles at different loci. We propose a framework for estimating and interpreting epistasis from a classical experiment that combines the strengths of each approach. A regression analysis step accommodates the quantitative nature of expression measurements by estimating the effect of gene deletions plus any interaction. Effects are selected by significance such that a reduced model describes each expression trait. We show how the resulting models correspond to specific hierarchical relationships between two regulator genes and a target gene. These relationships are the basic units of genetic pathways and genomic system diagrams. Our approach can be extended to analyze data from a variety of experiments, multiple loci, and multiple environments.

  2. The echinoderm larval skeleton as a possible model system for experimental evolutionary biology.

    Science.gov (United States)

    Koga, Hiroyuki; Morino, Yoshiaki; Wada, Hiroshi

    2014-03-01

    The evolution of various body plans results from the acquisition of novel structures as well as the loss of existing structures. Some novel structures necessitate multiple evolutionary steps, requiring organisms to overcome the intermediate steps, which might be less adaptive or neutral. To examine this issue, echinoderms might provide an ideal experimental system. A larval skeleton is acquired in some echinoderm lineages, such as sea urchins, probably via the co-option of the skeletogenic machinery that was already established to produce the adult skeleton. The acquisition of a larval skeleton was found to require multiple steps and so provides a model experimental system for reproducing intermediate evolutionary stages. The fact that echinoderm embryology has been studied with various natural populations also presents an advantage. Copyright © 2014 Wiley Periodicals, Inc.

  3. 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...... computational approaches, about the relation between living and artificial systems, and about the implications of interdisciplinary research for science and society. The entry can be openly accessed at the webpage of the Stanford Encyclopaedia of Philosophy: https://plato.stanford.edu/entries/systems-synthetic-biology/...... 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...

  4. Decision Making in Biological Systems

    DEFF Research Database (Denmark)

    Tian, Chengzhe

    -dormancy transition is primarily mediated by (p)ppGpp fluctuation. In the second topic, we discuss the transition paths between two stable steady states. We construct a simple model of coupled bistable gene circuits and demonstrate the possibility of bifurcation of transition path in biology. We then construct...... a theory to predict whether a general coupled bistable system exhibits bifurcated path or not and verify the theory through numerical simulation. We also show that a primary function of bifurcated paths is to facilitate transition by lowering the associated action. In the third topic, we discuss...

  5. Tracing overlapping biological signals in mid-infrared using colonic tissues as a model system.

    Science.gov (United States)

    Sahu, Ranjit Kumar; Salman, Ahmad; Mordechai, Shaul

    2017-01-14

    To understand the interference of carbohydrates absorbance in nucleic acids signals during diagnosis of malignancy using Fourier transform infrared (FTIR) spectroscopy. We used formalin fixed paraffin embedded colonic tissues to obtain infrared (IR) spectra in the mid IR region using a bruker II IR microscope with a facility for varying the measurement area by varying the aperture available. Following this procedure we could measure different regions of the crypt circles containing different biochemicals. Crypts from 18 patients were measured. Circular crypts with a maximum diameter of 120 μm and a lumen of about 30 μm were selected for uniformity. The spectral data was analyzed using conventional and advanced computational methods. Among the various components that are observed to contribute to the diagnostic capabilities of FTIR, the carbohydrates and nucleic acids are prominent. However there are intrinsic difficulties in the diagnostic capabilities due to the overlap of major absorbance bands of nucleic acids, carbohydrates and phospholipids in the mid-IR region. The result demonstrates colonic tissues as a biological system suitable for studying interference of carbohydrates and nucleic acids under ex vivo conditions. Among the diagnostic parameters that are affected by the absorbance from nucleic acids is the RNA/DNA ratio, dependent on absorbance at 1121 cm -1 and 1020 cm -1 that is used to classify the normal and cancerous tissues especially during FTIR based diagnosis of colonic malignancies. The signals of the nucleic acids and the ratio (RNA/DNA) are likely increased due to disappearance of interfering components like carbohydrates and phosphates along with an increase in amount of RNA. The present work, proposes one mechanism for the observed changes in the nucleic acid absorbance in mid-IR during disease progression (carcinogenesis).

  6. Introducing systems biology for nursing science.

    Science.gov (United States)

    Founds, Sandra A

    2009-07-01

    Systems biology expands on general systems theory as the "omics'' era rapidly progresses. Although systems biology has been institutionalized as an interdisciplinary framework in the biosciences, it is not yet apparent in nursing. This article introduces systems biology for nursing science by presenting an overview of the theory. This framework for the study of organisms from molecular to environmental levels includes iterations of computational modeling, experimentation, and theory building. Synthesis of complex biological processes as whole systems rather than isolated parts is emphasized. Pros and cons of systems biology are discussed, and relevance of systems biology to nursing is described. Nursing research involving molecular, physiological, or biobehavioral questions may be guided by and contribute to the developing science of systems biology. Nurse scientists can proactively incorporate systems biology into their investigations as a framework for advancing the interdisciplinary science of human health care. Systems biology has the potential to advance the research and practice goals of the National Institute for Nursing Research in the National Institutes of Health Roadmap initiative.

  7. 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 ...

  8. Systems Biology Approach and Mathematical Modeling for Analyzing Phase-Space Switch During Epithelial-Mesenchymal Transition.

    Science.gov (United States)

    Simeoni, Chiara; Dinicola, Simona; Cucina, Alessandra; Mascia, Corrado; Bizzarri, Mariano

    2018-01-01

    In this report, we aim at presenting a viable strategy for the study of Epithelial-Mesenchymal Transition (EMT) and its opposite Mesenchymal-Epithelial Transition (MET) by means of a Systems Biology approach combined with a suitable Mathematical Modeling analysis. Precisely, it is shown how the presence of a metastable state, that is identified at a mesoscopic level of description, is crucial for making possible the appearance of a phase transition mechanism in the framework of fast-slow dynamics for Ordinary Differential Equations (ODEs).

  9. Time lags in biological models

    CERN Document Server

    MacDonald, Norman

    1978-01-01

    In many biological models it is necessary to allow the rates of change of the variables to depend on the past history, rather than only the current values, of the variables. The models may require discrete lags, with the use of delay-differential equations, or distributed lags, with the use of integro-differential equations. In these lecture notes I discuss the reasons for including lags, especially distributed lags, in biological models. These reasons may be inherent in the system studied, or may be the result of simplifying assumptions made in the model used. I examine some of the techniques available for studying the solution of the equations. A large proportion of the material presented relates to a special method that can be applied to a particular class of distributed lags. This method uses an extended set of ordinary differential equations. I examine the local stability of equilibrium points, and the existence and frequency of periodic solutions. I discuss the qualitative effects of lags, and how these...

  10. Incorporation of poly-saccharidic derivatives in model biological systems: monolayers, lamellar phases and vesicles

    International Nuclear Information System (INIS)

    Deme, Bruno

    1995-01-01

    Our aim is to introduce a soluble polymer in a lyotropic lamellar phase, and to modify the force balance in the case of a collapsed system where no repulsive contribution overcomes the van der Waals attraction, except at very short distances where hydration forces dominate (i.e. a collapsed stack of membranes). Mixed layers of a synthetic lecithin (DMPC) and a hydrophobically modified polysaccharide (cholesteryl-pullulan, CHP) have been investigated at the air-water interface by surface tension experiments and by specular reflection of neutrons. The DMPC/CHP/water ternary phase diagram has been determined by small angle X-ray scattering (SAXS) and small angle neutron scattering (SANS). CHP derivatives are associative polymers bearing lateral cholesterol groups that interact with a polar phases such as phospholipid monolayers and biological membranes. These derivatives are surface active and self-aggregate in solution leading to the formation of soluble micellar type aggregates. The interaction of CHP derivatives with lipidic structures involves the anchoring of the cholesterol groups that yields to the tethering of the poly-saccharidic backbones at lipid/water interfaces. These poly-saccharidic backbones are flexible chains in good solvent in water. Using these derivatives and a new preparation procedure, we show that it is possible to avoid the depletion of the polysaccharide due to its steric exclusion by the collapsed DMPC lamellar phase. We are able to prepare samples at thermodynamic equilibrium with the polysaccharide solubilized in the lamellar phase, a situation opposed to the well known behavior of mixed polysaccharide/lecithin Systems commonly used in osmotic stress experiments. Here, the osmotic pressure of the chains confined in the lamellar lattice acts as a new long range repulsive contribution in the DMPC lyotropic L α phase and results in the swelling of the lamellar phase at large membrane separations (570 A). Such bilayer separations allow out of

  11. Biological NOx removal by denitrification process in a jet-loop bioreactor: system performance and model development.

    Science.gov (United States)

    Durmazpinar, Serdar; Ilhan, Nalan; Demir, Gonca; Insel, Güçlü; Dizge, Nadir; Ergenekon, Pinar; Erhan, Elif; Keskinler, Bülent

    2014-01-01

    Nitrogen monoxide (NO) and nitrogen dioxide referred as NOx are one of the most important air pollutants in the atmosphere. Biological NOx removal technologies have been developing to reach a cost-effective control method for upcoming stringent NOx emission standards. The BioDeNOx system was seen as a promising biological NOx control technology which is composed of two reactors, one for absorbing of NO in an aqueous Fe(II)EDTA2- solution and the other for subsequent reduction to N2 gas in a biological reactor by the denitrification process. In this study, instead of two discrete reactors, only one jet-loop bioreactor (JLBR) was utilized as both absorption and denitrification unit and no chelate-forming chemicals were added. In other words, the advantage of better mass transfer conditions of jet bioreactor was used instead of Fe(II)EDTA2-. The process was named as Jet-BioDeNOx. The JLBR was operated for the removal of NOx from air streams containing 500-3000 ppm NOx and the results showed that the removal efficiency was between 81% and 94%. The air to liquid flow ratio (Q(G)/Q(RAS)) varied in the range of 0.07-0.12. Mathematical modelling of the system demonstrated that the removal efficiency strongly depends on this ratio. The high mass transfer conditions prevailed in the reactor provided a competitive advantage on removing NO gas without any requirement of chelating chemicals.

  12. 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.

  13. 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

  14. Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling

    Directory of Open Access Journals (Sweden)

    Resendis-Antonio Osbaldo

    2011-07-01

    Full Text Available Abstract Background Bacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process. Results In this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris (bean plant. Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1 extended the metabolic reconstruction reported for R. etli; 2 simulated the metabolic activity during symbiotic nitrogen fixation; and 3 evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced

  15. Systems Biology and Livestock Science

    NARCIS (Netherlands)

    Pas, te M.F.W.; Woelders, H.; Bannink, A.

    2011-01-01

    Systems Biology is an interdisciplinary approach to the study of life made possible through the explosion of molecular data made available through the genome revolution and the simultaneous development of computational technologies that allow us to interpret these large data sets. Systems Biology

  16. 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....

  17. Muscle Stem Cells: A Model System for Adult Stem Cell Biology.

    Science.gov (United States)

    Cornelison, Ddw; Perdiguero, Eusebio

    2017-01-01

    Skeletal muscle stem cells, originally termed satellite cells for their position adjacent to differentiated muscle fibers, are absolutely required for the process of skeletal muscle repair and regeneration. In the last decade, satellite cells have become one of the most studied adult stem cell systems and have emerged as a standard model not only in the field of stem cell-driven tissue regeneration but also in stem cell dysfunction and aging. Here, we provide background in the field and discuss recent advances in our understanding of muscle stem cell function and dysfunction, particularly in the case of aging, and the potential involvement of muscle stem cells in genetic diseases such as the muscular dystrophies.

  18. Applications of Magnetic Resonance in Model Systems: Tumor Biology and Physiology

    Directory of Open Access Journals (Sweden)

    Robert J. Gillies

    2000-01-01

    Full Text Available A solid tumor presents a unique challenge as a system in which the dynamics of the relationship between vascularization, the physiological environment and metabolism are continually changing with growth and following treatment. Magnetic resonance imaging (MRI and magnetic resonance spectroscopy (MRS studies have demonstrated quantifiable linkages between the physiological environment, angiogenesis, vascularization and metabolism of tumors. The dynamics between these parameters continually change with tumor aggressiveness, tumor growth and during therapy and each of these can be monitored longitudinally, quantitatively and non-invasively with MRI and MRS. An important aspect of MRI and MRS studies is that techniques and findings are easily translated between systems. Hence, pre-clinical studies using cultured cells or experimental animals have a high connectivity to potential clinical utility. In the following review, leaders in the field of MR studies of basic tumor physiology using pre-clinical models have contributed individual sections according to their expertise and outlook. The following review is a cogent and timely overview of the current capabilities and state-of-the-art of MRI and MRS as applied to experimental cancers. A companion review deals with the application of MR methods to anticancer therapy.

  19. 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.

  20. Mathematical modeling of biological processes

    CERN Document Server

    Friedman, Avner

    2014-01-01

    This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

  1. 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.

  2. Metabolic systems biology: a brief primer.

    Science.gov (United States)

    Edwards, Lindsay M

    2017-05-01

    In the early to mid-20th century, reductionism as a concept in biology was challenged by key thinkers, including Ludwig von Bertalanffy. He proposed that living organisms were specific examples of complex systems and, as such, they should display characteristics including hierarchical organisation and emergent behaviour. Yet the true study of complete biological systems (for example, metabolism) was not possible until technological advances that occurred 60 years later. Technology now exists that permits the measurement of complete levels of the biological hierarchy, for example the genome and transcriptome. The complexity and scale of these data require computational models for their interpretation. The combination of these - systems thinking, high-dimensional data and computation - defines systems biology, typically accompanied by some notion of iterative model refinement. Only sequencing-based technologies, however, offer full coverage. Other 'omics' platforms trade coverage for sensitivity, although the densely connected nature of biological networks suggests that full coverage may not be necessary. Systems biology models are often characterised as either 'bottom-up' (mechanistic) or 'top-down' (statistical). This distinction can mislead, as all models rely on data and all are, to some degree, 'middle-out'. Systems biology has matured as a discipline, and its methods are commonplace in many laboratories. However, many challenges remain, especially those related to large-scale data integration. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

  3. Detecting critical state before phase transition of complex biological systems by hidden Markov model.

    Science.gov (United States)

    Chen, Pei; Liu, Rui; Li, Yongjun; Chen, Luonan

    2016-07-15

    Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages, i.e. before-transition state, pre-transition state and after-transition state, which can be considered as three different Markov processes. By exploring the rich dynamical information provided by high-throughput data, we present a novel computational method, i.e. hidden Markov model (HMM) based approach, to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process), thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets, and further identify the pre-transition states as well as their critical modules for three real datasets, i.e. the acute lung injury triggered by phosgene inhalation, MCF-7 human breast cancer caused by heregulin and HCV-induced dysplasia and hepatocellular carcinoma. Both functional and pathway enrichment analyses validate the computational results. The source code and some supporting files are available at https://github.com/rabbitpei/HMM_based-method lnchen@sibs.ac.cn or liyj@scut.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Dynamical systems in population biology

    CERN Document Server

    Zhao, Xiao-Qiang

    2017-01-01

    This research monograph provides an introduction to the theory of nonautonomous semiflows with applications to population dynamics. It develops dynamical system approaches to various evolutionary equations such as difference, ordinary, functional, and partial differential equations, and pays more attention to periodic and almost periodic phenomena. The presentation includes persistence theory, monotone dynamics, periodic and almost periodic semiflows, basic reproduction ratios, traveling waves, and global analysis of prototypical population models in ecology and epidemiology. Research mathematicians working with nonlinear dynamics, particularly those interested in applications to biology, will find this book useful. It may also be used as a textbook or as supplementary reading for a graduate special topics course on the theory and applications of dynamical systems. Dr. Xiao-Qiang Zhao is a University Research Professor at Memorial University of Newfoundland, Canada. His main research interests involve applied...

  5. Plant systems biology: insights, advances and challenges.

    Science.gov (United States)

    Sheth, Bhavisha P; Thaker, Vrinda S

    2014-07-01

    Plants dwelling at the base of biological food chain are of fundamental significance in providing solutions to some of the most daunting ecological and environmental problems faced by our planet. The reductionist views of molecular biology provide only a partial understanding to the phenotypic knowledge of plants. Systems biology offers a comprehensive view of plant systems, by employing a holistic approach integrating the molecular data at various hierarchical levels. In this review, we discuss the basics of systems biology including the various 'omics' approaches and their integration, the modeling aspects and the tools needed for the plant systems research. A particular emphasis is given to the recent analytical advances, updated published examples of plant systems biology studies and the future trends.

  6. 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.

  7. On finding and using identifiable parameter combinations in nonlinear dynamic systems biology models and COMBOS: a novel web implementation.

    Directory of Open Access Journals (Sweden)

    Nicolette Meshkat

    Full Text Available Parameter identifiability problems can plague biomodelers when they reach the quantification stage of development, even for relatively simple models. Structural identifiability (SI is the primary question, usually understood as knowing which of P unknown biomodel parameters p1,…, pi,…, pP are-and which are not-quantifiable in principle from particular input-output (I-O biodata. It is not widely appreciated that the same database also can provide quantitative information about the structurally unidentifiable (not quantifiable subset, in the form of explicit algebraic relationships among unidentifiable pi. Importantly, this is a first step toward finding what else is needed to quantify particular unidentifiable parameters of interest from new I-O experiments. We further develop, implement and exemplify novel algorithms that address and solve the SI problem for a practical class of ordinary differential equation (ODE systems biology models, as a user-friendly and universally-accessible web application (app-COMBOS. Users provide the structural ODE and output measurement models in one of two standard forms to a remote server via their web browser. COMBOS provides a list of uniquely and non-uniquely SI model parameters, and-importantly-the combinations of parameters not individually SI. If non-uniquely SI, it also provides the maximum number of different solutions, with important practical implications. The behind-the-scenes symbolic differential algebra algorithms are based on computing Gröbner bases of model attributes established after some algebraic transformations, using the computer-algebra system Maxima. COMBOS was developed for facile instructional and research use as well as modeling. We use it in the classroom to illustrate SI analysis; and have simplified complex models of tumor suppressor p53 and hormone regulation, based on explicit computation of parameter combinations. It's illustrated and validated here for models of moderate

  8. Surface Immobilized His-tagged Azurin as a Model Interface for the Investigation of Vectorial Electron Transfer in Biological Systems

    International Nuclear Information System (INIS)

    Casalini, Stefano; Berto, Marcello; Kovtun, Alessandro; Operamolla, Alessandra; Di Rocco, Giulia; Facci, Paolo; Liscio, Andrea; Farinola, Gianluca M.; Borsari, Marco; Bortolotti, Carlo A.

    2015-01-01

    A model system for the electrochemical investigation of vectorial electron transfer in biological systems was designed, assembled and characterized. Gold electrodes, functionalized with a -OCH 3 terminated, aromatic self-assembled monolayer, were used as a substrate for the adsorption of variants of copper-containing, redox metalloprotein azurin. The engineered azurin bears a polyhistidine tag at its C-terminus. Thanks to the presence of the solvent exposed tag, which chelates Cu 2+ ions in solution, we introduced an exogenous redox centre. The different reduction potentials of the two redox centres and their positioning with respect to the surface are such that electron transfer from the exogenous copper centre and the electrode is mediated by the native azurin active site, closely paralleling electron transfer processes in naturally occurring multicentre metalloproteins.

  9. Electromagnetic fields in biological systems

    CERN Document Server

    Lin, James C

    2016-01-01

    As wireless technology becomes more sophisticated and accessible to more users, the interactions of electromagnetic fields with biological systems have captured the interest not only of the scientific community but also the general public. Unintended or deleterious biological effects of electromagnetic fields and radiation may indicate grounds for health and safety precautions in their use. Spanning static fields to terahertz waves, Electromagnetic Fields in Biological Systems explores the range of consequences these fields have on the human body. With contributions by an array of experts, topics discussed include: Essential interactions and field coupling phenomena, highlighting their importance in research on biological effects and in scientific, industrial, and medical applications Electric field interactions in cells, focusing on ultrashort, pulsed high-intensity fields The effect of exposure to naturally occurring and human-made static, low-frequency, and pulsed magnetic fields in biological systems Dosi...

  10. Introduction to stochastic models in biology

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Samson, Adeline

    2013-01-01

    This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exp...

  11. 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.

  12. Gradient matching methods for computational inference in mechanistic models for systems biology: a review and comparative analysis

    Directory of Open Access Journals (Sweden)

    Benn eMacdonald

    2015-11-01

    Full Text Available Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs, is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimised so as to minimise some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.

  13. Mesoscopic models of biological membranes

    DEFF Research Database (Denmark)

    Venturoli, M.; Sperotto, Maria Maddalena; Kranenburg, M.

    2006-01-01

    Phospholipids are the main components of biological membranes and dissolved in water these molecules self-assemble into closed structures, of which bilayers are the most relevant from a biological point of view. Lipid bilayers are often used, both in experimental and by theoretical investigations...... to coarse grain a biological membrane. The conclusion of this comparison is that there can be many valid different strategies, but that the results obtained by the various mesoscopic models are surprisingly consistent. A second objective of this review is to illustrate how mesoscopic models can be used...

  14. A Philosophical Perspective on Evolutionary Systems Biology.

    Science.gov (United States)

    O'Malley, Maureen A; Soyer, Orkun S; Siegal, Mark L

    2015-03-01

    Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB's progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology.

  15. Biological mechanisms beyond network analysis via mathematical modeling. Comment on "Network science of biological systems at different scales: A review" by Marko Gosak et al.

    Science.gov (United States)

    Pedersen, Morten Gram

    2018-03-01

    Methods from network theory are increasingly used in research spanning from engineering and computer science to psychology and the social sciences. In this issue, Gosak et al. [1] provide a thorough review of network science applications to biological systems ranging from the subcellular world via neuroscience to ecosystems, with special attention to the insulin-secreting beta-cells in pancreatic islets.

  16. Systems biology of human atherosclerosis.

    Science.gov (United States)

    Shalhoub, Joseph; Sikkel, Markus B; Davies, Kerry J; Vorkas, Panagiotis A; Want, Elizabeth J; Davies, Alun H

    2014-01-01

    Systems biology describes a holistic and integrative approach to understand physiology and pathology. The "omic" disciplines include genomics, transcriptomics, proteomics, and metabolic profiling (metabonomics and metabolomics). By adopting a stance, which is opposing (yet complimentary) to conventional research techniques, systems biology offers an overview by assessing the "net" biological effect imposed by a disease or nondisease state. There are a number of different organizational levels to be understood, from DNA to protein, metabolites, cells, organs and organisms, even beyond this to an organism's context. Systems biology relies on the existence of "nodes" and "edges." Nodes are the constituent part of the system being studied (eg, proteins in the proteome), while the edges are the way these constituents interact. In future, it will be increasingly important to collaborate, collating data from multiple studies to improve data sets, making them freely available and undertaking integrative analyses.

  17. Dimensionality reduction of bistable biological systems.

    Science.gov (United States)

    Zakharova, A; Nikoloski, Z; Koseska, A

    2013-03-01

    Time hierarchies, arising as a result of interactions between system's components, represent a ubiquitous property of dynamical biological systems. In addition, biological systems have been attributed switch-like properties modulating the response to various stimuli across different organisms and environmental conditions. Therefore, establishing the interplay between these features of system dynamics renders itself a challenging question of practical interest in biology. Existing methods are suitable for systems with one stable steady state employed as a well-defined reference. In such systems, the characterization of the time hierarchies has already been used for determining the components that contribute to the dynamics of biological systems. However, the application of these methods to bistable nonlinear systems is impeded due to their inherent dependence on the reference state, which in this case is no longer unique. Here, we extend the applicability of the reference-state analysis by proposing, analyzing, and applying a novel method, which allows investigation of the time hierarchies in systems exhibiting bistability. The proposed method is in turn used in identifying the components, other than reactions, which determine the systemic dynamical properties. We demonstrate that in biological systems of varying levels of complexity and spanning different biological levels, the method can be effectively employed for model simplification while ensuring preservation of qualitative dynamical properties (i.e., bistability). Finally, by establishing a connection between techniques from nonlinear dynamics and multivariate statistics, the proposed approach provides the basis for extending reference-based analysis to bistable systems.

  18. 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...

  19. Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

    Science.gov (United States)

    Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

    2017-01-01

    Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham

  20. A Systems Biology Framework for Modeling Metabolic Enzyme Inhibition of Mycobacterium Tuberculosis

    Science.gov (United States)

    2009-09-15

    parameters, and group IV included those that, by definition , were directly determined once the other parameters were defined. During the sensitivity...III parameters were assumed to be related to the parameters of the first two groups; and group IV parameters are, by definition , determined once the...population growth model are described below. sAMS inhibition model sAMS inhibits the enzyme salicyl -AMP ligase (MbtA; encoded by the gene Rv2384) that

  1. 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.

  2. Systems biology and metabolic modelling unveils limitations to polyhydroxybutyrate accumulation in sugarcane leaves; lessons for C4 engineering.

    Science.gov (United States)

    McQualter, Richard B; Bellasio, Chandra; Gebbie, Leigh K; Petrasovits, Lars A; Palfreyman, Robin W; Hodson, Mark P; Plan, Manuel R; Blackman, Deborah M; Brumbley, Stevens M; Nielsen, Lars K

    2016-02-01

    In planta production of the bioplastic polyhydroxybutyrate (PHB) is one important way in which plant biotechnology can address environmental problems and emerging issues related to peak oil. However, high biomass C4 plants such as maize, switch grass and sugarcane develop adverse phenotypes including stunting, chlorosis and reduced biomass as PHB levels in leaves increase. In this study, we explore limitations to PHB accumulation in sugarcane chloroplasts using a systems biology approach, coupled with a metabolic model of C4 photosynthesis. Decreased assimilation was evident in high PHB-producing sugarcane plants, which also showed a dramatic decrease in sucrose and starch content of leaves. A subtle decrease in the C/N ratio was found which was not associated with a decrease in total protein content. An increase in amino acids used for nitrogen recapture was also observed. Based on the accumulation of substrates of ATP-dependent reactions, we hypothesized ATP starvation in bundle sheath chloroplasts. This was supported by mRNA differential expression patterns. The disruption in ATP supply in bundle sheath cells appears to be linked to the physical presence of the PHB polymer which may disrupt photosynthesis by scattering photosynthetically active radiation and/or physically disrupting thylakoid membranes. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  3. Cell culture models of biological barriers: in vitro test systems for drug absorption and delivery

    National Research Council Canada - National Science Library

    Lehr, Claus-Michael

    2002-01-01

    ... may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Every effort has been made to ensure that the advice and information in this book is t...

  4. Crop systems biology : an approach to connect functional genomics with crop modelling

    NARCIS (Netherlands)

    Yin, X.; Struik, P.C.

    2007-01-01

    The response of the whole crop to environmental conditions is a critical factor in agriculture. It can only be understood if the organization of the crop system is taken into account. A popular view in modern science is that genomics (and other `omics¿) will provide knowledge and tools to allow the

  5. Epidemiology and population biology of pseudoperonospora cubensis: a model system for management of downy mildews

    Science.gov (United States)

    The resurgence of cucurbit downy mildew has dramatically influenced production of cucurbits and disease management systems at multiple scales. Long-distance dispersal is a fundamental aspect of epidemic development that influences the timing and extent of disease outbreaks. Dispersal potential of th...

  6. 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)

  7. A framework for evolutionary systems biology.

    Science.gov (United States)

    Loewe, Laurence

    2009-02-24

    Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects. Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism. EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

  8. Instance-Based Generative Biological Shape Modeling.

    Science.gov (United States)

    Peng, Tao; Wang, Wei; Rohde, Gustavo K; Murphy, Robert F

    2009-01-01

    Biological shape modeling is an essential task that is required for systems biology efforts to simulate complex cell behaviors. Statistical learning methods have been used to build generative shape models based on reconstructive shape parameters extracted from microscope image collections. However, such parametric modeling approaches are usually limited to simple shapes and easily-modeled parameter distributions. Moreover, to maximize the reconstruction accuracy, significant effort is required to design models for specific datasets or patterns. We have therefore developed an instance-based approach to model biological shapes within a shape space built upon diffeomorphic measurement. We also designed a recursive interpolation algorithm to probabilistically synthesize new shape instances using the shape space model and the original instances. The method is quite generalizable and therefore can be applied to most nuclear, cell and protein object shapes, in both 2D and 3D.

  9. From systems biology to photosynthesis and whole-plant physiology: a conceptual model for integrating multi-scale networks.

    Science.gov (United States)

    Weston, David J; Hanson, Paul J; Norby, Richard J; Tuskan, Gerald A; Wullschleger, Stan D

    2012-02-01

    Network analysis is now a common statistical tool for molecular biologists. Network algorithms are readily used to model gene, protein and metabolic correlations providing insight into pathways driving biological phenomenon. One output from such an analysis is a candidate gene list that can be responsible, in part, for the biological process of interest. The question remains, however, as to whether molecular network analysis can be used to inform process models at higher levels of biological organization. In our previous work, transcriptional networks derived from three plant species were constructed, interrogated for orthology and then correlated with photosynthetic inhibition at elevated temperature. One unique aspect of that study was the link from co-expression networks to net photosynthesis. In this addendum, we propose a conceptual model where traditional network analysis can be linked to whole-plant models thereby informing predictions on key processes such as photosynthesis, nutrient uptake and assimilation, and C partitioning.

  10. 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

  11. Systems biology: leading the revolution in ecotoxicology.

    Science.gov (United States)

    Garcia-Reyero, Natàlia; Perkins, Edward J

    2011-02-01

    The rapid development of new technologies such as transcriptomics, proteomics, and metabolomics (Omics) are changing the way ecotoxicology is practiced. The data deluge has begun with genomes of over 65 different aquatic species that are currently being sequenced, and many times that number with at least some level of transcriptome sequencing. Integrating these top-down methodologies is an essential task in the field of systems biology. Systems biology is a biology-based interdisciplinary field that focuses on complex interactions in biological systems, with the intent to model and discover emergent properties of the system. Recent studies demonstrate that Omics technologies provide valuable insight into ecotoxicity, both in laboratory exposures with model organisms and with animals exposed in the field. However, these approaches require a context of the whole animal and population to be relevant. Powerful approaches using reverse engineering to determine interacting networks of genes, proteins, or biochemical reactions are uncovering unique responses to toxicants. Modeling efforts in aquatic animals are evolving to interrelate the interacting networks of a system and the flow of information linking these elements. Just as is happening in medicine, systems biology approaches that allow the integration of many different scales of interaction and information are already driving a revolution in understanding the impacts of pollutants on aquatic systems. © 2010 SETAC.

  12. Models of neural networks temporal aspects of coding and information processing in biological systems

    CERN Document Server

    Hemmen, J; Schulten, Klaus

    1994-01-01

    Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

  13. Model system for plant cell biology: GFP imaging in living onion epidermal cells

    Science.gov (United States)

    Scott, A.; Wyatt, S.; Tsou, P. L.; Robertson, D.; Allen, N. S.

    1999-01-01

    The ability to visualize organelle localization and dynamics is very useful in studying cellular physiological events. Until recently, this has been accomplished using a variety of staining methods. However, staining can give inaccurate information due to nonspecific staining, diffusion of the stain or through toxic effects. The ability to target green fluorescent protein (GFP) to various organelles allows for specific labeling of organelles in vivo. The disadvantages of GFP thus far have been the time and money involved in developing stable transformants or maintaining cell cultures for transient expression. In this paper, we present a rapid transient expression system using onion epidermal peels. We have localized GFP to various cellular compartments (including the cell wall) to illustrate the utility of this method and to visualize dynamics of these compartments. The onion epidermis has large, living, transparent cells in a monolayer, making them ideal for visualizing GFP. This method is easy and inexpensive, and it allows for testing of new GFP fusion proteins in a living tissue to determine deleterious effects and the ability to express before stable transformants are attempted.

  14. A tree-like Bayesian structure learning algorithm for small-sample datasets from complex biological model systems.

    Science.gov (United States)

    Yin, Weiwei; Garimalla, Swetha; Moreno, Alberto; Galinski, Mary R; Styczynski, Mark P

    2015-08-28

    There are increasing efforts to bring high-throughput systems biology techniques to bear on complex animal model systems, often with a goal of learning about underlying regulatory network structures (e.g., gene regulatory networks). However, complex animal model systems typically have significant limitations on cohort sizes, number of samples, and the ability to perform follow-up and validation experiments. These constraints are particularly problematic for many current network learning approaches, which require large numbers of samples and may predict many more regulatory relationships than actually exist. Here, we test the idea that by leveraging the accuracy and efficiency of classifiers, we can construct high-quality networks that capture important interactions between variables in datasets with few samples. We start from a previously-developed tree-like Bayesian classifier and generalize its network learning approach to allow for arbitrary depth and complexity of tree-like networks. Using four diverse sample networks, we demonstrate that this approach performs consistently better at low sample sizes than the Sparse Candidate Algorithm, a representative approach for comparison because it is known to generate Bayesian networks with high positive predictive value. We develop and demonstrate a resampling-based approach to enable the identification of a viable root for the learned tree-like network, important for cases where the root of a network is not known a priori. We also develop and demonstrate an integrated resampling-based approach to the reduction of variable space for the learning of the network. Finally, we demonstrate the utility of this approach via the analysis of a transcriptional dataset of a malaria challenge in a non-human primate model system, Macaca mulatta, suggesting the potential to capture indicators of the earliest stages of cellular differentiation during leukopoiesis. We demonstrate that by starting from effective and efficient approaches

  15. 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...... 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...... 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...

  16. Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

    Directory of Open Access Journals (Sweden)

    Tim D Williams

    2011-08-01

    Full Text Available The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

  17. Systems biology modeling reveals a possible mechanism of the tumor cell death upon oncogene inactivation in EGFR addicted cancers.

    Directory of Open Access Journals (Sweden)

    Jian-Ping Zhou

    Full Text Available Despite many evidences supporting the concept of "oncogene addiction" and many hypotheses rationalizing it, there is still a lack of detailed understanding to the precise molecular mechanism underlying oncogene addiction. In this account, we developed a mathematic model of epidermal growth factor receptor (EGFR associated signaling network, which involves EGFR-driving proliferation/pro-survival signaling pathways Ras/extracellular-signal-regulated kinase (ERK and phosphoinositol-3 kinase (PI3K/AKT, and pro-apoptotic signaling pathway apoptosis signal-regulating kinase 1 (ASK1/p38. In the setting of sustained EGFR activation, the simulation results show a persistent high level of proliferation/pro-survival effectors phospho-ERK and phospho-AKT, and a basal level of pro-apoptotic effector phospho-p38. The potential of p38 activation (apoptotic potential due to the elevated level of reactive oxygen species (ROS is largely suppressed by the negative crosstalk between PI3K/AKT and ASK1/p38 pathways. Upon acute EGFR inactivation, the survival signals decay rapidly, followed by a fast increase of the apoptotic signal due to the release of apoptotic potential. Overall, our systems biology modeling together with experimental validations reveals that inhibition of survival signals and concomitant release of apoptotic potential jointly contribute to the tumor cell death following the inhibition of addicted oncogene in EGFR addicted cancers.

  18. A systems biology approach to reconcile metabolic network models with application to Synechocystis sp. PCC 6803 for biofuel production.

    Science.gov (United States)

    Mohammadi, Reza; Fallah-Mehrabadi, Jalil; Bidkhori, Gholamreza; Zahiri, Javad; Javad Niroomand, Mohammad; Masoudi-Nejad, Ali

    2016-07-19

    Production of biofuels has been one of the promising efforts in biotechnology in the past few decades. The perspective of these efforts can be reduction of increasing demands for fossil fuels and consequently reducing environmental pollution. Nonetheless, most previous approaches did not succeed in obviating many big challenges in this way. In recent years systems biology with the help of microorganisms has been trying to overcome these challenges. Unicellular cyanobacteria are widespread phototrophic microorganisms that have capabilities such as consuming solar energy and atmospheric carbon dioxide for growth and thus can be a suitable chassis for the production of valuable organic materials such as biofuels. For the ultimate use of metabolic potential of cyanobacteria, it is necessary to understand the reactions that are taking place inside the metabolic network of these microorganisms. In this study, we developed a Java tool to reconstruct an integrated metabolic network of a cyanobacterium (Synechocystis sp. PCC 6803). We merged three existing reconstructed metabolic networks of this microorganism. Then, after modeling for biofuel production, the results from flux balance analysis (FBA) disclosed an increased yield in biofuel production for ethanol, isobutanol, 3-methyl-1-butanol, 2-methyl-1-butanol, and propanol. The numbers of blocked reactions were also decreased for 2-methyl-1-butanol production. In addition, coverage of the metabolic network in terms of the number of metabolites and reactions was increased in the new obtained model.

  19. Bridging physics and biology teaching through modeling

    Science.gov (United States)

    Hoskinson, Anne-Marie; Couch, Brian A.; Zwickl, Benjamin M.; Hinko, Kathleen A.; Caballero, Marcos D.

    2014-05-01

    As the frontiers of biology become increasingly interdisciplinary, the physics education community has engaged in ongoing efforts to make physics classes more relevant to life science majors. These efforts are complicated by the many apparent differences between these fields, including the types of systems that each studies, the behavior of those systems, the kinds of measurements that each makes, and the role of mathematics in each field. Nonetheless, physics and biology are both sciences that rely on observations and measurements to construct models of the natural world. In this article, we propose that efforts to bridge the teaching of these two disciplines must emphasize shared scientific practices, particularly scientific modeling. We define modeling using language common to both disciplines and highlight how an understanding of the modeling process can help reconcile apparent differences between the teaching of physics and biology. We elaborate on how models can be used for explanatory, predictive, and functional purposes and present common models from each discipline demonstrating key modeling principles. By framing interdisciplinary teaching in the context of modeling, we aim to bridge physics and biology teaching and to equip students with modeling competencies applicable in any scientific discipline.

  20. 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.

  1. Mathematical models in biological discovery

    CERN Document Server

    Walter, Charles

    1977-01-01

    When I was asked to help organize an American Association for the Advancement of Science symposium about how mathematical models have con­ tributed to biology, I agreed immediately. The subject is of immense importance and wide-spread interest. However, too often it is discussed in biologically sterile environments by "mutual admiration society" groups of "theoreticians", many of whom have never seen, and most of whom have never done, an original scientific experiment with the biolog­ ical materials they attempt to describe in abstract (and often prejudiced) terms. The opportunity to address the topic during an annual meeting of the AAAS was irresistable. In order to try to maintain the integrity ;,f the original intent of the symposium, it was entitled, "Contributions of Mathematical Models to Biological Discovery". This symposium was organized by Daniel Solomon and myself, held during the 141st annual meeting of the AAAS in New York during January, 1975, sponsored by sections G and N (Biological and Medic...

  2. 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

    The increasing application of network models to interpret biological systems raises a number of important methodological and epistemological questions. What novel insights can network analysis provide in biology? Are network approaches an extension of or in conflict with mechanistic research...

  3. Magnetic Actuation of Biological Systems

    Science.gov (United States)

    Lauback, Stephanie D.

    Central to the advancement of many biomedical and nanotechnology capabilities is the capacity to precisely control the motion of micro and nanostructures. These applications range from single molecule experiments to cell isolation and separation, to drug delivery and nanomachine manipulation. This dissertation focuses on actuation of biological micro- and nano-entities through the use of weak external magnetic fields, superparamagnetic beads, and ferromagnetic thin films. The magnetic platform presents an excellent method for actuation of biological systems due to its ability to directly control the motion of an array of micro and nanostructures in real-time with calibrated picoNewton forces. The energy landscape of two ferromagnetic thin film patterns (disks and zigzag wires) is experimentally explored and compared to corresponding theoretical models to quantify the applied forces and trajectories of superparamagnetic beads due to the magnetic traps. A magnetic method to directly actuate DNA nanomachines in real-time with nanometer resolution and sub-second response times using micromagnetic control was implemented through the use of stiff DNA micro-levers which bridged the large length scale mismatch between the micro-actuator and the nanomachine. Compared to current alternative methods which are limited in the actuation speeds and the number of reconfiguration states of DNA constructs, this magnetic approach enables fast actuation (˜ milliseconds) and reconfigurable conformations achieved through a continuous range of finely tuned steps. The system was initially tested through actuation of the stiff arm tethered to the surface, and two prototype DNA nanomachines (rotor and hinge) were successfully actuated using the stiff mechanical lever. These results open new possibilities in the development of functional robotic systems at the molecular scale. In exploiting the use of DNA stiff levers, a new technique was also developed to investigate the emergence of the

  4. 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

    Science.gov (United States)

    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. PMID:22649757

  5. 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.

  6. 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

    Directory of Open Access Journals (Sweden)

    Timothy James Kinsella

    2011-08-01

    Full Text Available 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 radiosensitiztion 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.

  7. Stochastic resonance in biological nonlinear evolution models

    Science.gov (United States)

    Dunkel, Jörn; Hilbert, Stefan; Schimansky-Geier, Lutz; Hänggi, Peter

    2004-05-01

    We investigate stochastic resonance in the nonlinear, one-dimensional Fisher-Eigen model (FEM), which represents an archetypal model for biological evolution based on a global coupling scheme. In doing so we consider different periodically driven fitness functions which govern the evolution of a biological phenotype population. For the case of a simple harmonic fitness function we are able to derive the exact analytic solution for the asymptotic probability density. A distinct feature of this solution is a phase lag between the driving signal and the linear response of the system. Furthermore, for more complex systems a general perturbation theory (linear response approximation) is put forward. Using the latter approach, we investigate stochastic resonance in terms of the spectral amplification measure for a quadratic, a quartic single-peaked, and for a bistable fitness function. Our analytical results are also compared with those of detailed numerical simulations. Our findings vindicate that stochastic resonance does occur in these nonlinear, globally coupled biological systems.

  8. Unified data model for biological data

    International Nuclear Information System (INIS)

    Idrees, M.

    2014-01-01

    A data model empowers us to store, retrieve and manipulate data in a unified way. We consider the biological data consists of DNA (De-Oxyribonucleic Acid), RNA (Ribonucleic Acid) and protein structures. In our Bioinformatics Lab (Bioinformatics Lab, Alkhawarizmi Institute of Computer Science, University of Engineering and Technology, Lahore, Pakistan), we have already proposed two data models for DNA and protein structures individually. In this paper, we propose a unified data model by using the data models of TOS (Temporal Object Oriented System) after making some necessary modifications to this data model and our already proposed the two data models. This proposed unified data model can be used for the modeling and maintaining the biological data (i.e. DNA, RNA and protein structures), in a single unified way. (author)

  9. Radiation interactions with biological systems.

    Science.gov (United States)

    Islam, Muhammad Torequl

    2017-05-01

    The use of radiation, especially ionizing radiation (IR), is currently attracting great attention in the field of medical sciences. However, it should be mentioned that IR has both beneficial and harmful effects in biological systems. This review aims to focus on IR-mediated physiological events in a mechanistic way. Evidence from the databases, mainly from PUBMED and SCIENCE DIRECT were considered. IR directly and/or with their lyses products (indirect) causes oxidative stresses to biological systems. These activities may be localized and systematic. Otherwise, IR-induced non-/multi-targeted effects are also evident. IR in diagnosis and cancer radiotherapy is well-known. Reactive species produced by IR are not only beneficial, but also can exert harmful effects in a biological system such as aging, genetic instability and mutagenicity, membrane lysis and cell death, alteration of enzymatic activity and metabolic events, mitochondrial dysfunction, and even cancer. Additionally, DNA adducts formation, after IR-induced DNA breakage, is a cause of blockage of DNA repair capability with an increase in cellular radiosensitivity. These may allow cellular ruin even at low IR levels. Dependent on the dose, duration of action and quality, IR plays diverse roles in biological systems.

  10. 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...

  11. 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...

  12. 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......, the application of systems biology for analyzing global regulatory structures, engineering the metabolism of cell factories, and analyzing human diseases is discussed....

  13. 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).

  14. From biological membranes to biomimetic model membranes

    Directory of Open Access Journals (Sweden)

    Eeman, M.

    2010-01-01

    Full Text Available Biological membranes play an essential role in the cellular protection as well as in the control and the transport of nutrients. Many mechanisms such as molecular recognition, enzymatic catalysis, cellular adhesion and membrane fusion take place into the biological membranes. In 1972, Singer et al. provided a membrane model, called fluid mosaic model, in which each leaflet of the bilayer is formed by a homogeneous environment of lipids in a fluid state including globular assembling of proteins and glycoproteins. Since its conception in 1972, many developments were brought to this model in terms of composition and molecular organization. The main development of the fluid mosaic model was made by Simons et al. (1997 and Brown et al. (1997 who suggested that membrane lipids are organized into lateral microdomains (or lipid rafts with a specific composition and a molecular dynamic that are different to the composition and the dynamic of the surrounding liquid crystalline phase. The discovery of a phase separation in the plane of the membrane has induced an explosion in the research efforts related to the biology of cell membranes but also in the development of new technologies for the study of these biological systems. Due to the high complexity of biological membranes and in order to investigate the biological processes that occur on the membrane surface or within the membrane lipid bilayer, a large number of studies are performed using biomimicking model membranes. This paper aims at revisiting the fundamental properties of biological membranes in terms of membrane composition, membrane dynamic and molecular organization, as well as at describing the most common biomimicking models that are frequently used for investigating biological processes such as membrane fusion, membrane trafficking, pore formation as well as membrane interactions at a molecular level.

  15. 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

  16. 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.

  17. 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

    2013-10-11

    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.

  18. 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...... perspective about the contribution of genes and genetic variants to disease is a key reason 'omics' has failed to deliver the anticipated breakthroughs. We then point out the critical utility of key concepts from physiology like homeostasis, regulated systems and redundancy as major intellectual tools...... common diseases. Finally, we attempt to integrate our critique of reductionism into a broader social framework about so-called translational research in specific and the root causes of common diseases in general. Throughout we offer ideas and suggestions that might be incorporated into the current...

  19. 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)

  20. 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)

  1. A systems biology approach to investigate the mechanism of action of trabectedin in a model of myelomonocytic leukemia.

    Science.gov (United States)

    Mannarino, L; Paracchini, L; Craparotta, I; Romano, M; Marchini, S; Gatta, R; Erba, E; Clivio, L; Romualdi, C; D'Incalci, M; Beltrame, L; Pattini, L

    2018-01-01

    This study was designed to investigate the mode of action of trabectedin in myelomonocytic leukemia cells by applying systems biology approaches to mine gene expression profiling data and pharmacological assessment of the cellular effects. Significant enrichment was found in regulons of target genes inferred for specific transcription factors, among which MAFB was the most upregulated after treatment and was central in the transcriptional network likely to be relevant for the specific therapeutic effects of trabectedin against myelomonocytic cells. Using the Connectivity Map, similarity among transcriptional signatures elicited by treatment with different compounds was investigated, showing a high degree of similarity between transcriptional signatures of trabectedin and those of the topoisomerase I inhibitor, irinotecan, and an anti-dopaminergic antagonist, thioridazine. The study highlights the potential importance of systems biology approaches to generate new hypotheses that are experimentally testable to define the specificity of the mechanism of action of drugs.

  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. Anion binding in biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Feiters, Martin C [Department of Organic Chemistry, Institute for Molecules and Materials, Faculty of Science, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen (Netherlands); Meyer-Klaucke, Wolfram [EMBL Hamburg Outstation at DESY, Notkestrasse 85, D-22607 Hamburg (Germany); Kostenko, Alexander V; Soldatov, Alexander V [Faculty of Physics, Southern Federal University, Sorge 5, Rostov-na-Donu, 344090 (Russian Federation); Leblanc, Catherine; Michel, Gurvan; Potin, Philippe [Centre National de la Recherche Scientifique and Universite Pierre et Marie Curie Paris-VI, Station Biologique de Roscoff, Place Georges Teissier, BP 74, F-29682 Roscoff cedex, Bretagne (France); Kuepper, Frithjof C [Scottish Association for Marine Science, Dunstaffnage Marine Laboratory, Oban, Argyll PA37 1QA, Scotland (United Kingdom); Hollenstein, Kaspar; Locher, Kaspar P [Institute of Molecular Biology and Biophysics, ETH Zuerich, Schafmattstrasse 20, Zuerich, 8093 (Switzerland); Bevers, Loes E; Hagedoorn, Peter-Leon; Hagen, Wilfred R, E-mail: m.feiters@science.ru.n [Department of Biotechnology, Delft University of Technology, Julianalaan 67, 2628 BC Delft (Netherlands)

    2009-11-15

    We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L{sub 3} (2p{sub 3/2}) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

  4. Anion binding in biological systems

    International Nuclear Information System (INIS)

    Feiters, Martin C; Meyer-Klaucke, Wolfram; Kostenko, Alexander V; Soldatov, Alexander V; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Kuepper, Frithjof C; Hollenstein, Kaspar; Locher, Kaspar P; Bevers, Loes E; Hagedoorn, Peter-Leon; Hagen, Wilfred R

    2009-01-01

    We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L 3 (2p 3/2 ) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

  5. Anion binding in biological systems

    Science.gov (United States)

    Feiters, Martin C.; Meyer-Klaucke, Wolfram; Kostenko, Alexander V.; Soldatov, Alexander V.; Leblanc, Catherine; Michel, Gurvan; Potin, Philippe; Küpper, Frithjof C.; Hollenstein, Kaspar; Locher, Kaspar P.; Bevers, Loes E.; Hagedoorn, Peter-Leon; Hagen, Wilfred R.

    2009-11-01

    We compare aspects of biological X-ray absorption spectroscopy (XAS) studies of cations and anions, and report on some examples of anion binding in biological systems. Brown algae such as Laminaria digitata (oarweed) are effective accumulators of I from seawater, with tissue concentrations exceeding 50 mM, and the vanadate-containing enzyme haloperoxidase is implicated in halide accumulation. We have studied the chemical state of iodine and its biological role in Laminaria at the I K edge, and bromoperoxidase from Ascophyllum nodosum (knotted wrack) at the Br K edge. Mo is essential for many forms of life; W only for certain archaea, such as Archaeoglobus fulgidus and the hyperthermophilic archaeon Pyrococcus furiosus, and some bacteria. The metals are bound and transported as their oxo-anions, molybdate and tungstate, which are similar in size. The transport protein WtpA from P. furiosus binds tungstate more strongly than molybdate, and is related in sequence to Archaeoglobus fulgidus ModA, of which a crystal structure is known. We have measured A. fulgidus ModA with tungstate at the W L3 (2p3/2) edge, and compared the results with the refined crystal structure. XAS studies of anion binding are feasible even if only weak interactions are present, are biologically relevant, and give new insights in the spectroscopy.

  6. Prospective Tests on Biological Models of Acupuncture

    Directory of Open Access Journals (Sweden)

    Charles Shang

    2009-01-01

    Full Text Available The biological effects of acupuncture include the regulation of a variety of neurohumoral factors and growth control factors. In science, models or hypotheses with confirmed predictions are considered more convincing than models solely based on retrospective explanations. Literature review showed that two biological models of acupuncture have been prospectively tested with independently confirmed predictions: The neurophysiology model on the long-term effects of acupuncture emphasizes the trophic and anti-inflammatory effects of acupuncture. Its prediction on the peripheral effect of endorphin in acupuncture has been confirmed. The growth control model encompasses the neurophysiology model and suggests that a macroscopic growth control system originates from a network of organizers in embryogenesis. The activity of the growth control system is important in the formation, maintenance and regulation of all the physiological systems. Several phenomena of acupuncture such as the distribution of auricular acupuncture points, the long-term effects of acupuncture and the effect of multimodal non-specific stimulation at acupuncture points are consistent with the growth control model. The following predictions of the growth control model have been independently confirmed by research results in both acupuncture and conventional biomedical sciences: (i Acupuncture has extensive growth control effects. (ii Singular point and separatrix exist in morphogenesis. (iii Organizers have high electric conductance, high current density and high density of gap junctions. (iv A high density of gap junctions is distributed as separatrices or boundaries at body surface after early embryogenesis. (v Many acupuncture points are located at transition points or boundaries between different body domains or muscles, coinciding with the connective tissue planes. (vi Some morphogens and organizers continue to function after embryogenesis. Current acupuncture research suggests a

  7. Modeling nonspecific interactions at biological interfaces

    Science.gov (United States)

    White, Andrew D.

    Difficulties in applied biomaterials often arise from the complexities of interactions in biological environments. These interactions can be broadly broken into two categories: those which are important to function (strong binding to a single target) and those which are detrimental to function (weak binding to many targets). These will be referred to as specific and nonspecific interactions, respectively. Nonspecific interactions have been central to failures of biomaterials, sensors, and surface coatings in harsh biological environments. There is little modeling work on studying nonspecific interactions. Modeling all possible nonspecific interactions within a biological system is difficult, yet there are ways to both indirectly model nonspecific interactions and directly model many interactions using machine-learning. This research utilizes bioinformatics, phenomenological modeling, molecular simulations, experiments, and stochastic modeling to study nonspecific interactions. These techniques are used to study the hydration molecules which resist nonspecific interactions, the formation of salt bridges, the chemistry of protein surfaces, nonspecific stabilization of proteins in molecular chaperones, and analysis of high-throughput screening experiments. The common aspect for these systems is that nonspecific interactions are more important than specific interactions. Studying these disparate systems has created a set of principles for resisting nonspecific interactions which have been experimentally demonstrated with the creation and testing of novel materials which resist nonspecific interactions.

  8. Reaction of long-lived radicals and vitamin C in γ-irradiated mammalian cells and their model system at 295 K. Tunneling reaction in biological system

    International Nuclear Information System (INIS)

    Matsumoto, Takuro; Miyazaki, Tetsuo; Kosugi, Yoshio; Kumada, Takayuki; Koyama, Sinji; Kodama, Seiji; Watanabe, Masami.

    1996-01-01

    When golden hamster embryo (GHE) cells or concentrated albumin solution (0.1 kg dm -3 ) that is a model system of cells is irradiated with γ-rays at 295 K, organic radicals produced can be observed by ESR. The organic radicals survive at both 295 K and 310 K for such a long time as 20 hr. The long-lived radicals in GHE cells and the albumin solution react with vitamin C by the rate constants of 0.007 dm 3 mol -1 s -1 and 0.014 dm 3 mol -1 s -1 , respectively. The long-lived radicals in human cells cause gene mutation, which is suppressed by addition of vitamin C. The isotope effect on the rate constant (k) for the reaction of the long-lived radicals and vitamin C has been studied in the albumin solution by use of protonated vitamin C and deuterated vitamin C. The isotope effect (k H /k D ) was more than 20-50 and was interpreted in terms of tunneling reaction. When GHE cells or the aqueous albumin solution (0.1 kg dm -3 ) is irradiated with γ-rays at 295 K, organic radicals produced survive for more than 24 hr at room temperature. Very recently we have found that vitamin C reacts with the long-lived organic radicals in the γ-irradiated albumin solution at high concentration of 0.1 kg dm -3 by the rate constant of 0.014 dm 3 mol -1 s -1 . Since most of reactions in biological systems including the reaction of vitamin C are a transfer of a hydrogen atom or a proton that has a large wave character, it is generally expected that the tunneling reaction may play an important role in biological systems at room temperature. The studies of isotope effects on reactions will give an information on the contribution of tunneling reaction. (J.P.N.)

  9. Free radical scavenging and antiatherogenic activities of Sesamum indicum seed extracts in chemical and biological model systems.

    Science.gov (United States)

    Visavadiya, Nishant P; Soni, Badrish; Dalwadi, Nirav

    2009-10-01

    An emerging consensus underscores the importance of oxidative events in vascular disease including excess production of reactive oxygen/nitrogen species (ROS/RNS), in addition to lipoprotein oxidation. Sesamum indicum has long been used extensively as a traditional food. The aim of present study was to evaluate antioxidant action of aqueous and ethanolic seed extracts from S. indicum using various in vitro ROS/RNS generated chemical and biological models. Results demonstrated that the graded-dose (25-1000 microg/ml) of aqueous and ethanolic extracts markedly scavenged the nitric oxide, superoxide, hydroxyl, 1,1-diphenyl-2-picrylhydrazyl and 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) radicals and, showed metal chelating ability as well as reducing capacity in Fe(3+)/ferricyanide complex and ferric reducing antioxidant power assays. In biological models, both extracts were found to inhibit metal-induced lipid peroxidation in mitochondrial fractions, human serum and LDL oxidation models. In lipoprotein kinetics study, both extracts significantly (Pindicum showed higher amounts of total polyphenol and flavonoid content as compared to their counterpart. The IC(50) values of both extracts were compared with respective antioxidant standards. Overall, ethanolic extract of S. indicum possess strong antioxidant capacity and offering effective protection against LDL oxidation susceptibility.

  10. 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...... does one choose the correct promoter and what are the appropriate methods for reading promoter strength? Furthermore, how fine should the tuning of gene expression be for some specific applications and how can the simultaneous and individual tuning of multiple genes be achieved? Some recent studies...

  11. 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.

  12. Determination of Relative Biological Efficacy (RBE) and Oxygen Enhancement Ratio (OER) for the entire negative and positive pion beam profile using Vicia faba roots and Drosophila embryos as biological model systems

    International Nuclear Information System (INIS)

    Baarli, J.; Bianchi, M.; Keusch, F.; Mindek, G.; Sullivan, A.H.

    As an introduction to preclinical studies, pilot studies of pion beams are planned with relatively simple biological model systems that can be quickly evaluated and that yield indicative data for further action. Inhibition of growth was studied in Vicia faba roots, a biological system excellently suited for RBE and OER studies. For comparison there are already results from a low-intensity pion irradiation. A second system used Drosophila embryos 1 and 4 hours old, which are especially well suited for LET studies. The unambiguous criterion will be failure to slip out of the oolemma. The smallness of the objects (their beam sensitivity) will make it possible to determine empirically the peak region and to determine Gain factors; furthermore, the known dependency of RBE on the development stage promises highly informative results

  13. Understanding Global Change (UGC) as a Unifying Conceptual Framework for Teaching Ecology: Using UGC in a High School Biology Program to Integrate Earth Science and Biology, and to Demonstrate the Value of Modeling Global Systems in Promoting Conceptual Learning

    Science.gov (United States)

    Levine, J.; Bean, J. R.

    2017-12-01

    Global change science is ideal for NGSS-informed teaching, but presents a serious challenge to K-12 educators because it is complex and interdisciplinary- combining earth science, biology, chemistry, and physics. Global systems are themselves complex. Adding anthropogenic influences on those systems creates a formidable list of topics - greenhouse effect, climate change, nitrogen enrichment, introduced species, land-use change among them - which are often presented as a disconnected "laundry list" of "facts." This complexity, combined with public and mass-media scientific illiteracy, leaves global change science vulnerable to misrepresentation and politicization, creating additional challenges to teachers in public schools. Ample stand-alone, one-off, online resources, many of them excellent, are (to date) underutilized by teachers in the high school science course taken by most students: biology. The Understanding Global Change project (UGC) from the UC Berkeley Museum of Paleontology has created a conceptual framework that organizes, connects, and explains global systems, human and non-human drivers of change in those systems, and measurable changes in those systems. This organization and framework employ core ideas, crosscutting concepts, structure/function relationships, and system models in a unique format that facilitates authentic understanding, rather than memorization. This system serves as an organizing framework for the entire ecology unit of a forthcoming mainstream high school biology program. The UGC system model is introduced up front with its core informational graphic. The model is elaborated, step by step, by adding concepts and processes as they are introduced and explained in each chapter. The informational graphic is thus used in several ways: to organize material as it is presented, to summarize topics in each chapter and put them in perspective, and for review and critical thinking exercises that supplement the usual end-of-chapter lists of

  14. Track structure in biological models.

    Science.gov (United States)

    Curtis, S B

    1986-01-01

    High-energy heavy ions in the galactic cosmic radiation (HZE particles) may pose a special risk during long term manned space flights outside the sheltering confines of the earth's geomagnetic field. These particles are highly ionizing, and they and their nuclear secondaries can penetrate many centimeters of body tissue. The three dimensional patterns of ionizations they create as they lose energy are referred to as their track structure. Several models of biological action on mammalian cells attempt to treat track structure or related quantities in their formulation. The methods by which they do this are reviewed. The proximity function is introduced in connection with the theory of Dual Radiation Action (DRA). The ion-gamma kill (IGK) model introduces the radial energy-density distribution, which is a smooth function characterizing both the magnitude and extension of a charged particle track. The lethal, potentially lethal (LPL) model introduces lambda, the mean distance between relevant ion clusters or biochemical species along the track. Since very localized energy depositions (within approximately 10 nm) are emphasized, the proximity function as defined in the DRA model is not of utility in characterizing track structure in the LPL formulation.

  15. The Impact of Systems Biology on Bioprocessing

    DEFF Research Database (Denmark)

    Campbell, Kate; Xia, Jianye; Nielsen, Jens

    2017-01-01

    alongside mathematical modeling to characterize and predict cellular physiology. This approach can drive cycles of design, build, test, and learn implemented by metabolic engineers to optimize the cell factory performance. Streamlining of the design phase requires a clearer understanding of metabolism...... and its regulation, which can be achieved using quantitative and integrated omic characterization, alongside more advanced analytical methods. We discuss here the current impact of systems biology and challenges of closing the gap between bioprocessing and more traditional methods of chemical production....

  16. Systems biology solutions for biochemical production challenges

    DEFF Research Database (Denmark)

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

    2017-01-01

    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......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...

  17. Spatial Structures and Regulation in Biological Systems

    DEFF Research Database (Denmark)

    Yde, Pernille

    , and the other is the spatial regulation of biological systems, here related to different aspects of the inflammatory response. All systems are studied using computational modelling and mathematical analysis. The first part of the thesis explores different protein aggregation scenarios. In Chapter 1, we consider...... a previously studied and very general aggregation model describing frangible linear filaments. This model is especially relevant for the growth of amyloid fibres, that have been related to a number of serious human diseases, and which are known to grow in an accelerated self-enhanced manner.We derive...... model of the tissue and show how coupled cells are able to function as an excitable medium and propagate waves of high cytokine concentration through the tissue. If the internal regulation in the cells is over-productive, the model predicts a continuous amplification of cytokines, which spans the entire...

  18. 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

  19. From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

    Science.gov (United States)

    Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

    2010-01-01

    We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

  20. Oscillation and stability of delay models in biology

    CERN Document Server

    Agarwal, Ravi P; Saker, Samir H

    2014-01-01

    Environmental variation plays an important role in many biological and ecological dynamical systems. This monograph focuses on the study of oscillation and the stability of delay models occurring in biology. The book presents recent research results on the qualitative behavior of mathematical models under different physical and environmental conditions, covering dynamics including the distribution and consumption of food. Researchers in the fields of mathematical modeling, mathematical biology, and population dynamics will be particularly interested in this material.

  1. 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.

  2. Integration of host plant resistance and biological control: using Arabidopsis-insect interactions as a model system

    NARCIS (Netherlands)

    Yang, L.

    2008-01-01

    Two main methods in sustainable pest control are host plant resistance and biological control. These methods have been developed in isolation. However, host plant characteristics can decisively affect the effectiveness of biological control agents, and therefore when altering plant characteristics

  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. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  5. 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 ...

  6. 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.

  7. Discovery of Chemical Toxicity via Biological Networks and Systems Biology

    Energy Technology Data Exchange (ETDEWEB)

    Perkins, Edward; Habib, Tanwir; Guan, Xin; Escalon, Barbara; Falciani, Francesco; Chipman, J.K.; Antczak, Philipp; Edwards, Stephen; Taylor, Ronald C.; Vulpe, Chris; Loguinov, Alexandre; Van Aggelen, Graham; Villeneuve, Daniel L.; Garcia-Reyero, Natalia

    2010-09-30

    Both soldiers and animals are exposed to many chemicals as the result of military activities. Tools are needed to understand the hazards and risks that chemicals and new materials pose to soldiers and the environment. We have investigated the potential of global gene regulatory networks in understanding the impact of chemicals on reproduction. We characterized effects of chemicals on ovaries of the model animal system, the Fathead minnow (Pimopheles promelas) connecting chemical impacts on gene expression to circulating blood levels of the hormones testosterone and estradiol in addition to the egg yolk protein vitellogenin. We describe the application of reverse engineering complex interaction networks from high dimensional gene expression data to characterize chemicals that disrupt the hypothalamus-pituitary-gonadal endocrine axis that governs reproduction in fathead minnows. The construction of global gene regulatory networks provides deep insights into how drugs and chemicals effect key organs and biological pathways.

  8. Global asymptotic stability of bistable traveling fronts in reaction-diffusion systems and their applications to biological models

    International Nuclear Information System (INIS)

    Wu Shiliang; Li Wantong

    2009-01-01

    This paper deals with the global asymptotic stability and uniqueness (up to translation) of bistable traveling fronts in a class of reaction-diffusion systems. The known results do not apply in solving these problems because the reaction terms do not satisfy the required monotone condition. To overcome the difficulty, a weak monotone condition is proposed for the reaction terms, which is called interval monotone condition. Under such a weak monotone condition, the existence and comparison theorem of solutions is first established for reaction-diffusion systems on R by appealing to the theory of abstract differential equations. The global asymptotic stability and uniqueness (up to translation) of bistable traveling fronts are then proved by the elementary super- and sub-solution comparison and squeezing methods for nonlinear evolution equations. Finally, these abstract results are applied to a two species competition-diffusion model and a system modeling man-environment-man epidemics.

  9. 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

  10. Evidence for phenotypic plasticity in aggressive triple-negative breast cancer: human biology is recapitulated by a novel model system.

    Directory of Open Access Journals (Sweden)

    Nicholas C D'Amato

    Full Text Available Breast cancers with a basal-like gene signature are primarily triple-negative, frequently metastatic, and carry a poor prognosis. Basal-like breast cancers are enriched for markers of breast cancer stem cells as well as markers of epithelial-mesenchymal transition (EMT. While EMT is generally thought to be important in the process of metastasis, in vivo evidence of EMT in human disease remains rare. Here we report a novel model of human triple-negative breast cancer, the DKAT cell line, which was isolated from an aggressive, treatment-resistant triple-negative breast cancer that demonstrated morphological and biochemical evidence suggestive of phenotypic plasticity in the patient. The DKAT cell line displays a basal-like phenotype in vitro when cultured in serum-free media, and undergoes phenotypic changes consistent with EMT/MET in response to serum-containing media, a unique property among the breast cancer cell lines we tested. This EMT is marked by increased expression of the transcription factor Zeb1, and Zeb1 is required for the enhanced migratory ability of DKAT cells in the mesenchymal state. DKAT cells also express progenitor-cell markers, and single DKAT cells are able to generate tumorspheres containing both epithelial and mesenchymal cell types. In vivo, as few as ten DKAT cells are capable of forming xenograft tumors which display a range of epithelial and mesenchymal phenotypes. The DKAT model provides a novel model to study the molecular mechanisms regulating phenotypic plasticity and the aggressive biology of triple-negative breast cancers.

  11. Simulated influence of postweaning production system on performance of different biological types of cattle: I. Estimation of model parameters.

    Science.gov (United States)

    Williams, C B; Bennett, G L; Keele, J W

    1995-03-01

    Breed parameters for a computer model that simulated differences in the composition of empty-body gain of beef cattle, resulting from differences in postweaning level of nutrition that are not associated with empty BW, were estimated for 17 biological types of cattle (steers from F1 crosses of 16 sire breeds [Hereford, Angus, Jersey, South Devon, Limousin, Simmental, Charolais, Red Poll, Brown Swiss, Gelbvieh, Maine Anjou, Chianina, Brahman, Sahiwal, Pinzgauer, and Tarentaise] mated to Hereford and Angus dams). One value for the maximum fractional growth rate of fat-free matter (KMAX) was estimated and used across all breed types. Mature fat-free matter (FFMmat) was estimated from data on mature cows for each of the 17 breed types. Breed type values for a fattening parameter (THETA) were estimated from growth and composition data at slaughter on steers of the 17 breed types, using the previously estimated constant KMAX and breed values for FFMmat. For each breed type, THETA values were unique for given values of KMAX, FFMmat, and composition at slaughter. The results showed that THETA was most sensitive to KMAX and had similar sensitivity to FFMmat and composition at slaughter. Values for THETA were most sensitive for breed types with large THETA values (Chianina, Charolais, and Limousin crossbred steers) and least sensitive for breed types with small THETA values (purebred Angus, crossbred Jersey, and Red Poll steers).(ABSTRACT TRUNCATED AT 250 WORDS)

  12. Modeling the fate and effect of benzalkonium chlorides in a continuous-flow biological nitrogen removal system treating poultry processing wastewater.

    Science.gov (United States)

    Hajaya, Malek G; Pavlostathis, Spyros G

    2013-02-01

    The fate and effect of the antimicrobial compounds benzalkonium chlorides (BACs) on the biological nitrogen removal (BNR) processes for a continuous-flow, three-stage laboratory-scale BNR system were modeled. Three kinetic sub-models, corresponding to each reactor, were developed and then combined in a comprehensive ASM1-based model. Kinetic parameters for the three sub-models were evaluated using experimental data obtained from independent batch assays. The biodegradation of BACs was modeled with a mixed-substrate Monod equation. The inhibitory effect of BACs on the utilization of degradable COD and denitrification was modeled as competitive inhibition, whereas non-competitive inhibition was used to model the effect of BACs on nitrification and inhibition coefficients were evaluated. The model simulated well the long-term performance of the BNR system treating a poultry processing wastewater with and without BACs. Enhanced BAC degradation by heterotrophs and increased resistance of nitrifiers to BACs, reflecting acclimation/enrichment over time, is a salient feature of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Proteome analysis of mouse model systems: A tool to model human disease and for the investigation of tissue-specific biology.

    Science.gov (United States)

    Kislinger, Thomas; Gramolini, Anthony O

    2010-10-10

    The molecular dissections of the mechanistic pathways involved in human disease have always relied on the use of model organisms. Among the higher mammalian organisms, the laboratory mouse (Mus musculus) is the most widely used model. A large number of commercially-available, inbred strains are available to the community, including an ever growing collection of transgenic, knock-out, and disease models. Coupled to availability is the fact that animal colonies can be kept under standardized housing condition at most major universities and research institutes, with relative ease and cost efficiency (compared to larger vertebrates). As such, mouse models to study human biology and disease remains extremely attractive. In the current review we will provide an historic overview of the use of mouse models in proteome research with a focus on general tissue and organelle biology, comparative proteomics of human and mouse and the use of mouse models to study cardiac disease. Crown Copyright © 2010. Published by Elsevier B.V. All rights reserved.

  14. A biological model for construction of meaning to serve as an interface between an intelligent system and its environments

    Energy Technology Data Exchange (ETDEWEB)

    Freeman, W.J. [Univ of California, Berkeley, CA (United States)

    1996-12-31

    There are two main levels of neural function to be modeled with appropriate state variables and operations. Microscopic activity is seen in the fraction of the variance of single neuron pulse trains (>99.9%) that is largely random and uncorrelated with pulse trains of other neurons in the neuropil. Macroscopic activity is revealed in the >0.1% of the total variance of each neuron that is covariant with all other neurons in neuropil comprising a population. It is observed in dendritic potentials recorded as surface EEGs. The {open_quotes}spontaneous{close_quotes} background activity of neuropil at both levels arises from mutual excitation within a population of excitatory neurons. Its governing point attractor is set by the macroscopic state, which acts as an order parameter to regulate the contributing neurons. The point attractor manifests a homogeneous field of white noise, which can be modeled by a continuous time state variable for pulse density. Neuropil comprises both excitatory and inhibitory neurons Their interactions at the macroscopic level give oscillations, manifesting a limit cycle attractor. Multiple areas of neuropil comprising a sensory system interact. Due to their incommensurate characteristic frequencies and the long axonal delays between them, the system maintains a global chaotic attractor having multiple wings, one for each discriminable class of stimuli. Access to each wing is by stimulus- induced state transitions, causing construction of macroscopic chaotic patterns, that are carried to targets of cortical transmission by axon tracts. AM patterns of the carrier are extracted by the targets by spatiotemporal integration, thereby retrieving the covariance comprising the chaotic signal. In digital models, noise serves to stabilize the chaotic attractors. An example will be given of the model operating as an interface between the environment and a pattern classifier, which learns to form its own feature detectors.

  15. INTERVAL OBSERVER FOR A BIOLOGICAL REACTOR MODEL

    Directory of Open Access Journals (Sweden)

    T. A. Kharkovskaia

    2014-05-01

    Full Text Available The method of an interval observer design for nonlinear systems with parametric uncertainties is considered. The interval observer synthesis problem for systems with varying parameters consists in the following. If there is the uncertainty restraint for the state values of the system, limiting the initial conditions of the system and the set of admissible values for the vector of unknown parameters and inputs, the interval existence condition for the estimations of the system state variables, containing the actual state at a given time, needs to be held valid over the whole considered time segment as well. Conditions of the interval observers design for the considered class of systems are shown. They are: limitation of the input and state, the existence of a majorizing function defining the uncertainty vector for the system, Lipschitz continuity or finiteness of this function, the existence of an observer gain with the suitable Lyapunov matrix. The main condition for design of such a device is cooperativity of the interval estimation error dynamics. An individual observer gain matrix selection problem is considered. In order to ensure the property of cooperativity for interval estimation error dynamics, a static transformation of coordinates is proposed. The proposed algorithm is demonstrated by computer modeling of the biological reactor. Possible applications of these interval estimation systems are the spheres of robust control, where the presence of various types of uncertainties in the system dynamics is assumed, biotechnology and environmental systems and processes, mechatronics and robotics, etc.

  16. JAK/STAT signalling--an executable model assembled from molecule-centred modules demonstrating a module-oriented database concept for systems and synthetic biology.

    Science.gov (United States)

    Blätke, Mary Ann; Dittrich, Anna; Rohr, Christian; Heiner, Monika; Schaper, Fred; Marwan, Wolfgang

    2013-06-01

    Mathematical models of molecular networks regulating biological processes in cells or organisms are most frequently designed as sets of ordinary differential equations. Various modularisation methods have been applied to reduce the complexity of models, to analyse their structural properties, to separate biological processes, or to reuse model parts. Taking the JAK/STAT signalling pathway with the extensive combinatorial cross-talk of its components as a case study, we make a natural approach to modularisation by creating one module for each biomolecule. Each module consists of a Petri net and associated metadata and is organised in a database publically accessible through a web interface (). The Petri net describes the reaction mechanism of a given biomolecule and its functional interactions with other components including relevant conformational states. The database is designed to support the curation, documentation, version control, and update of individual modules, and to assist the user in automatically composing complex models from modules. Biomolecule centred modules, associated metadata, and database support together allow the automatic creation of models by considering differential gene expression in given cell types or under certain physiological conditions or states of disease. Modularity also facilitates exploring the consequences of alternative molecular mechanisms by comparative simulation of automatically created models even for users without mathematical skills. Models may be selectively executed as an ODE system, stochastic, or qualitative models or hybrid and exported in the SBML format. The fully automated generation of models of redesigned networks by metadata-guided modification of modules representing biomolecules with mutated function or specificity is proposed.

  17. 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. 

  18. Biological diversity in the patent system.

    Directory of Open Access Journals (Sweden)

    Paul Oldham

    Full Text Available Biological diversity in the patent system is an enduring focus of controversy but empirical analysis of the presence of biodiversity in the patent system has been limited. To address this problem we text mined 11 million patent documents for 6 million Latin species names from the Global Names Index (GNI established by the Global Biodiversity Information Facility (GBIF and Encyclopedia of Life (EOL. We identified 76,274 full Latin species names from 23,882 genera in 767,955 patent documents. 25,595 species appeared in the claims section of 136,880 patent documents. This reveals that human innovative activity involving biodiversity in the patent system focuses on approximately 4% of taxonomically described species and between 0.8-1% of predicted global species. In this article we identify the major features of the patent landscape for biological diversity by focusing on key areas including pharmaceuticals, neglected diseases, traditional medicines, genetic engineering, foods, biocides, marine genetic resources and Antarctica. We conclude that the narrow focus of human innovative activity and ownership of genetic resources is unlikely to be in the long term interest of humanity. We argue that a broader spectrum of biodiversity needs to be opened up to research and development based on the principles of equitable benefit-sharing, respect for the objectives of the Convention on Biological Diversity, human rights and ethics. Finally, we argue that alternative models of innovation, such as open source and commons models, are required to open up biodiversity for research that addresses actual and neglected areas of human need. The research aims to inform the implementation of the 2010 Nagoya Protocol on Access to Genetic Resources and the Equitable Sharing of Benefits Arising from their Utilization and international debates directed to the governance of genetic resources. Our research also aims to inform debates under the Intergovernmental Committee on

  19. Biological Diversity in the Patent System

    Science.gov (United States)

    Oldham, Paul; Hall, Stephen; Forero, Oscar

    2013-01-01

    Biological diversity in the patent system is an enduring focus of controversy but empirical analysis of the presence of biodiversity in the patent system has been limited. To address this problem we text mined 11 million patent documents for 6 million Latin species names from the Global Names Index (GNI) established by the Global Biodiversity Information Facility (GBIF) and Encyclopedia of Life (EOL). We identified 76,274 full Latin species names from 23,882 genera in 767,955 patent documents. 25,595 species appeared in the claims section of 136,880 patent documents. This reveals that human innovative activity involving biodiversity in the patent system focuses on approximately 4% of taxonomically described species and between 0.8–1% of predicted global species. In this article we identify the major features of the patent landscape for biological diversity by focusing on key areas including pharmaceuticals, neglected diseases, traditional medicines, genetic engineering, foods, biocides, marine genetic resources and Antarctica. We conclude that the narrow focus of human innovative activity and ownership of genetic resources is unlikely to be in the long term interest of humanity. We argue that a broader spectrum of biodiversity needs to be opened up to research and development based on the principles of equitable benefit-sharing, respect for the objectives of the Convention on Biological Diversity, human rights and ethics. Finally, we argue that alternative models of innovation, such as open source and commons models, are required to open up biodiversity for research that addresses actual and neglected areas of human need. The research aims to inform the implementation of the 2010 Nagoya Protocol on Access to Genetic Resources and the Equitable Sharing of Benefits Arising from their Utilization and international debates directed to the governance of genetic resources. Our research also aims to inform debates under the Intergovernmental Committee on Intellectual

  20. 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.

  1. 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...

  2. 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.

  3. Interdisciplinary problem-solving: emerging modes in integrative systems biology

    NARCIS (Netherlands)

    MacLeod, Miles Alexander James; Nersessian, Nancy J.

    2016-01-01

    Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an

  4. Piecewise deterministic processes in biological models

    CERN Document Server

    Rudnicki, Ryszard

    2017-01-01

    This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

  5. Language Based Techniques for Systems Biology

    DEFF Research Database (Denmark)

    Pilegaard, Henrik

    Process calculus is the common denominator for a class of compact, idealised, domain-specific formalisms normally associated with the study of reactive concurrent systems within Computer Science. With the rise of the interactioncentred science of Systems Biology a number of bio-inspired process......), is context insensitive, while the other, a poly-variant analysis (2CFA), is context-sensitive. These analyses compute safe approximations to the set of spatial configurations that are reachable according to a given model. This is useful in the qualitative study of cellular self-organisation and, e.......g., the effects of receptor defects or drug delivery mechanisms. The property of sequential realisability. which is closely related to the function of biochemical pathways, is addressed by a variant of traditional Data Flow Analysis (DFA). This so-called ‘Pathway Analysis’ computes safe approximations to the set...

  6. 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...

  7. A top-down systems biology view of microbiome-mammalian metabolic interactions in a mouse model

    Science.gov (United States)

    Martin, François-Pierre J; Dumas, Marc-Emmanuel; Wang, Yulan; Legido-Quigley, Cristina; Yap, Ivan K S; Tang, Huiru; Zirah, Séverine; Murphy, Gerard M; Cloarec, Olivier; Lindon, John C; Sprenger, Norbert; Fay, Laurent B; Kochhar, Sunil; van Bladeren, Peter; Holmes, Elaine; Nicholson, Jeremy K

    2007-01-01

    Symbiotic gut microorganisms (microbiome) interact closely with the mammalian host's metabolism and are important determinants of human health. Here, we decipher the complex metabolic effects of microbial manipulation, by comparing germfree mice colonized by a human baby flora (HBF) or a normal flora to conventional mice. We perform parallel microbiological profiling, metabolic profiling by 1H nuclear magnetic resonance of liver, plasma, urine and ileal flushes, and targeted profiling of bile acids by ultra performance liquid chromatography–mass spectrometry and short-chain fatty acids in cecum by GC-FID. Top-down multivariate analysis of metabolic profiles reveals a significant association of specific metabotypes with the resident microbiome. We derive a transgenomic graph model showing that HBF flora has a remarkably simple microbiome/metabolome correlation network, impacting directly on the host's ability to metabolize lipids: HBF mice present higher ileal concentrations of tauro-conjugated bile acids, reduced plasma levels of lipoproteins but higher hepatic triglyceride content associated with depletion of glutathione. These data indicate that the microbiome modulates absorption, storage and the energy harvest from the diet at the systems level. PMID:17515922

  8. Development of a Model, Metal-reducing Microbial Community for a System Biology Level Assessment of Desulfovibrio vulgaris as part of a Community

    Energy Technology Data Exchange (ETDEWEB)

    Elias, Dwayne; Schadt, Christopher; Miller, Lance; Phelps, Tommy; Brown, S. D.; Arkin, Adam; Hazen, Terry; Drake, Megin; Yang, Z.K.; Podar, Mircea

    2010-05-17

    One of the largest experimental gaps is between the simplicity of pure cultures and the complexity of open environmental systems, particularly in metal-contaminated areas. These microbial communities form ecosystem foundations, drive biogeochemical processes, and are relevant for biotechnology and bioremediation. A model, metal-reducing microbial community was constructed as either syntrophic or competitive to study microbial cell to cell interactions, cell signaling and competition for resources. The microbial community was comprised of the metal-reducing Desulfovibrio vulgaris Hildenborough and Geobacter sulfurreducens PCA. Additionally, Methanococcus maripaludis S2 was added to study complete carbon reduction and maintain a low hydrogen partial pressure for syntrophism to occur. Further, considerable work has been published on D. vulgaris and the D. vulgaris/ Mc. maripaludis co-culture both with and without stress. We are extending this work by conducting the same stress conditions on the model community. Additionally, this comprehensive investigation includes physiological and metabolic analyses as well as specially designed mRNA microarrays with the genes for all three organisms on one slide so as to follow gene expression changes in the various cultivation conditions as well as being comparable to the co- and individual cultures. Further, state-of -the-art comprehensive AMT tag proteomics allows for these comparisons at the protein level for a systems biology assessment of a model, metal-reducing microbial community. Preliminary data revealed that lactate oxidation by D. vulgaris was sufficient to support both G. sulfurreducens and M. maripaludis via the excretion of H2 and acetate. Fumarate was utilized by G. sulfurreducens and reduced to succinate since neither of the other two organisms can reduce fumarate. Methane was quantified, suggesting acetate and H2 concentrations were sufficient for M. maripaludis. Steady state community cultivation will allow for

  9. Decarboxylation mechanisms in biological system.

    Science.gov (United States)

    Li, Tingfeng; Huo, Lu; Pulley, Christopher; Liu, Aimin

    2012-08-01

    This review examines the mechanisms propelling cofactor-independent, organic cofactor-dependent and metal-dependent decarboxylase chemistry. Decarboxylation, the removal of carbon dioxide from organic acids, is a fundamentally important reaction in biology. Numerous decarboxylase enzymes serve as key components of aerobic and anaerobic carbohydrate metabolism and amino acid conversion. In the past decade, our knowledge of the mechanisms enabling these crucial decarboxylase reactions has continued to expand and inspire. This review focuses on the organic cofactors biotin, flavin, NAD, pyridoxal 5'-phosphate, pyruvoyl, and thiamin pyrophosphate as catalytic centers. Significant attention is also placed on the metal-dependent decarboxylase mechanisms. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Network-Based Models in Molecular Biology

    Science.gov (United States)

    Beyer, Andreas

    Biological systems are characterized by a large number of diverse interactions. Interaction maps have been used to abstract those interactions at all biological scales ranging from food webs at the ecosystem level down to protein interaction networks at the molecular scale.

  11. 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...

  12. Computer Models and Automata Theory in Biology and Medicine

    CERN Document Server

    Baianu, I C

    2004-01-01

    The applications of computers to biological and biomedical problem solving goes back to the very beginnings of computer science, automata theory [1], and mathematical biology [2]. With the advent of more versatile and powerful computers, biological and biomedical applications of computers have proliferated so rapidly that it would be virtually impossible to compile a comprehensive review of all developments in this field. Limitations of computer simulations in biology have also come under close scrutiny, and claims have been made that biological systems have limited information processing power [3]. Such general conjectures do not, however, deter biologists and biomedical researchers from developing new computer applications in biology and medicine. Microprocessors are being widely employed in biological laboratories both for automatic data acquisition/processing and modeling; one particular area, which is of great biomedical interest, involves fast digital image processing and is already established for rout...

  13. Integrating interactive computational modeling in biology curricula.

    Directory of Open Access Journals (Sweden)

    Tomáš Helikar

    2015-03-01

    Full Text Available While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  14. Integrating interactive computational modeling in biology curricula.

    Science.gov (United States)

    Helikar, Tomáš; Cutucache, Christine E; Dahlquist, Lauren M; Herek, Tyler A; Larson, Joshua J; Rogers, Jim A

    2015-03-01

    While the use of computer tools to simulate complex processes such as computer circuits is normal practice in fields like engineering, the majority of life sciences/biological sciences courses continue to rely on the traditional textbook and memorization approach. To address this issue, we explored the use of the Cell Collective platform as a novel, interactive, and evolving pedagogical tool to foster student engagement, creativity, and higher-level thinking. Cell Collective is a Web-based platform used to create and simulate dynamical models of various biological processes. Students can create models of cells, diseases, or pathways themselves or explore existing models. This technology was implemented in both undergraduate and graduate courses as a pilot study to determine the feasibility of such software at the university level. First, a new (In Silico Biology) class was developed to enable students to learn biology by "building and breaking it" via computer models and their simulations. This class and technology also provide a non-intimidating way to incorporate mathematical and computational concepts into a class with students who have a limited mathematical background. Second, we used the technology to mediate the use of simulations and modeling modules as a learning tool for traditional biological concepts, such as T cell differentiation or cell cycle regulation, in existing biology courses. Results of this pilot application suggest that there is promise in the use of computational modeling and software tools such as Cell Collective to provide new teaching methods in biology and contribute to the implementation of the "Vision and Change" call to action in undergraduate biology education by providing a hands-on approach to biology.

  15. Cellular potts models multiscale extensions and biological applications

    CERN Document Server

    Scianna, Marco

    2013-01-01

    A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

  16. Redefining plant systems biology: from cell to ecosystem.

    Science.gov (United States)

    Keurentjes, Joost J B; Angenent, Gerco C; Dicke, Marcel; Dos Santos, Vítor A P Martins; Molenaar, Jaap; van der Putten, Wim H; de Ruiter, Peter C; Struik, Paul C; Thomma, Bart P H J

    2011-04-01

    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 agricultural productivity while decreasing the ecological footprint. This requires a holistic systems biology approach that couples different aggregation levels while considering the variables that affect these biological systems from cell to community. The challenge is to generate accurate experimental data that can be used together with modelling concepts and techniques that allow experimentally verifying in silico predictions. The coupling of aggregation levels in plant sciences, termed Integral Quantification of Biological Organization (IQ(BiO)), might enhance our abilities to generate new desired plant phenotypes. Copyright © 2010 Elsevier Ltd. All rights reserved.

  17. Modelling collagen diseases: STRUCTURAL BIOLOGY

    OpenAIRE

    Brodsky, Barbara; Baum, Jean

    2008-01-01

    Mutations in collagen lead to hereditary disorders such as brittle-bone disease. Peptide models for aberrant collagens are beginning to clarify how these amino-acid replacements lead to clinical problems.

  18. Setting Parameters for Biological Models With ANIMO

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran

    2014-01-01

    ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions

  19. 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...

  20. 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...

  1. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

  2. Structured population models in biology and epidemiology

    CERN Document Server

    Ruan, Shigui

    2008-01-01

    This book consists of six chapters written by leading researchers in mathematical biology. These chapters present recent and important developments in the study of structured population models in biology and epidemiology. Topics include population models structured by age, size, and spatial position; size-structured models for metapopulations, macroparasitc diseases, and prion proliferation; models for transmission of microparasites between host populations living on non-coincident spatial domains; spatiotemporal patterns of disease spread; method of aggregation of variables in population dynamics; and biofilm models. It is suitable as a textbook for a mathematical biology course or a summer school at the advanced undergraduate and graduate level. It can also serve as a reference book for researchers looking for either interesting and specific problems to work on or useful techniques and discussions of some particular problems.

  3. Recent introduction of an allodapine bee into Fiji: A new model system for understanding biological invasions by pollinators.

    Science.gov (United States)

    Groom, Scott V C; Tuiwawa, Marika V; Stevens, Mark I; Schwarz, Michael P

    2015-08-01

    Morphology-based studies have suggested a very depauperate bee fauna for islands in the South West Pacific, and recent genetic studies since have indicated an even smaller endemic fauna with many bee species in this region resulting from human-aided dispersal. These introduced species have the potential to both disrupt native pollinator suites as well as augment crop pollination, but for most species the timings of introduction are unknown. We examined the distribution and nesting biology of the long-tongued bee Braunsapis puangensis that was first recorded from Fiji in 2007. This bee has now become widespread in Fiji and both its local abundance and geographical range are likely to increase dramatically. The impacts of this invasion are potentially enormous for agriculture and native ecosystems, but they also provide opportunities for understanding how social insect species adapt to new environments. We outline the major issues associated with this recent invasion and argue that a long-term monitoring study is needed. © 2014 Institute of Zoology, Chinese Academy of Sciences.

  4. Applications of membrane computing in systems and synthetic biology

    CERN Document Server

    Gheorghe, Marian; Pérez-Jiménez, Mario

    2014-01-01

    Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying th...

  5. 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.

  6. Physiologically based kinetic modelling based prediction of oral systemic bioavailability of flavonoids, their metabolites, and their biological effects

    NARCIS (Netherlands)

    Boonpawa, Rungnapa

    2017-01-01

    Flavonoids, abundantly present in fruits and vegetables, have been reported to exert various positive health effects based on in vitro bioassays. However, effects detected in in vitro models cannot be directly correlated to human health as most in vitro studies have been performed using flavonoid

  7. Physiologically based kinetic modelling based prediction of oral systemic bioavailability of flavonoids, their metabolites, and their biological effects

    NARCIS (Netherlands)

    Boonpawa, Rungnapa

    2017-01-01

    Flavonoids, abundantly present in fruits and vegetables, have been reported to exert various positive health effects based on in vitro bioassays. However, effects detected in in vitro models cannot be directly correlated to human health as most in vitro studies have

  8. From the bush to the bench: the annual Nothobranchius fishes as a new model system in biology

    Czech Academy of Sciences Publication Activity Database

    Cellerino, A.; Valenzano, D. R.; Reichard, Martin

    2016-01-01

    Roč. 91, č. 2 (2016), s. 511-533 ISSN 1464-7931 R&D Projects: GA ČR(CZ) GAP506/11/0112 Institutional support: RVO:68081766 Keywords : ageing * longevity * killifish * annual fish * diapause * inbred lines * life -history traits * quantitative genetics * model species * senescence Subject RIV: EG - Zoology Impact factor: 11.615, year: 2016

  9. Laser interaction with biological material mathematical modeling

    CERN Document Server

    Kulikov, Kirill

    2014-01-01

    This book covers the principles of laser interaction with biological cells and tissues of varying degrees of organization. The problems of biomedical diagnostics are considered. Scattering of laser irradiation of blood cells is modeled for biological structures (dermis, epidermis, vascular plexus). An analytic theory is provided which is based on solving the wave equation for the electromagnetic field. It allows the accurate analysis of interference effects arising from the partial superposition of scattered waves. Treated topics of mathematical modeling are: optical characterization of biological tissue with large-scale and small-scale inhomogeneities in the layers, heating blood vessel under laser irradiation incident on the outer surface of the skin and thermo-chemical denaturation of biological structures at the example of human skin.

  10. Biological darkening of ice: measurements and models

    Science.gov (United States)

    Cook, J.; Tedstone, A.; Hodson, A. J.; Williamson, C.; McCutcheon, J.; Tranter, M.

    2017-12-01

    Biological growth occurs in the ablation zones of glaciers and ice sheets, resulting in a reduction of the ice albedo. Given the critical role of albedo in determining the surface energy balance - and therefore melt rate - of a mass of ice, understanding and quantifying biological albedo reduction is fundamental to predicting future ice dynamics. This may be particularly important on ablating ice on the western Greenland Ice Sheet, where a `dark ice zone' of varying spatial extent may be partly or mostly explained by biological growth. However, our ability to quantify and predict the contribution of biological impurities to the overall energy balance of glacial systems is currently limited by a lack of understanding of the mechanisms of biological darkening, difficulties in determining the spatial extent of biological impurities and uncertainty in isolating biological from non-biological albedo reduction. Here, new spectral measurements are presented for ice containing varying amounts of biological impurities which were obtained on the ground using a field spectrometer and from the air using a purpose built UAV on the Greenland Ice Sheet in summer 2016 and 2017. Distinctive spectral signatures are identified and used to map the spatial extent of algal blooms on the ice surface. A new radiative transfer scheme (BioSNICAR) for predicting the albedo of snow or ice discolored by microbial life is also described, offering insight into the mechanisms of biological darkening. Together, these demonstrate the critical role played by pigmented algae in darkening ice surfaces and provide a framework for predicting biological albedo reduction in future climate scenarios.

  11. Topological Data Analysis of Biological Aggregation Models

    Science.gov (United States)

    Topaz, Chad M.; Ziegelmeier, Lori; Halverson, Tom

    2015-01-01

    We apply tools from topological data analysis to two mathematical models inspired by biological aggregations such as bird flocks, fish schools, and insect swarms. Our data consists of numerical simulation output from the models of Vicsek and D'Orsogna. These models are dynamical systems describing the movement of agents who interact via alignment, attraction, and/or repulsion. Each simulation time frame is a point cloud in position-velocity space. We analyze the topological structure of these point clouds, interpreting the persistent homology by calculating the first few Betti numbers. These Betti numbers count connected components, topological circles, and trapped volumes present in the data. To interpret our results, we introduce a visualization that displays Betti numbers over simulation time and topological persistence scale. We compare our topological results to order parameters typically used to quantify the global behavior of aggregations, such as polarization and angular momentum. The topological calculations reveal events and structure not captured by the order parameters. PMID:25970184

  12. Notions of similarity for computational biology models

    KAUST Repository

    Waltemath, Dagmar

    2016-03-21

    Computational models used in biology are rapidly increasing in complexity, size, and numbers. To build such large models, researchers need to rely on software tools for model retrieval, model combination, and 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 introduce a general notion of quantitative model similarities, survey the use of existing model comparison methods in model building and management, and discuss potential applications of model comparison. To frame model comparison as a general problem, we describe a theoretical approach to defining and computing similarities based on different model aspects. Potentially relevant aspects of a model comprise its references to biological entities, network structure, mathematical equations and parameters, and dynamic behaviour. Future similarity measures could combine these model aspects in flexible, problem-specific ways in order to mimic users\\' intuition about model similarity, and to support complex model searches in databases.

  13. Modeling Biology Spanning Different Scales: An Open Challenge

    Directory of Open Access Journals (Sweden)

    Filippo Castiglione

    2014-01-01

    Full Text Available It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.

  14. 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.

  15. Mathematical aspects of pattern formation in biological systems

    CERN Document Server

    Wei, Juncheng

    2013-01-01

    This monograph is concerned with the mathematical analysis of patterns which are encountered in biological systems. It summarises, expands and relates results obtained in the field during the last fifteen years. It also links the results to biological applications and highlights their relevance to phenomena in nature. Of particular concern are large-amplitude patterns far from equilibrium in biologically relevant models.The approach adopted in the monograph is based on the following paradigms:• Examine the existence of spiky steady states in reaction-diffusion systems and select as observabl

  16. Systems Biology and Ecology of Streamlined Bacterioplankton

    Science.gov (United States)

    Giovannoni, S. J.

    2014-12-01

    complex questions hinge on translating gene frequencies into trait based ecological models that reflect the systems biology of cells.

  17. Integrative Systems Biology Visualization with MAYDAY

    Directory of Open Access Journals (Sweden)

    Symonsy Stephan

    2010-12-01

    Full Text Available Visualization is pivotal for gaining insight in systems biology data. As the size and complexity of datasets and supplemental information increases, an efficient, integrated framework for general and specialized views is necessary. MAYDAY is an application for analysis and visualization of general ‘omics’ data. It follows a trifold approach for data visualization, consisting of flexible data preprocessing, highly customizable data perspective plots for general purpose visualization and systems based plots. Here, we introduce two new systems biology visualization tools for MAYDAY. Efficiently implemented genomic viewers allow the display of variables associated with genomic locations. Multiple variables can be viewed using our new track-based ChromeTracks tool. A functional perspective is provided by visualizing metabolic pathways either in KEGG or BioPax format. Multiple options of displaying pathway components are available, including Systems Biology Graphical Notation (SBGN glyphs. Furthermore, pathways can be viewed together with gene expression data either as heatmaps or profiles.

  18. Setting Parameters for Biological Models With ANIMO

    Directory of Open Access Journals (Sweden)

    Stefano Schivo

    2014-03-01

    Full Text Available ANIMO (Analysis of Networks with Interactive MOdeling is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.

  19. Structural Systems Biology Evaluation of Metabolic Thermotolerance in Escherichia coli

    DEFF Research Database (Denmark)

    Chang, Roger L.; Andrews, Kathleen; Kim, Donghyuk

    2013-01-01

    Improve the System A "systems biology" approach may clarify, for example, how particular proteins determine sensitivity of bacteria to extremes of temperature. Chang et al. (p. 1220) integrated information on protein structure with a model of metabolism, thus associating the protein structure of ...

  20. Photosynthetic system as a biological functional element

    International Nuclear Information System (INIS)

    Zakhidov, E.A.; Zakhidova, M.A.; Kasymdzhanov, M.A.; Kurbanov, S.S.; Nematov, Sh.K.; Khabibullaev, P.K.

    2005-01-01

    Photosynthetic apparatus of high plants and photosynthetic bacteria is essentially autonomic system in terms of genetics and structural -functional properties located in specific medium, a bio-membrane. Processes of light absorption and exciton migration in light harvesting antenna, separation and further transfer of charges in reaction centers have specific features, which may be used for application of these objects as key elements in construction of future biological functional elements. Progress in study and genetic modification of photosynthetic membranes achieved during the last decade opens great prospects in development biological functional elements and systems. The main characteristics of photosynthetic system for these purposes are: (i) energy conversion processes in the first light phase of the photosynthesis have very short periods, up to picoseconds, which indicates possibility of creation of ultrafast functional elements on their basis; (ii) characteristics sizes of photosynthetic units, 10-100 nm, and possibility to arrange regularly disposed elements in relevant membranes could be prospective point for creation of nano structures and on their basis relevant biologic functional elements; (iii) elements based on modified photosynthetic apparatus and bio-membranes might be efficiently created by methods of gene engineering and manipulation, that open huge opportunities for development of read biological functional systems. In the paper structural-functional properties and characteristics of high plants and purple photosynthetic bacteria, which may be useful for creation of future biological functional elements are considered. (author)

  1. A dynamic model for functional mapping of biological rhythms.

    Science.gov (United States)

    Fu, Guifang; Luo, Jiangtao; Berg, Arthur; Wang, Zhong; Li, Jiahan; Das, Kiranmoy; Li, Runze; Wu, Rongling

    2011-01-01

    Functional mapping is a statistical method for mapping quantitative trait loci (QTLs) that regulate the dynamic pattern of a biological trait. This method integrates mathematical aspects of biological complexity into a mixture model for genetic mapping and tests the genetic effects of QTLs by comparing genotype-specific curve parameters. As a way of quantitatively specifying the dynamic behavior of a system, differential equations have proven to be powerful for modeling and unraveling the biochemical, molecular, and cellular mechanisms of a biological process, such as biological rhythms. The equipment of functional mapping with biologically meaningful differential equations provides new insights into the genetic control of any dynamic processes. We formulate a new functional mapping framework for a dynamic biological rhythm by incorporating a group of ordinary differential equations (ODE). The Runge-Kutta fourth order algorithm was implemented to estimate the parameters that define the system of ODE. The new model will find its implications for understanding the interplay between gene interactions and developmental pathways in complex biological rhythms.

  2. Toward mechanical systems biology in bone.

    Science.gov (United States)

    Trüssel, Andreas; Müller, Ralph; Webster, Duncan

    2012-11-01

    Cyclic mechanical loading is perhaps the most important physiological factor regulating bone mass and shape in a way which balances optimal strength with minimal weight. This bone adaptation process spans multiple length and time scales. Forces resulting from physiological exercise at the organ scale are sensed at the cellular scale by osteocytes, which reside inside the bone matrix. Via biochemical pathways, osteocytes orchestrate the local remodeling action of osteoblasts (bone formation) and osteoclasts (bone resorption). Together these local adaptive remodeling activities sum up to strengthen bone globally at the organ scale. To resolve the underlying mechanisms it is required to identify and quantify both cause and effect across the different scales. Progress has been made at the different scales experimentally. Computational models of bone adaptation have been developed to piece together various experimental observations at the different scales into coherent and plausible mechanisms. However additional quantitative experimental validation is still required to build upon the insights which have already been achieved. In this review we discuss emerging as well as state of the art experimental and computational techniques and how they might be used in a mechanical systems biology approach to further our understanding of the mechanisms governing load induced bone adaptation, i.e., ways are outlined in which experimental and computational approaches could be coupled, in a quantitative manner to create more reliable multiscale models of bone.

  3. Modelling biological pathway dynamics with Timed Automata

    NARCIS (Netherlands)

    Schivo, Stefano; Scholma, Jetse; Urquidi Camacho, R.A.; Wanders, B.; van der Vet, P.E.; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; van de Pol, Jan Cornelis; Post, Janine Nicole

    2012-01-01

    When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create

  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...... internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively...

  5. Heavy ion action on biological systems

    Energy Technology Data Exchange (ETDEWEB)

    Kiefer, J. [Giessen Univ. (Germany). Zentrum fuer Radiologie; Brend`amour, M. [Giessen Univ. (Germany). Zentrum fuer Radiologie; Stoll, U. [Giessen Univ. (Germany). Zentrum fuer Radiologie

    1996-02-01

    Life is governed by molecular processes, particularly involving the expression and conservation of genetic information. Heavy ions deposit large amount of energy at very small scale comparable to the essential molecular structures of biological systems. This paper illustrates the special aspects of heavy ion radiobiology from a fundamental point of view. After a short summary of the structure and function of biological systems, concentrating on the cell and its constituents, the pattern of energy deposition by heavy ions is discussed. Experimental examples are the induction of molecular changes in deoxyribonucleic acid, cell killing and the formation of mutations. It is shown that a close link exists between the physical parameters and the inactivation of biological functions that is not restricted to direct particle traversals but may also be brought about by the action of far-reaching secondary electrons. (orig.).

  6. Contemporary Phage Biology: From Classic Models to New Insights.

    Science.gov (United States)

    Ofir, Gal; Sorek, Rotem

    2018-03-08

    Bacteriophages, discovered about a century ago, have been pivotal as models for understanding the fundamental principles of molecular biology. While interest in phage biology declined after the phage "golden era," key recent developments, including advances in phage genomics, microscopy, and the discovery of the CRISPR-Cas anti-phage defense system, have sparked a renaissance in phage research in the past decade. This review highlights recently discovered unexpected complexities in phage biology, describes a new arsenal of phage genes that help them overcome bacterial defenses, and discusses advances toward documentation of the phage biodiversity on a global scale. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Systems biology of cellular membranes: a convergence with biophysics.

    Science.gov (United States)

    Chabanon, Morgan; Stachowiak, Jeanne C; Rangamani, Padmini

    2017-09-01

    Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  8. Optical Biosensors to Explore Biological Systems

    DEFF Research Database (Denmark)

    Palanco, Marta Espina; Mogensen, Klaus Bo; Andersen, Nils H. Skovgaard

    2016-01-01

    protein may be used as an efficient sensor in an organic environment via a biomimetic membrane model. The combination of both biomimetic membranes and protein membranes as a signal transduction medium has interesting applications in biology and medicine. It is crucial that the matrix where a protein...

  9. Systems Biology Model of Interactions Between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFbeta and ATM Signaling

    Energy Technology Data Exchange (ETDEWEB)

    O' Neill, Peter [University of Oxford; Anderson, Jennifer [University of Oxford

    2014-10-02

    The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently the transforming growth factor β (TGFβ) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low dose responses and cross-talk between the ATM and TGFβ pathways initiated by low and high LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to cross- talk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental

  10. Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling

    Energy Technology Data Exchange (ETDEWEB)

    Cucinotta, Francis A [Univ. of Nevada, Las Vegas, NV (United States)

    2016-09-01

    The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently, the transforming growth factor β (TGFβ) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses, and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low-dose responses and cross-talk between the ATM and TGFβ pathways initiated by low- and high-LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to crosstalk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental

  11. Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling

    International Nuclear Information System (INIS)

    Cucinotta, Francis A

    2016-01-01

    The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently, the transforming growth factor β (TGFβ) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses, and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low-dose responses and cross-talk between the ATM and TGFβ pathways initiated by low- and high-LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to crosstalk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental

  12. A SYSTEMIC VISION OF BIOLOGY: OVERCOMING LINEARITY

    Directory of Open Access Journals (Sweden)

    M. Mayer

    2005-07-01

    Full Text Available Many  authors have proposed  that contextualization of reality  is necessary  to teach  Biology, empha- sizing students´ social and  economic realities.   However, contextualization means  more than  this;  it is related  to working with  different kinds of phenomena  and/or objects  which enable  the  expression of scientific concepts.  Thus,  contextualization allows the integration of different contents.  Under this perspective,  the  objectives  of this  work were to articulate different  biology concepts  in order  to de- velop a systemic vision of biology; to establish  relationships with other areas of knowledge and to make concrete the  cell molecular  structure and organization as well as their  implications  on living beings´ environment, using  contextualization.  The  methodology  adopted  in this  work  was based  on three aspects:  interdisciplinarity, contextualization and development of competences,  using energy:  its flux and transformations as a thematic axis and  an approach  which allowed the  interconnection between different situations involving  these  concepts.   The  activities developed  were:  1.   dialectic exercise, involving a movement around  micro and macroscopic aspects,  by using questions  and activities,  sup- ported  by the use of alternative material  (as springs, candles on the energy, its forms, transformations and  implications  in the  biological way (microscopic  concepts;  2, Construction of molecular  models, approaching the concepts of atom,  chemical bonds and bond energy in molecules; 3. Observations de- veloped in Manguezal¨(mangrove swamp  ecosystem (Itapissuma, PE  were used to work macroscopic concepts  (as  diversity  and  classification  of plants  and  animals,  concerning  to  energy  flow through food chains and webs. A photograph register of all activities  along the course plus texts

  13. Radiological/biological/aerosol removal system

    Science.gov (United States)

    Haslam, Jeffery J

    2015-03-17

    An air filter replacement system for existing buildings, vehicles, arenas, and other enclosed airspaces includes a replacement air filter for replacing a standard air filter. The replacement air filter has dimensions and air flow specifications that allow it to replace the standard air filter. The replacement air filter includes a filter material that removes radiological or biological or aerosol particles.

  14. Studies on Semantic Systems Chemical Biology

    Science.gov (United States)

    Chen, Bin

    2012-01-01

    Current "one disease, one target and one drug" drug development paradigm is under question as relatively few drugs have reached the market in the last two decades. Increasingly research focus is being placed on the study of drug action against biological systems as a whole rather than against a single component (called "Systems…

  15. Modular microfluidic system for biological sample preparation

    Science.gov (United States)

    Rose, Klint A.; Mariella, Jr., Raymond P.; Bailey, Christopher G.; Ness, Kevin Dean

    2015-09-29

    A reconfigurable modular microfluidic system for preparation of a biological sample including a series of reconfigurable modules for automated sample preparation adapted to selectively include a) a microfluidic acoustic focusing filter module, b) a dielectrophoresis bacteria filter module, c) a dielectrophoresis virus filter module, d) an isotachophoresis nucleic acid filter module, e) a lyses module, and f) an isotachophoresis-based nucleic acid filter.

  16. Nutritional Systems Biology: Definitions and Approaches

    DEFF Research Database (Denmark)

    Panagiotou, Gianni; Nielsen, Jens

    2009-01-01

    waiting for a predictive knowledge of genetic variation. It is widely recognized that systems and network biology has the potential to increase our understanding of how nutrition influences metabolic pathways and homeostasis, how this regulation is disturbed in a diet-related disease, and to what extent...... individual genotypes contribute to such diseases....

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

    Indian Academy of Sciences (India)

    B J Rao

    2018-02-13

    Feb 13, 2018 ... triggering 'escape from homeostasis' (Nijhout et al. 2014) where phenotypes begin to become less stable and eventually turn into fully unstable state, the start of 'chaos' in a system. Therefore, the key to biological designs is to stay close to or within the 'homeostatic plateau' and resist drifting into 'chaos'.

  18. Notions of radiation chemistry in biological systems

    International Nuclear Information System (INIS)

    Mastro, N.L. del.

    1989-10-01

    The present paper examines some aspects of the direct and indirect biological radiation effects: pair formation, free radicals, superoxide ion, hydrogen peroxide, hydroxyl radical, oxygen singlet together with the endogen radioprotector mechanisms of organisms and the ways in which an improved radioresistance of biochemical systems can be achieved. (author) [pt

  19. Quantifying electron transfer reactions in biological systems

    DEFF Research Database (Denmark)

    Sjulstok, Emil Sjulstok; Olsen, Jógvan Magnus Haugaard; Solov'yov, Ilia A

    2015-01-01

    to deduce the driving force for the electron transfer reaction and to establish those interactions that play the major role in propelling the electron. The suggested approach is seen as a general recipe to treat electron transfer events in biological systems computationally, and we utilize it to describe...

  20. Micromechanics of engineered and biological systems

    Indian Academy of Sciences (India)

    Microsystems are good examples of integrated engineered systems of small size. Although this .... In develop- mental biology, the application of controlled forces on growing embryos is shown to help in under- standing ..... Optimization is a useful tool for synthesis. Many optimal synthesis methods have been developed for.

  1. Boolean Models of Biological Processes Explain Cascade-Like Behavior

    Science.gov (United States)

    Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

    2016-01-01

    Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either “on” or “off” and along with the molecules interact with each other, their individual status changes from “on” to “off” or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes. PMID:26821940

  2. 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.

  3. Cardiovascular Biology of the Incretin System

    Science.gov (United States)

    Ussher, John R.; Drucker, Daniel J.

    2012-01-01

    Glucagon-like peptide-1 (GLP-1) is an incretin hormone that enhances glucose-stimulated insulin secretion and exerts direct and indirect actions on the cardiovascular system. GLP-1 and its related incretin hormone, glucose-dependent insulinotropic polypeptide (GIP), are rapidly inactivated by the enzyme dipeptidyl peptidase 4 (DPP-4), a key determinant of incretin bioactivity. Two classes of medications that enhance incretin action, GLP-1R agonists and DPP-4 inhibitors, are used for the treatment of type 2 diabetes mellitus (T2DM). We review herein the cardiovascular biology of GLP-1R agonists and DPP-4 inhibitors, including direct and indirect effects on cardiomyocytes, blood vessels, adipocytes, the control of blood pressure and postprandial lipoprotein secretion. Both GLP-1R activation and DPP-4 inhibition exert multiple cardioprotective actions in preclinical models of cardiovascular dysfunction, and short term studies in human subjects appear to demonstrate modest yet beneficial actions on cardiac function in subjects with ischemic heart disease. Incretin-based agents control body weight, improve glycemic control with a low risk of hypoglycemia, decrease blood pressure, inhibit the secretion of intestinal chylomicrons, and reduce inflammation in preclinical studies. Nevertheless, there is limited information on the cardiovascular actions of these agents in patients with diabetes and established cardiovascular disease. Hence, a more complete understanding of the cardiovascular risk:benefit ratio of incretin-based therapies will require completion of long term cardiovascular outcome studies currently underway in patients with T2DM. PMID:22323472

  4. Visualizing dimensionality reduction of systems biology data

    OpenAIRE

    Lehrmann, Andreas; Huber, Michael; Polatkan, Aydin C.; Pritzkau, Albert; Nieselt, Kay

    2012-01-01

    One of the challenges in analyzing high-dimensional expression data is the detection of important biological signals. A common approach is to apply a dimension reduction method, such as principal component analysis. Typically, after application of such a method the data is projected and visualized in the new coordinate system, using scatter plots or profile plots. These methods provide good results if the data have certain properties which become visible in the new coordinate system and which...

  5. Removal of Antibiotics in Biological Wastewater Treatment Systems-A Critical Assessment Using the Activated Sludge Modeling Framework for Xenobiotics (ASM-X).

    Science.gov (United States)

    Polesel, Fabio; Andersen, Henrik R; Trapp, Stefan; Plósz, Benedek Gy

    2016-10-04

    Many scientific studies present removal efficiencies for pharmaceuticals in laboratory-, pilot-, and full-scale wastewater treatment plants, based on observations that may be impacted by theoretical and methodological approaches used. In this Critical Review, we evaluated factors influencing observed removal efficiencies of three antibiotics (sulfamethoxazole, ciprofloxacin, tetracycline) in pilot- and full-scale biological treatment systems. Factors assessed include (i) retransformation to parent pharmaceuticals from e.g., conjugated metabolites and analogues, (ii) solid retention time (SRT), (iii) fractions sorbed onto solids, and (iv) dynamics in influent and effluent loading. A recently developed methodology was used, relying on the comparison of removal efficiency predictions (obtained with the Activated Sludge Model for Xenobiotics (ASM-X)) with representative measured data from literature. By applying this methodology, we demonstrated that (a) the elimination of sulfamethoxazole may be significantly underestimated when not considering retransformation from conjugated metabolites, depending on the type (urban or hospital) and size of upstream catchments; (b) operation at extended SRT may enhance antibiotic removal, as shown for sulfamethoxazole; (c) not accounting for fractions sorbed in influent and effluent solids may cause slight underestimation of ciprofloxacin removal efficiency. Using tetracycline as example substance, we ultimately evaluated implications of effluent dynamics and retransformation on environmental exposure and risk prediction.

  6. Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

    OpenAIRE

    Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

    2012-01-01

    Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

  7. Standards, Data Exchange and Intellectual Property Rights in Systems Biology

    DEFF Research Database (Denmark)

    van Zimmeren, Esther; Rutz, Berthold; Minssen, Timo

    2016-01-01

    and qualitative data on biological processes and activities in much greater volumes, velocity, variety and veracity. The skilful integration of multiple heterogeneous data sets allows scientists to model and predict biological processes. SysBio’s interdisciplinary nature requires data, models and other research...... we provided a number of recommendations for a variety of stakeholders. The current article offers some deeper reflections about the interface between IPRs, standards and data exchange in Systems Biology resulting from an Expert Meeting funded by another ERA-Net, ERASysAPP. The meeting brought...... assets to be formatted and described in standard ways to enable exchange and reuse of high quality data. This allows a more effective utilisation of the enormous potential that rests in “big data” analysis. Finally, SysBio is often closely linked to or provides the foundation for Synthetic Biology (Syn...

  8. Scaling for Dynamical Systems in Biology.

    Science.gov (United States)

    Ledder, Glenn

    2017-11-01

    Asymptotic methods can greatly simplify the analysis of all but the simplest mathematical models and should therefore be commonplace in such biological areas as ecology and epidemiology. One essential difficulty that limits their use is that they can only be applied to a suitably scaled dimensionless version of the original dimensional model. Many books discuss nondimensionalization, but with little attention given to the problem of choosing the right scales and dimensionless parameters. In this paper, we illustrate the value of using asymptotics on a properly scaled dimensionless model, develop a set of guidelines that can be used to make good scaling choices, and offer advice for teaching these topics in differential equations or mathematical biology courses.

  9. Software that goes with the flow in systems biology

    Directory of Open Access Journals (Sweden)

    Le Novère Nicolas

    2010-11-01

    Full Text Available Abstract A recent article in BMC Bioinformatics describes new advances in workflow systems for computational modeling in systems biology. Such systems can accelerate, and improve the consistency of, modeling through automation not only at the simulation and results-production stages, but also at the model-generation stage. Their work is a harbinger of the next generation of more powerful software for systems biologists. See research article: http://www.biomedcentral.com/1471-2105/11/582/abstract/ Ever since the rise of systems biology at the end of the last century, mathematical representations of biological systems and their activities have flourished. They are being used to describe everything from biomolecular networks, such as gene regulation, metabolic processes and signaling pathways, at the lowest biological scales, to tissue growth and differentiation, drug effects, environmental interactions, and more. A very active area in the field has been the development of techniques that facilitate the construction, analysis and dissemination of computational models. The heterogeneous, distributed nature of most data resources today has increased not only the opportunities for, but also the difficulties of, developing software systems to support these tasks. The work by Li et al. 1 published in BMC Bioinformatics represents a promising evolutionary step forward in this area. They describe a workflow system - a visual software environment enabling a user to create a connected set of operations to be performed sequentially using seperate tools and resources. Their system uses third-party data resources accessible over the Internet to elaborate and parametrize (that is, assign parameter values to computational models in a semi-automated manner. In Li et al.'s work, the authors point towards a promising future for computational modeling and simultaneously highlight some of the difficulties that need to be overcome before we get there.

  10. Parameter estimation and model selection in computational biology.

    Directory of Open Access Journals (Sweden)

    Gabriele Lillacci

    2010-03-01

    Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.

  11. Institute for Multiscale Modeling of Biological Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham

    2009-12-26

    The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.

  12. Systems biology of vaccination in the elderly.

    Science.gov (United States)

    Duraisingham, Sai S; Rouphael, Nadine; Cavanagh, Mary M; Nakaya, Helder I; Goronzy, Jorg J; Pulendran, Bali

    2013-01-01

    Aging population demographics, combined with suboptimal vaccine responses in the elderly, make the improvement of vaccination strategies in the elderly a developing public health issue. The immune system changes with age, with innate and adaptive cell components becoming increasingly dysfunctional. As such, vaccine responses in the elderly are impaired in ways that differ depending on the type of vaccine (e.g., live attenuated, polysaccharide, conjugate, or subunit) and the mediators of protection (e.g., antibody and/or T cell). The rapidly progressing field of systems biology has been shown to be useful in predicting immunogenicity and offering insights into potential mechanisms of protection in young adults. Future application of systems biology to vaccination in the elderly may help to identify gene signatures that predict suboptimal responses and help to identify more accurate correlates of protection. Moreover, the identification of specific defects may be used to target novel vaccination strategies that improve efficacy in elderly populations.

  13. Measuring cell identity in noisy biological systems

    Science.gov (United States)

    Birnbaum, Kenneth D.; Kussell, Edo

    2011-01-01

    Global gene expression measurements are increasingly obtained as a function of cell type, spatial position within a tissue and other biologically meaningful coordinates. Such data should enable quantitative analysis of the cell-type specificity of gene expression, but such analyses can often be confounded by the presence of noise. We introduce a specificity measure Spec that quantifies the information in a gene's complete expression profile regarding any given cell type, and an uncertainty measure dSpec, which measures the effect of noise on specificity. Using global gene expression data from the mouse brain, plant root and human white blood cells, we show that Spec identifies genes with variable expression levels that are nonetheless highly specific of particular cell types. When samples from different individuals are used, dSpec measures genes’ transcriptional plasticity in each cell type. Our approach is broadly applicable to mapped gene expression measurements in stem cell biology, developmental biology, cancer biology and biomarker identification. As an example of such applications, we show that Spec identifies a new class of biomarkers, which exhibit variable expression without compromising specificity. The approach provides a unifying theoretical framework for quantifying specificity in the presence of noise, which is widely applicable across diverse biological systems. PMID:21803789

  14. The Chernobyl Tissue Bank — A Repository for Biomaterial and Data Used in Integrative and Systems Biology Modeling the Human Response to Radiation

    Science.gov (United States)

    Thomas, Geraldine; Unger, Kristian; Krznaric, Marko; Galpine, Angela; Bethel, Jackie; Tomlinson, Christopher; Woodbridge, Mark; Butcher, Sarah

    2012-01-01

    The only unequivocal radiological effect of the Chernobyl accident on human health is the increase in thyroid cancer in those exposed in childhood or early adolescence. In response to the scientific interest in studying the molecular biology of thyroid cancer post Chernobyl, the Chernobyl Tissue Bank (CTB: www.chernobyltissuebank.com) was established in 1998. Thus far it is has collected biological samples from 3,861 individuals, and provided 27 research projects with 11,254 samples. The CTB was designed from its outset as a resource to promote the integration of research and clinical data to facilitate a systems biology approach to radiation related thyroid cancer. The project has therefore developed as a multidisciplinary collaboration between clinicians, dosimetrists, molecular biologists and bioinformaticians and serves as a paradigm for tissue banking in the omics era. PMID:24704918

  15. Structural sensitivity of biological models revisited.

    Science.gov (United States)

    Cordoleani, Flora; Flora, Cordoleani; Nerini, David; David, Nerini; Gauduchon, Mathias; Mathias, Gauduchon; Morozov, Andrew; Andrew, Morozov; Poggiale, Jean-Christophe; Jean-Christophe, Poggiale

    2011-08-21

    Enhancing the predictive power of models in biology is a challenging issue. Among the major difficulties impeding model development and implementation are the sensitivity of outcomes to variations in model parameters, the problem of choosing of particular expressions for the parametrization of functional relations, and difficulties in validating models using laboratory data and/or field observations. In this paper, we revisit the phenomenon which is referred to as structural sensitivity of a model. Structural sensitivity arises as a result of the interplay between sensitivity of model outcomes to variations in parameters and sensitivity to the choice of model functions, and this can be somewhat of a bottleneck in improving the models predictive power. We provide a rigorous definition of structural sensitivity and we show how we can quantify the degree of sensitivity of a model based on the Hausdorff distance concept. We propose a simple semi-analytical test of structural sensitivity in an ODE modeling framework. Furthermore, we emphasize the importance of directly linking the variability of field/experimental data and model predictions, and we demonstrate a way of assessing the robustness of modeling predictions with respect to data sampling variability. As an insightful illustrative example, we test our sensitivity analysis methods on a chemostat predator-prey model, where we use laboratory data on the feeding of protozoa to parameterize the predator functional response. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Reaction of long-lived radicals and vitamin C in γ-irradiated mammalian cells and their model system at 295 K. Tunneling reaction in biological system

    International Nuclear Information System (INIS)

    Matsumoto, Takuro; Kumada, Takayuki; Kodama, Seiji; Watanabe, Masami

    1997-01-01

    When golden hamster embryo (GHE) cells or concentrated albumin solution (0.1 kg dm -3 ), that is a model system of cells, is irradiated with γ-rays at 295 K, organic radicals produced can be observed by ESR. The organic radicals survive at both 295 and 310 K for as long as 20 h. The long-lived radicals in GHE cells and the albumin solution react with vitamin C by the rate constants of 0.007 dm 3 mol -1 s -1 and 0.014 dm 3 mol -1 s -1 , respectively. The long-lived radicals in human cells cause gene mutation, which is suppressed by the addition of vitamin C. The isotope effect on the rate constant (κ) for the reaction of the long-lived radicals and vitamin C has been studied in the albumin solution by use of protonated vitamin C and deuterated vitamin C. The isotope effect (κ H /κ D ) was more than 20 ∼ 50 and was interpreted in terms of tunnelling reaction. (author)

  17. A Transformative Model for Undergraduate Quantitative Biology Education

    Science.gov (United States)

    Driscoll, Tobin A.; Dhurjati, Prasad; Pelesko, John A.; Rossi, Louis F.; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B.

    2010-01-01

    The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions. PMID:20810949

  18. A transformative model for undergraduate quantitative biology education.

    Science.gov (United States)

    Usher, David C; Driscoll, Tobin A; Dhurjati, Prasad; Pelesko, John A; Rossi, Louis F; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B

    2010-01-01

    The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions.

  19. 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.

  20. Glycoengineering in CHO cells: Advances in systems biology

    DEFF Research Database (Denmark)

    Tejwani, Vijay; Andersen, Mikael Rørdam; Nam, Jong Hyun

    2018-01-01

    are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling...

  1. Effects of Pesticides on Biological Systems

    Directory of Open Access Journals (Sweden)

    Ergul Belge Kurutas

    2003-06-01

    Full Text Available The use of pesticid both in Turkey and other contries is widespread in order to combat against many pests which cause economical damages. However, pesticides in human pass through skin, respiratory or digestive systems and is metabolized by monooxygenase system dependent upon cytocrome P450 in liver. They also give rise to severe decreases cytochrome P450 and amount of "hem" enzyme activites of glucose-6-phosphatase, pyrophosphatase by stimulating lipid peroxidation on hepatic microsomes. In this study effects of pesticides on biological systems will be presented in genaral terms. [Archives Medical Review Journal 2003; 12(3.000: 215-228

  2. ISBE – set out for a Systems Biology Infrastructure for Europe

    NARCIS (Netherlands)

    Hollmann, S.; Martins dos Santos, V.A.P.; Regierer, Babette

    2013-01-01

    Systems biology requires the availability, co-ordination and simultaneous interaction of a large number of diverse facilities and activities. These cover an entire spectrum, from mathematical modelling, through biological, biomedical and clinical experiments, to dedicated technology development. The

  3. Radionuclide Imaging Technologies for Biological Systems

    Energy Technology Data Exchange (ETDEWEB)

    Howell, Calvin R. [Duke Univ., Durham, NC (United States); Reid, Chantal D. [Duke Univ., Durham, NC (United States); Weisenberger, Andrew G. [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2014-05-14

    The main objective of this project is to develop technologies and experimental techniques for studying the dynamics of physiological responses of plants to changes in their interface with the local environment and to educate a new generation of scientists in an interdisciplinary environment of biology, physics and engineering. Also an important goal is to perform measurements to demonstrate the new data that can be produced and made available to the plant-biology community using the imaging technologies and experimental techniques developed in this project. The study of the plant-environment interface includes a wide range of topics in plant physiology, e.g., the root-soil interface, resource availability, impact of herbivores, influence of microbes on root surface, and responses to toxins in the air and soil. The initial scientific motivation for our work is to improve understanding of the mechanisms for physiological responses to abrupt changes in the local environment, in particular, the responses that result in short-term adjustments in resource (e.g., sugars, nutrients and water) allocations. Data of time-dependent responses of plants to environmental changes are essential in developing mechanistic models for substance intake and resource allocation. Our approach is to use radioisotope tracing techniques to study whole-plant and plant organ (e.g., leaves, stems, roots) dynamical responses to abrupt changes in environmental conditions such as concentration of CO2 in the atmosphere, nutrient availability and lighting. To this aim we are collaborating with the Radiation Detector and Imaging Group at the Thomas Jefferson National Laboratory Facility (JLab) to develop gamma-ray and beta particle imaging systems optimized for plant studies. The radioisotope tracing measurements are conducted at the Phytotron facility at Duke University. The Phytotron is a controlled environment plant research facility with a variety of plant growth chambers. One chamber

  4. Optoelectronic system and apparatus for connection to biological systems

    Energy Technology Data Exchange (ETDEWEB)

    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.

  5. Engineering plant metabolism into microbes: from systems biology to synthetic biology.

    Science.gov (United States)

    Xu, Peng; Bhan, Namita; Koffas, Mattheos A G

    2013-04-01

    Plant metabolism represents an enormous repository of compounds that are of pharmaceutical and biotechnological importance. Engineering plant metabolism into microbes will provide sustainable solutions to produce pharmaceutical and fuel molecules that could one day replace substantial portions of the current fossil-fuel based economy. Metabolic engineering entails targeted manipulation of biosynthetic pathways to maximize yields of desired products. Recent advances in Systems Biology and the emergence of Synthetic Biology have accelerated our ability to design, construct and optimize cell factories for metabolic engineering applications. Progress in predicting and modeling genome-scale metabolic networks, versatile gene assembly platforms and delicate synthetic pathway optimization strategies has provided us exciting opportunities to exploit the full potential of cell metabolism. In this review, we will discuss how systems and synthetic biology tools can be integrated to create tailor-made cell factories for efficient production of natural products and fuel molecules in microorganisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Two classes of bipartite networks: nested biological and social systems.

    Science.gov (United States)

    Burgos, Enrique; Ceva, Horacio; Hernández, Laura; Perazzo, R P J; Devoto, Mariano; Medan, Diego

    2008-10-01

    Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

  7. Nutritional systems biology of type 2 diabetes

    OpenAIRE

    Zhao, Y; Barrere-Cain, RE; Yang, X

    2015-01-01

    © 2015, The Author(s). Type 2 diabetes (T2D) has become an increasingly challenging health burden due to its high morbidity, mortality, and heightened prevalence worldwide. Although dietary and nutritional imbalances have long been recognized as key risk factors for T2D, the underlying mechanisms remain unclear. The advent of nutritional systems biology, a field that aims to elucidate the interactions between dietary nutrients and endogenous molecular entities in disease-related tissues, offe...

  8. Bifurcations of a class of singular biological economic models

    International Nuclear Information System (INIS)

    Zhang Xue; Zhang Qingling; Zhang Yue

    2009-01-01

    This paper studies systematically a prey-predator singular biological economic model with time delay. It shows that this model exhibits two bifurcation phenomena when the economic profit is zero. One is transcritical bifurcation which changes the stability of the system, and the other is singular induced bifurcation which indicates that zero economic profit brings impulse, i.e., rapid expansion of the population in biological explanation. On the other hand, if the economic profit is positive, at a critical value of bifurcation parameter, the system undergoes a Hopf bifurcation, i.e., the increase of delay destabilizes the system and bifurcates into small amplitude periodic solution. Finally, by using Matlab software, numerical simulations illustrate the effectiveness of the results obtained here. In addition, we study numerically that the system undergoes a saddle-node bifurcation when the bifurcation parameter goes through critical value of positive economic profit.

  9. Cancer systems biology: signal processing for cancer research

    Science.gov (United States)

    Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

    2011-01-01

    In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

  10. 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.

  11. 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 ...

  12. Unit testing, model validation, and biological simulation.

    Science.gov (United States)

    Sarma, Gopal P; Jacobs, Travis W; Watts, Mark D; Ghayoomie, S Vahid; Larson, Stephen D; Gerkin, Richard C

    2016-01-01

    The growth of the software industry has gone hand in hand with the development of tools and cultural practices for ensuring the reliability of complex pieces of software. These tools and practices are now acknowledged to be essential to the management of modern software. As computational models and methods have become increasingly common in the biological sciences, it is important to examine how these practices can accelerate biological software development and improve research quality. In this article, we give a focused case study of our experience with the practices of unit testing and test-driven development in OpenWorm, an open-science project aimed at modeling Caenorhabditis elegans. We identify and discuss the challenges of incorporating test-driven development into a heterogeneous, data-driven project, as well as the role of model validation tests, a category of tests unique to software which expresses scientific models.

  13. 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.

  14. Synthetic and systems biology for microbial production of commodity chemicals.

    Science.gov (United States)

    Chubukov, Victor; Mukhopadhyay, Aindrila; Petzold, Christopher J; Keasling, Jay D; Martín, Héctor García

    2016-01-01

    The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

  15. Engineering biological systems toward a sustainable bioeconomy.

    Science.gov (United States)

    Lopes, Mateus Schreiner Garcez

    2015-06-01

    The nature of our major global risks calls for sustainable innovations to decouple economic growth from greenhouse gases emission. The development of sustainable technologies has been negatively impacted by several factors including sugar production costs, production scale, economic crises, hydraulic fracking development and the market inability to capture externality costs. However, advances in engineering of biological systems allow bridging the gap between exponential growth of knowledge about biology and the creation of sustainable value chains for a broad range of economic sectors. Additionally, industrial symbiosis of different biobased technologies can increase competitiveness and sustainability, leading to the development of eco-industrial parks. Reliable policies for carbon pricing and revenue reinvestments in disruptive technologies and in the deployment of eco-industrial parks could boost the welfare while addressing our major global risks toward the transition from a fossil to a biobased economy.

  16. Biological Therapy in Systemic Lupus Erythematosus

    Directory of Open Access Journals (Sweden)

    Mariana Postal

    2012-01-01

    Full Text Available Systemic lupus erythematosus (SLE is a prototypic inflammatory autoimmune disorder characterized by multisystem involvement and fluctuating disease activity. Symptoms range from rather mild manifestations such as rash or arthritis to life-threatening end-organ manifestations. Despite new and improved therapy having positively impacted the prognosis of SLE, a subgroup of patients do not respond to conventional therapy. Moreover, the risk of fatal outcomes and the damaging side effects of immunosuppressive therapies in SLE call for an improvement in the current therapeutic management. New therapeutic approaches are focused on B-cell targets, T-cell downregulation and costimulatory blockade, cytokine inhibition, and the modulation of complement. Several biological agents have been developed, but this encouraging news is associated with several disappointments in trials and provide a timely moment to reflect on biologic therapy in SLE.

  17. Adaptable data management for systems biology investigations

    Directory of Open Access Journals (Sweden)

    Burdick David

    2009-03-01

    Full Text Available Abstract Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry. We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.

  18. Adaptable data management for systems biology investigations

    Science.gov (United States)

    Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

    2009-01-01

    Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community. PMID:19265554

  19. 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.

  20. Specifications of Standards in Systems and Synthetic Biology.

    Science.gov (United States)

    Schreiber, Falk; Bader, Gary D; Golebiewski, Martin; Hucka, Michael; Kormeier, Benjamin; Le Novère, Nicolas; Myers, Chris; Nickerson, David; Sommer, Björn; Waltemath, Dagmar; Weise, Stephan

    2015-09-04

    Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation). Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/. So far the different standards were published and made accessible through the standards’ web- pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.

  1. Spherical Cancer Models in Tumor Biology

    Directory of Open Access Journals (Sweden)

    Louis-Bastien Weiswald

    2015-01-01

    Full Text Available Three-dimensional (3D in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type.

  2. Spherical cancer models in tumor biology.

    Science.gov (United States)

    Weiswald, Louis-Bastien; Bellet, Dominique; Dangles-Marie, Virginie

    2015-01-01

    Three-dimensional (3D) in vitro models have been used in cancer research as an intermediate model between in vitro cancer cell line cultures and in vivo tumor. Spherical cancer models represent major 3D in vitro models that have been described over the past 4 decades. These models have gained popularity in cancer stem cell research using tumorospheres. Thus, it is crucial to define and clarify the different spherical cancer models thus far described. Here, we focus on in vitro multicellular spheres used in cancer research. All these spherelike structures are characterized by their well-rounded shape, the presence of cancer cells, and their capacity to be maintained as free-floating cultures. We propose a rational classification of the four most commonly used spherical cancer models in cancer research based on culture methods for obtaining them and on subsequent differences in sphere biology: the multicellular tumor spheroid model, first described in the early 70s and obtained by culture of cancer cell lines under nonadherent conditions; tumorospheres, a model of cancer stem cell expansion established in a serum-free medium supplemented with growth factors; tissue-derived tumor spheres and organotypic multicellular spheroids, obtained by tumor tissue mechanical dissociation and cutting. In addition, we describe their applications to and interest in cancer research; in particular, we describe their contribution to chemoresistance, radioresistance, tumorigenicity, and invasion and migration studies. Although these models share a common 3D conformation, each displays its own intrinsic properties. Therefore, the most relevant spherical cancer model must be carefully selected, as a function of the study aim and cancer type. Copyright © 2014 Neoplasia Press, Inc. Published by Elsevier Inc. All rights reserved.

  3. 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...

  4. Integrative biological simulation praxis: Considerations from physics, philosophy, and data/model curation practices

    OpenAIRE

    Sarma, Gopal P.; Faundez, Victor

    2017-01-01

    ABSTRACT Integrative biological simulations have a varied and controversial history in the biological sciences. From computational models of organelles, cells, and simple organisms, to physiological models of tissues, organ systems, and ecosystems, a diverse array of biological systems have been the target of large-scale computational modeling efforts. Nonetheless, these research agendas have yet to prove decisively their value among the broader community of theoretical and experimental biolo...

  5. 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…

  6. Multiscale mechanical modeling of soft biological tissues

    Science.gov (United States)

    Stylianopoulos, Triantafyllos

    2008-10-01

    Soft biological tissues include both native and artificial tissues. In the human body, tissues like the articular cartilage, arterial wall, and heart valve leaflets are examples of structures composed of an underlying network of collagen fibers, cells, proteins and molecules. Artificial tissues are less complex than native tissues and mainly consist of a fiber polymer network with the intent of replacing lost or damaged tissue. Understanding of the mechanical function of these materials is essential for many clinical treatments (e.g. arterial clamping, angioplasty), diseases (e.g. arteriosclerosis) and tissue engineering applications (e.g. engineered blood vessels or heart valves). This thesis presents the derivation and application of a multiscale methodology to describe the macroscopic mechanical function of soft biological tissues incorporating directly their structural architecture. The model, which is based on volume averaging theory, accounts for structural parameters such as the network volume fraction and orientation, the realignment of the fibers in response to strain, the interactions among the fibers and the interactions between the fibers and the interstitial fluid in order to predict the overall tissue behavior. Therefore, instead of using a constitutive equation to relate strain to stress, the tissue microstructure is modeled within a representative volume element (RVE) and the macroscopic response at any point in the tissue is determined by solving a micromechanics problem in the RVE. The model was applied successfully to acellular collagen gels, native blood vessels, and electrospun polyurethane scaffolds and provided accurate predictions for permeability calculations in isotropic and oriented fiber networks. The agreement of model predictions with experimentally determined mechanical properties provided insights into the mechanics of tissues and tissue constructs, while discrepancies revealed limitations of the model framework.

  7. System for determining sizes of biological macromolecules

    International Nuclear Information System (INIS)

    Nelson, R.M.; Danby, P.C.

    1987-01-01

    An electrophoresis system for determining the sizes of radiolabelled biological macromolecules is described. It comprises a cell containing an electrophoresis gel and having at least one lane, a voltage source connected across the gel for effecting the movement of macromolecules in the lane, a detector fixed relative to the moving molecules for generating electrical pulses responsive to signals emitted by the radiolabelled molecules; a pulse processor for counting the pulse rate, and a computational device for comparing the pulse rate to a predetermined value. (author)

  8. Integrative Systems Biology Applied to Toxicology

    DEFF Research Database (Denmark)

    Kongsbak, Kristine Grønning

    associated with combined exposure to multiple chemicals. Testing all possible combinations of the tens of thousands environmental chemicals is impractical. This PhD project was launched to apply existing computational systems biology methods to toxicological research. In this thesis, I present in three...... projects three different approaches to using computational toxicology to aid classical toxicological investigations. In project I, we predicted human health effects of five pesticides using publicly available data. We obtained a grouping of the chemical according to their potential human health effects...

  9. Applying systems biology methods to the study of human physiology in extreme environments

    OpenAIRE

    Edwards, Lindsay M; Thiele, Ines

    2013-01-01

    Systems biology is defined in this review as ‘an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems’. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is e...

  10. Preservice Biology Teachers' Conceptions About the Tentative Nature of Theories and Models in Biology

    Science.gov (United States)

    Reinisch, Bianca; Krüger, Dirk

    2018-02-01

    In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers ( N = 10) were asked about their understanding of theories and models. They were requested to give reasons why they see theories and models as either tentative or certain constructs. Their conceptions were then compared to philosophers' positions (e.g., Popper, Giere). A category system was developed from the qualitative content analysis of the interviews. These categories include 16 conceptions for theories ( n tentative = 11; n certai n = 5) and 18 conceptions for models ( n tentative = 10; n certain = 8). The analysis of the interviews showed that the preservice teachers gave reasons for the tentativeness or certainty of theories and models either due to their understanding of the terms or due to their understanding of the generation or evaluation of theories and models. Therefore, a variety of different terminology, from different sources, should be used in learning-teaching situations. Additionally, an understanding of which processes lead to the generation, evaluation, and refinement or rejection of theories and models should be discussed with preservice teachers. Within philosophy of science, there has been a shift from theories to models. This should be transferred to educational contexts by firstly highlighting the role of models and also their connections to theories.

  11. Preface: the hydra model system.

    Science.gov (United States)

    Galliot, Brigitte

    2012-01-01

    The freshwater Hydra polyp emerged as a model system in 1741 when Abraham Trembley not only discovered its amazing regenerative potential, but also demonstrated that experimental manipulations pave the way to research in biology. Since then, Hydra flourished as a potent and fruitful model system to help answer questions linked to cell and developmental biology, as such as the setting up of an organizer to regenerate a complex missing structure, the establishment and maintainance of polarity in a multicellular organism, the development of mathematical models to explain the robust developmental rules observed in this animal, the maintainance of stemness and multipotency in a highly dynamic environment, the plasticity of differentiated cells, to name but a few. However the Hydra model system is not restricted to cell and developmental biology; during the past 270 years it has also been heavily used to investigate the relationships between Hydra and its environment, opening new horizons concerning neurophysiology, innate immunity, ecosystems, ecotoxicology, symbiosis...

  12. Documentation of TRU biological transport model (BIOTRAN)

    International Nuclear Information System (INIS)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text

  13. Documentation of TRU biological transport model (BIOTRAN)

    Energy Technology Data Exchange (ETDEWEB)

    Gallegos, A.F.; Garcia, B.J.; Sutton, C.M.

    1980-01-01

    Inclusive of Appendices, this document describes the purpose, rationale, construction, and operation of a biological transport model (BIOTRAN). This model is used to predict the flow of transuranic elements (TRU) through specified plant and animal environments using biomass as a vector. The appendices are: (A) Flows of moisture, biomass, and TRU; (B) Intermediate variables affecting flows; (C) Mnemonic equivalents (code) for variables; (D) Variable library (code); (E) BIOTRAN code (Fortran); (F) Plants simulated; (G) BIOTRAN code documentation; (H) Operating instructions for BIOTRAN code. The main text is presented with a specific format which uses a minimum of space, yet is adequate for tracking most relationships from their first appearance to their formulation in the code. Because relationships are treated individually in this manner, and rely heavily on Appendix material for understanding, it is advised that the reader familiarize himself with these materials before proceeding with the main text.

  14. ACTIVE AND PARTICIPATORY METHODS IN BIOLOGY: MODELING

    Directory of Open Access Journals (Sweden)

    Brînduşa-Antonela SBÎRCEA

    2011-01-01

    Full Text Available By using active and participatory methods it is hoped that pupils will not only come to a deeper understanding of the issues involved, but also that their motivation will be heightened. Pupil involvement in their learning is essential. Moreover, by using a variety of teaching techniques, we can help students make sense of the world in different ways, increasing the likelihood that they will develop a conceptual understanding. The teacher must be a good facilitator, monitoring and supporting group dynamics. Modeling is an instructional strategy in which the teacher demonstrates a new concept or approach to learning and pupils learn by observing. In the teaching of biology the didactic materials are fundamental tools in the teaching-learning process. Reading about scientific concepts or having a teacher explain them is not enough. Research has shown that modeling can be used across disciplines and in all grade and ability level classrooms. Using this type of instruction, teachers encourage learning.

  15. Link between truncated fractals and coupled oscillators in biological systems.

    Science.gov (United States)

    Paar, V; Pavin, N; Rosandić, M

    2001-09-07

    This article aims at providing a new theoretical insight into the fundamental question of the origin of truncated fractals in biological systems. It is well known that fractal geometry is one of the characteristics of living organisms. However, contrary to mathematical fractals which are self-similar at all scales, the biological fractals are truncated, i.e. their self-similarity extends at most over a few orders of magnitude of separation. We show that nonlinear coupled oscillators, modeling one of the basic features of biological systems, may generate truncated fractals: a truncated fractal pattern for basin boundaries appears in a simple mathematical model of two coupled nonlinear oscillators with weak dissipation. This fractal pattern can be considered as a particular hidden fractal property. At the level of sufficiently fine precision technique the truncated fractality acts as a simple structure, leading to predictability, but at a lower level of precision it is effectively fractal, limiting the predictability of the long-term behavior of biological systems. We point out to the generic nature of our result. Copyright 2001 Academic Press.

  16. 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

  17. AN INTEGRATED BIOLOGICAL CONTROL SYSTEM AT HANFORD

    Energy Technology Data Exchange (ETDEWEB)

    JOHNSON AR; CAUDILL JG; GIDDINGS RF; RODRIGUEZ JM; ROOS RC; WILDE JW

    2010-02-11

    In 1999 an integrated biological control system was instituted at the U.S. Department of Energy's Hanford Site. Successes and changes to the program needed to be communicated to a large and diverse mix of organizations and individuals. Efforts at communication are directed toward the following: Hanford Contractors (Liquid or Tank Waste, Solid Waste, Environmental Restoration, Science and Technology, Site Infrastructure), General Hanford Employees, and Hanford Advisory Board (Native American Tribes, Environmental Groups, Local Citizens, Washington State and Oregon State regulatory agencies). Communication was done through direct interface meetings, individual communication, where appropriate, and broadly sharing program reports. The objectives of the communication efforts was to have the program well coordinated with Hanford contractors, and to have the program understood well enough that all stakeholders would have confidence in the work performed by the program to reduce or elimated spread of radioactive contamination by biotic vectors. Communication of successes and changes to an integrated biological control system instituted in 1999 at the Department of Energy's Hanford Site have required regular interfaces with not only a diverse group of Hanford contractors (i.e., those responsible for liquid or tank waste, solid wastes, environmental restoration, science and technology, and site infrastructure), and general Hanford employees, but also with a consortium of designated stake holders organized as the Hanford Advisory Board (i.e., Native American tribes, various environmental groups, local citizens, Washington state and Oregon regulatory agencies, etc.). Direct interface meetings, individual communication where appropriate, and transparency of the biological control program were the methods and outcome of this effort.

  18. An Integrated Biological Control System At Hanford

    International Nuclear Information System (INIS)

    Johnson, A.R.; Caudill, J.G.; Giddings, R.F.; Rodriguez, J.M.; Roos, R.C.; Wilde, J.W.

    2010-01-01

    In 1999 an integrated biological control system was instituted at the U.S. Department of Energy's Hanford Site. Successes and changes to the program needed to be communicated to a large and diverse mix of organizations and individuals. Efforts at communication are directed toward the following: Hanford Contractors (Liquid or Tank Waste, Solid Waste, Environmental Restoration, Science and Technology, Site Infrastructure), General Hanford Employees, and Hanford Advisory Board (Native American Tribes, Environmental Groups, Local Citizens, Washington State and Oregon State regulatory agencies). Communication was done through direct interface meetings, individual communication, where appropriate, and broadly sharing program reports. The objectives of the communication efforts was to have the program well coordinated with Hanford contractors, and to have the program understood well enough that all stakeholders would have confidence in the work performed by the program to reduce or elimate spread of radioactive contamination by biotic vectors. Communication of successes and changes to an integrated biological control system instituted in 1999 at the Department of Energy's Hanford Site have required regular interfaces with not only a diverse group of Hanford contractors (i.e., those responsible for liquid or tank waste, solid wastes, environmental restoration, science and technology, and site infrastructure), and general Hanford employees, but also with a consortium of designated stake holders organized as the Hanford Advisory Board (i.e., Native American tribes, various environmental groups, local citizens, Washington state and Oregon regulatory agencies, etc.). Direct interface meetings, individual communication where appropriate, and transparency of the biological control program were the methods and outcome of this effort.

  19. 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

    2018-02-27

    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.

  20. 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...

  1. 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...... 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....

  2. Biological Systems for Hydrogen Photoproduction (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Ghirardi, M. L.

    2012-05-01

    This presentation summarizes NREL biological systems for hydrogen photoproduction work for the DOE Hydrogen and Fuel Cells Program Annual Merit Review and Peer Evaluation Meeting, May 14-18, 2012. General goal is develop photobiological systems for large-scale, low cost and efficient H{sub 2} production from water (barriers AH, AI and AJ). Specific tasks are: (1) Address the O{sub 2} sensitivity of hydrogenases that prevent continuity of H{sub 2} photoproduction under aerobic, high solar-to-hydrogen (STH) light conversion efficiency conditions; and (2) Utilize a limited STH H{sub 2}-producing method (sulfur deprivation) as a platform to address or test other factors limiting commercial algal H{sub 2} photoproduction, including low rates due to biochemical and engineering mechanisms.

  3. Microbial stress tolerance for biofuels. Systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Zonglin Lewis (ed.) [National Center for Agricultural Utilization Research, USDA-ARS, Peoria, IL (United States)

    2012-07-01

    The development of sustainable and renewable biofuels is attracting growing interest. It is vital to develop robust microbial strains for biocatalysts that are able to function under multiple stress conditions. This Microbiology Monograph provides an overview of methods for studying microbial stress tolerance for biofuels applications using a systems biology approach. Topics covered range from mechanisms to methodology for yeast and bacteria, including the genomics of yeast tolerance and detoxification; genetics and regulation of glycogen and trehalose metabolism; programmed cell death; high gravity fermentations; ethanol tolerance; improving biomass sugar utilization by engineered Saccharomyces; the genomics on tolerance of Zymomonas mobilis; microbial solvent tolerance; control of stress tolerance in bacterial host organisms; metabolomics for ethanologenic yeast; automated proteomics work cell systems for strain improvement; and unification of gene expression data for comparable analyses under stress conditions. (orig.)

  4. Invertebrates as model organisms for research on aging biology.

    Science.gov (United States)

    Murthy, Mahadev; Ram, Jeffrey L

    2015-01-30

    Invertebrate model systems, such as nematodes and fruit flies, have provided valuable information about the genetics and cellular biology involved in aging. However, limitations of these simple, genetically tractable organisms suggest the need for other model systems, some of them invertebrate, to facilitate further advances in the understanding of mechanisms of aging and longevity in mammals, including humans. This paper introduces 10 review articles about the use of invertebrate model systems for the study of aging by authors who participated in an 'NIA-NIH symposium on aging in invertebrate model systems' at the 2013 International Congress for Invertebrate Reproduction and Development. In contrast to the highly derived characteristics of nematodes and fruit flies as members of the superphylum Ecdysozoa, cnidarians, such as Hydra, are more 'basal' organisms that have a greater number of genetic orthologs in common with humans. Moreover, some other new model systems, such as the urochordate Botryllus schlosseri , the tunicate Ciona , and the sea urchins (Echinodermata) are members of the Deuterostomia, the same superphylum that includes all vertebrates, and thus have mechanisms that are likely to be more closely related to those occurring in humans. Additional characteristics of these new model systems, such as the recent development of new molecular and genetic tools and a more similar pattern to humans of regeneration and stem cell function suggest that these new model systems may have unique advantages for the study of mechanisms of aging and longevity.

  5. Systems biology approaches and pathway tools for investigating cardiovascular disease

    NARCIS (Netherlands)

    Wheelock, C.E.; Wheelock, A.M.; Kawashima, S.; Diez, D.; Kanehisa, M.; Erk, M. van; Kleemann, R.; Haeggström, J.Z.; Goto, S.

    2009-01-01

    Systems biology aims to understand the nonlinear interactions of multiple biomolecular components that characterize a living organism. One important aspect of systems biology approaches is to identify the biological pathways or networks that connect the differing elements of a system, and examine

  6. Promoting Systems Thinking through Biology Lessons

    Science.gov (United States)

    Riess, Werner; Mischo, Christoph

    2010-04-01

    This study's goal was to analyze various teaching approaches within the context of natural science lessons, especially in biology. The main focus of the paper lies on the effectiveness of different teaching methods in promoting systems thinking in the field of Education for Sustainable Development. The following methods were incorporated into the study: special lessons designed to promote systems thinking, a computer-simulated scenario on the topic "ecosystem forest," and a combination of both special lessons and the computer simulation. These groups were then compared to a control group. A questionnaire was used to assess systems thinking skills of 424 sixth-grade students of secondary schools in Germany. The assessment differentiated between a conceptual understanding (measured as achievement score) and a reflexive justification (measured as justification score) of systems thinking. The following control variables were used: logical thinking, grades in school, memory span, and motivational goal orientation. Based on the pretest-posttest control group design, only those students who received both special instruction and worked with the computer simulation showed a significant increase in their achievement scores. The justification score increased in the computer simulation condition as well as in the combination of computer simulation and lesson condition. The possibilities and limits of promoting various forms of systems thinking by using realistic computer simulations are discussed.

  7. Molecular profiles to biology and pathways: a systems biology approach.

    Science.gov (United States)

    Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

    2016-06-16

    Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

  8. Behaviors of tritium in terrestrial biological system

    International Nuclear Information System (INIS)

    Inomata, Tsuyako

    1983-01-01

    The in vivo behaviors of HTO- 3 H in food chain models in experimental animals were described. Of pregnant mice that had ingested HTO and drinking water alone for 19 days, the total 3 H content in the tissue/wet weight was greater by 20% in fetuses and newborns than in mothers, and the proportion of tissue-bound 3 H was 8-24% in mothers and 3% in fetuses. The mean 3 H concentration in the free water in tissues was about 36% of ingested HTO. When only 3 H foods were ingested for 18 days, the total 3 H content in the tissue/wet weight showed no marked difference among the mother, fetuses and newborns, nor did the bound 3 H level show great differences. With respect to the tissue distribution of 3 H, only the incorporation rate by the mother's brain from HTO was satisfactory, whereas in other organs, the mother, fetuses and newborns showed higher incorporation rates from 3 H foods. The ratio of specific radioactivity of soft tissue 3 H in mothers to HTO in drinking water exceeded 1 only for the spleen, but other tissues showed no biological concentration. Again, no biological concentration was observed with 3 H foods. Environmental HTO did not result in biological concentration of 3 H in mother mice that had ingested 3 H foods, but 3 H was rather diluted. Tissues other than the spleen showed similar values of 3 H ingestion from environmental HTO through all routes. However, the proportion of bound 3 H in the total 3 H in the soft tissue was about 1.4-1.6 times that on ingestion of HTO alone. (Chiba, N.)

  9. Systems biology for understanding and engineering of heterotrophic oleaginous microorganisms.

    Science.gov (United States)

    Park, Beom Gi; Kim, Minsuk; Kim, Joonwon; Yoo, Heewang; Kim, Byung-Gee

    2017-01-01

    Heterotrophic oleaginous microorganisms continue to draw interest as they can accumulate a large amount of lipids which is a promising feedstock for the production of biofuels and oleochemicals. Nutrient limitation, especially nitrogen limitation, is known to effectively trigger the lipid production in these microorganisms. For the aim of developing improved strains, the mechanisms behind the lipid production have been studied for a long time. Nowadays, system-level understanding of their metabolism and associated metabolic switches is attainable with modern systems biology tools. This work reviews the systems biology studies, based on (i) top-down, large-scale 'omics' tools, and (ii) bottom-up, mathematical modeling methods, on the heterotrophic oleaginous microorganisms with an emphasis on further application to metabolic engineering. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Nonlinear Rheology in a Model Biological Tissue.

    Science.gov (United States)

    Matoz-Fernandez, D A; Agoritsas, Elisabeth; Barrat, Jean-Louis; Bertin, Eric; Martens, Kirsten

    2017-04-14

    The rheological response of dense active matter is a topic of fundamental importance for many processes in nature such as the mechanics of biological tissues. One prominent way to probe mechanical properties of tissues is to study their response to externally applied forces. Using a particle-based model featuring random apoptosis and environment-dependent division rates, we evidence a crossover from linear flow to a shear-thinning regime with an increasing shear rate. To rationalize this nonlinear flow we derive a theoretical mean-field scenario that accounts for the interplay of mechanical and active noise in local stresses. These noises are, respectively, generated by the elastic response of the cell matrix to cell rearrangements and by the internal activity.

  11. 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.

  12. Quantum mechanical simulation methods for studying biological systems

    International Nuclear Information System (INIS)

    Bicout, D.; Field, M.

    1996-01-01

    Most known biological mechanisms can be explained using fundamental laws of physics and chemistry and a full understanding of biological processes requires a multidisciplinary approach in which all the tools of biology, chemistry and physics are employed. An area of research becoming increasingly important is the theoretical study of biological macromolecules where numerical experimentation plays a double role of establishing a link between theoretical models and predictions and allowing a quantitative comparison between experiments and models. This workshop brought researchers working on different aspects of the development and application of quantum mechanical simulation together, assessed the state-of-the-art in the field and highlighted directions for future research. Fourteen lectures (theoretical courses and specialized seminars) deal with following themes: 1) quantum mechanical calculations of large systems, 2) ab initio molecular dynamics where the calculation of the wavefunction and hence the energy and forces on the atoms for a system at a single nuclear configuration are combined with classical molecular dynamics algorithms in order to perform simulations which use a quantum mechanical potential energy surface, 3) quantum dynamical simulations, electron and proton transfer processes in proteins and in solutions and finally, 4) free seminars that helped to enlarge the scope of the workshop. (N.T.)

  13. Ising models of strongly coupled biological networks with multivariate interactions

    Science.gov (United States)

    Merchan, Lina; Nemenman, Ilya

    2013-03-01

    Biological networks consist of a large number of variables that can be coupled by complex multivariate interactions. However, several neuroscience and cell biology experiments have reported that observed statistics of network states can be approximated surprisingly well by maximum entropy models that constrain correlations only within pairs of variables. We would like to verify if this reduction in complexity results from intricacies of biological organization, or if it is a more general attribute of these networks. We generate random networks with p-spin (p > 2) interactions, with N spins and M interaction terms. The probability distribution of the network states is then calculated and approximated with a maximum entropy model based on constraining pairwise spin correlations. Depending on the M/N ratio and the strength of the interaction terms, we observe a transition where the pairwise approximation is very good to a region where it fails. This resembles the sat-unsat transition in constraint satisfaction problems. We argue that the pairwise model works when the number of highly probable states is small. We argue that many biological systems must operate in a strongly constrained regime, and hence we expect the pairwise approximation to be accurate for a wide class of problems. This research has been partially supported by the James S McDonnell Foundation grant No.220020321.

  14. Hydrogen production from biomass by biological systems

    International Nuclear Information System (INIS)

    Sharifan, H.R.; Qader, S.

    2009-01-01

    Hydrogen gas is seen as a future energy carrier, not involved in 'greenhouse' gas and its released energy in combustion can be converted to electric power. Biological system with low energy can produce hydrogen compared to electrochemical hydrogen production via solar battery-based water splitting which requires the use of solar batteries with high energy requirements. The biological hydrogen production occurs in microalgae and cyanobacteria by photosynthesis. They consume biochemical energy to produce molecular hydrogen. Hydrogen in some algae is an anaerobic production in the absence of light. In cyanobacteria the hydrogen production simultaneously happens with nitrogen fixation, and also catalyzed by nitrogenase as a side reaction. Hydrogen production by photosynthetic bacteria is mediated by nitrogenase activity, although hydrogenases may be active for both hydrogen production and hydrogen uptake under some conditions. Genetic studies on photosynthetic microorganisms have markedly increased in recent times, relatively few genetic engineering studies have focused on altering the characteristics of these microorganisms, particularly with respect to enhancing the hydrogen-producing capabilities of photosynthetic bacteria and cyanobacteria. (author)

  15. Theory of hybrid dynamical systems and its applications to biological and medical systems.

    Science.gov (United States)

    Aihara, Kazuyuki; Suzuki, Hideyuki

    2010-11-13

    In this introductory article, we survey the contents of this Theme Issue. This Theme Issue deals with a fertile region of hybrid dynamical systems that are characterized by the coexistence of continuous and discrete dynamics. It is now well known that there exist many hybrid dynamical systems with discontinuities such as impact, switching, friction and sliding. The first aim of this Issue is to discuss recent developments in understanding nonlinear dynamics of hybrid dynamical systems in the two main theoretical fields of dynamical systems theory and control systems theory. A combined study of the hybrid systems dynamics in the two theoretical fields might contribute to a more comprehensive understanding of hybrid dynamical systems. In addition, mathematical modelling by hybrid dynamical systems is particularly important for understanding the nonlinear dynamics of biological and medical systems as they have many discontinuities such as threshold-triggered firing in neurons, on-off switching of gene expression by a transcription factor, division in cells and certain types of chronotherapy for prostate cancer. Hence, the second aim is to discuss recent applications of hybrid dynamical systems in biology and medicine. Thus, this Issue is not only general to serve as a survey of recent progress in hybrid systems theory but also specific to introduce interesting and stimulating applications of hybrid systems in biology and medicine. As the introduction to the topics in this Theme Issue, we provide a brief history of nonlinear dynamics and mathematical modelling, different mathematical models of hybrid dynamical systems, the relationship between dynamical systems theory and control systems theory, examples of complex behaviour in a simple neuron model and its variants, applications of hybrid dynamical systems in biology and medicine as a road map of articles in this Theme Issue and future directions of hybrid systems modelling.

  16. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems.

    Science.gov (United States)

    Lomnitz, Jason G; Savageau, Michael A

    2016-01-01

    Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count

  17. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

    Science.gov (United States)

    Lomnitz, Jason G.; Savageau, Michael A.

    2016-01-01

    Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment, and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1) enumeration of the repertoire of model phenotypes, (2) prediction of values for the parameters for any model phenotype, and (3) analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3, and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between three stable states by transient stimulation through one of two input channels: a positive channel that increases the count

  18. Design Space Toolbox V2: Automated Software Enabling a Novel Phenotype-Centric Modeling Strategy for Natural and Synthetic Biological Systems

    Directory of Open Access Journals (Sweden)

    Jason Gunther Lomnitz

    2016-07-01

    Full Text Available Mathematical models of biochemical systems provide a means to elucidate the link between the genotype, environment and phenotype. A subclass of mathematical models, known as mechanistic models, quantitatively describe the complex non-linear mechanisms that capture the intricate interactions between biochemical components. However, the study of mechanistic models is challenging because most are analytically intractable and involve large numbers of system parameters. Conventional methods to analyze them rely on local analyses about a nominal parameter set and they do not reveal the vast majority of potential phenotypes possible for a given system design. We have recently developed a new modeling approach that does not require estimated values for the parameters initially and inverts the typical steps of the conventional modeling strategy. Instead, this approach relies on architectural features of the model to identify the phenotypic repertoire and then predict values for the parameters that yield specific instances of the system that realize desired phenotypic characteristics. Here, we present a collection of software tools, the Design Space Toolbox V2 based on the System Design Space method, that automates (1 enumeration of the repertoire of model phenotypes, (2 prediction of values for the parameters for any model phenotype and (3 analysis of model phenotypes through analytical and numerical methods. The result is an enabling technology that facilitates this radically new, phenotype-centric, modeling approach. We illustrate the power of these new tools by applying them to a synthetic gene circuit that can exhibit multi-stability. We then predict values for the system parameters such that the design exhibits 2, 3 and 4 stable steady states. In one example, inspection of the basins of attraction reveals that the circuit can count between 3 stable states by transient stimulation through one of two input channels: a positive channel that increases

  19. Accelerating Bayesian inference for evolutionary biology models.

    Science.gov (United States)

    Meyer, Xavier; Chopard, Bastien; Salamin, Nicolas

    2017-03-01

    Bayesian inference is widely used nowadays and relies largely on Markov chain Monte Carlo (MCMC) methods. Evolutionary biology has greatly benefited from the developments of MCMC methods, but the design of more complex and realistic models and the ever growing availability of novel data is pushing the limits of the current use of these methods. We present a parallel Metropolis-Hastings (M-H) framework built with a novel combination of enhancements aimed towards parameter-rich and complex models. We show on a parameter-rich macroevolutionary model increases of the sampling speed up to 35 times with 32 processors when compared to a sequential M-H process. More importantly, our framework achieves up to a twentyfold faster convergence to estimate the posterior probability of phylogenetic trees using 32 processors when compared to the well-known software MrBayes for Bayesian inference of phylogenetic trees. https://bitbucket.org/XavMeyer/hogan. nicolas.salamin@unil.ch. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  20. Integrative Systems Biology: Elucidating Complex Traits

    DEFF Research Database (Denmark)

    Pers, Tune Hannes

    Risk-phenotypes and diseases are oen caused by perturbed cellular networks, as biological processes depend on an overwhelming number of heavily intertwined components. e impact of a genetically altered gene may ripple through its molecular neighborhood instead of being confined to the gene...... product itself. My doctoral studies have been focused on the development of integrative approaches to identify systemic risk-modifying and disease-causing patterns. ey have been rooted in the hypothesis that data integration of complementary data sets may yield additional etiologic insights compared...... to analyses conducted within a single type of data. e first line of research presented here outlines two integrative methodologies designed to identify etiological pathways and susceptibility genes. In Paper I, my coworkers and I present an integrative approach that interrogates protein complexes...

  1. Biologically based multistage modeling of radiation effects

    Energy Technology Data Exchange (ETDEWEB)

    William Hazelton; Suresh Moolgavkar; E. Georg Luebeck

    2005-08-30

    This past year we have made substantial progress in modeling the contribution of homeostatic regulation to low-dose radiation effects and carcinogenesis. We have worked to refine and apply our multistage carcinogenesis models to explicitly incorporate cell cycle states, simple and complex damage, checkpoint delay, slow and fast repair, differentiation, and apoptosis to study the effects of low-dose ionizing radiation in mouse intestinal crypts, as well as in other tissues. We have one paper accepted for publication in ''Advances in Space Research'', and another manuscript in preparation describing this work. I also wrote a chapter describing our combined cell-cycle and multistage carcinogenesis model that will be published in a book on stochastic carcinogenesis models edited by Wei-Yuan Tan. In addition, we organized and held a workshop on ''Biologically Based Modeling of Human Health Effects of Low dose Ionizing Radiation'', July 28-29, 2005 at Fred Hutchinson Cancer Research Center in Seattle, Washington. We had over 20 participants, including Mary Helen Barcellos-Hoff as keynote speaker, talks by most of the low-dose modelers in the DOE low-dose program, experimentalists including Les Redpath (and Mary Helen), Noelle Metting from DOE, and Tony Brooks. It appears that homeostatic regulation may be central to understanding low-dose radiation phenomena. The primary effects of ionizing radiation (IR) are cell killing, delayed cell cycling, and induction of mutations. However, homeostatic regulation causes cells that are killed or damaged by IR to eventually be replaced. Cells with an initiating mutation may have a replacement advantage, leading to clonal expansion of these initiated cells. Thus we have focused particularly on modeling effects that disturb homeostatic regulation as early steps in the carcinogenic process. There are two primary considerations that support our focus on homeostatic regulation. First, a number of

  2. How to Build a Course in Mathematical-Biological Modeling: Content and Processes for Knowledge and Skill

    Science.gov (United States)

    Hoskinson, Anne-Marie

    2010-01-01

    Biological problems in the twenty-first century are complex and require mathematical insight, often resulting in mathematical models of biological systems. Building mathematical-biological models requires cooperation among biologists and mathematicians, and mastery of building models. A new course in mathematical modeling presented the opportunity…

  3. Systems biology in practice: concepts, implementation and application

    National Research Council Canada - National Science Library

    Klipp, E

    2005-01-01

    ... approaching systems biology from a different discipline. We see the origin and the methodological foundations for systems biology (1) in the accumulation of detailed biological knowledge with the prospect of utilization in biotechnology and health care, (2) in the emergence of new experimental techniques in genomics and proteomics, (3) in the traditio...

  4. Glycoengineering in CHO Cells: Advances in Systems Biology.

    Science.gov (United States)

    Tejwani, Vijay; Andersen, Mikael R; Nam, Jong Hyun; Sharfstein, Susan T

    2018-03-01

    For several decades, glycoprotein biologics have been successfully produced from Chinese hamster ovary (CHO) cells. The therapeutic efficacy and potency of glycoprotein biologics are often dictated by their post-translational modifications, particularly glycosylation, which unlike protein synthesis, is a non-templated process. Consequently, both native and recombinant glycoprotein production generate heterogeneous mixtures containing variable amounts of different glycoforms. Stability, potency, plasma half-life, and immunogenicity of the glycoprotein biologic are directly influenced by the glycoforms. Recently, CHO cells have also been explored for production of therapeutic glycosaminoglycans (e.g., heparin), which presents similar challenges as producing glycoproteins biologics. Approaches to controlling heterogeneity in CHO cells and directing the biosynthetic process toward desired glycoforms are not well understood. A systems biology approach combining different technologies is needed for complete understanding of the molecular processes accounting for this variability and to open up new venues in cell line development. In this review, we describe several advances in genetic manipulation, modeling, and glycan and glycoprotein analysis that together will provide new strategies for glycoengineering of CHO cells with desired or enhanced glycosylation capabilities. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Monitoring and modeling of microbial and biological water quality

    Science.gov (United States)

    Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

  6. 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.

  7. 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...... diseases were linked to the two DDT isomers. Asthma was uniquely linked with p,p´-DDT, and autism with o,p´-DDT. Several reproductive and neurobehavioral outcomes and cancer types were linked to all three compounds.Conclusions: Computer-based modeling relies on available information. Although differences...

  8. Computational intelligence approaches for pattern discovery in biological systems.

    Science.gov (United States)

    Fogel, Gary B

    2008-07-01

    Biology, chemistry and medicine are faced by tremendous challenges caused by an overwhelming amount of data and the need for rapid interpretation. Computational intelligence (CI) approaches such as artificial neural networks, fuzzy systems and evolutionary computation are being used with increasing frequency to contend with this problem, in light of noise, non-linearity and temporal dynamics in the data. Such methods can be used to develop robust models of processes either on their own or in combination with standard statistical approaches. This is especially true for database mining, where modeling is a key component of scientific understanding. This review provides an introduction to current CI methods, their application to biological problems, and concludes with a commentary about the anticipated impact of these approaches in bioinformatics.

  9. Models to study gravitational biology of Mammalian reproduction

    Science.gov (United States)

    Tou, Janet; Ronca, April; Grindeland, Richard; Wade, Charles

    2002-01-01

    Mammalian reproduction evolved within Earth's 1-g gravitational field. As we move closer to the reality of space habitation, there is growing scientific interest in how different gravitational states influence reproduction in mammals. Habitation of space and extended spaceflight missions require prolonged exposure to decreased gravity (hypogravity, i.e., weightlessness). Lift-off and re-entry of the spacecraft are associated with exposure to increased gravity (hypergravity). Existing data suggest that spaceflight is associated with a constellation of changes in reproductive physiology and function. However, limited spaceflight opportunities and confounding effects of various nongravitational factors associated with spaceflight (i.e., radiation, stress) have led to the development of ground-based models for studying the effects of altered gravity on biological systems. Human bed rest and rodent hindlimb unloading paradigms are used to study exposure to hypogravity. Centrifugation is used to study hypergravity. Here, we review the results of spaceflight and ground-based models of altered gravity on reproductive physiology. Studies utilizing ground-based models that simulate hyper- and hypogravity have produced reproductive results similar to those obtained from spaceflight and are contributing new information on biological responses across the gravity continuum, thereby confirming the appropriateness of these models for studying reproductive responses to altered gravity and the underlying mechanisms of these responses. Together, these unique tools are yielding new insights into the gravitational biology of reproduction in mammals.

  10. Effects of abiotic stress on plants: a systems biology perspective.

    Science.gov (United States)

    Cramer, Grant R; Urano, Kaoru; Delrot, Serge; Pezzotti, Mario; Shinozaki, Kazuo

    2011-11-17

    The natural environment for plants is composed of a complex set of abiotic stresses and biotic stresses. Plant responses to these stresses are equally complex. Systems biology approaches facilitate a multi-targeted approach by allowing one to identify regulatory hubs in complex networks. Systems biology takes the molecular parts (transcripts, proteins and metabolites) of an organism and attempts to fit them into functional networks or models designed to describe and predict the dynamic activities of that organism in different environments. In this review, research progress in plant responses to abiotic stresses is summarized from the physiological level to the molecular level. New insights obtained from the integration of omics datasets are highlighted. Gaps in our knowledge are identified, providing additional focus areas for crop improvement research in the future.

  11. Systems Biology in Animal Production and Health, Vol. 1

    DEFF Research Database (Denmark)

    for improved animal production and health. The book will contain online resources where additional data and programs can be accessed. Some chapters also come with computer programming codes and example datasets to provide readers hands-on (computer) exercises. This first volume presents the basic principles...... and concepts of systems biology with theoretical foundations including genetic, co-expression and metabolic networks. It will introduce to multi omics components of systems biology from genomics, through transcriptomics, proteomics to metabolomics. In addition it will highlight statistical methods...... and (bioinformatic) tools available to model and analyse these data sets along with phenotypes in animal production and health. This book is suitable for both students and teachers in animal sciences and veterinary medicine as well as to researchers in this discipline....

  12. Metabolic adaptation of a human pathogen during chronic infections - a systems biology approach

    DEFF Research Database (Denmark)

    Thøgersen, Juliane Charlotte

    modeling to uncover how human pathogens adapt to the human host. Pseudomonas aeruginosa infections in cystic fibrosis patients are used as a model system for under-­‐ standing these adaptation processes. The exploratory systems biology approach facilitates identification of important phenotypes...... by classical molecular biology approaches where genes and reactions typically are investigated in a one to one relationship. This thesis is an example of how mathematical approaches and modeling can facilitate new biologi-­‐ cal understanding and provide new surprising ideas to important biological processes....

  13. Programmable temperature control system for biological materials

    Science.gov (United States)

    Anselmo, V. J.; Harrison, R. G.; Rinfret, A. P.

    1982-01-01

    A system was constructed which allows programmable temperature-time control for a 5 cu cm sample volume of arbitrary biological material. The system also measures the parameters necessary for the determination of the sample volume specific heat and thermal conductivity as a function of temperature, and provides a detailed measurement of the temperature during phase change and a means of calculating the heat of the phase change. Steady-state and dynamic temperature control is obtained by supplying heat to the sample volume through resistive elements constructed as an integral part of the sample container. For cooling purposes, this container is totally immersed into a cold heat sink. Using a mixture of dry ice and alcohol at 79 C, the sample volume can be controlled from +40 to -60 C at rates from steady state to + or - 65 C/min. Steady-state temperature precision is better than 0.2 C, while the dynamic capability depends on the temperature rate of change as well as the mass of both the sample and the container.

  14. 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.

  15. [Systems biology applications to explore secondary metabolites in medicinal plants].

    Science.gov (United States)

    Huang, Luqi; Gao, Wei; Zhou, Jie; Wang, Ruiting

    2010-01-01

    Secondary metabolites are produced during the growth and development of plants along with the adaptation of outer environment, as a rule they are the main active ingredients in medicinal plants and ensure the quality of crude drugs. Since biogenesis is quite complex, the production and accumulation of secondary metabolites are influenced by various biotic and abiotic factors either from gene or environments, the complexity may affect quality control of crude drugs and utilization of the active ingredients. The thought and approach adopted in systems biology is a powerful tool to explore biology fully, along with the development of modern molecular biology and information biology, omics integration like genomics, transcriptomics, proteomics, and metabolomics will bring new opportunities for the study of secondary metabolites of medicinal plant. It has great significance to apply this holistic and systematic method in researches on biosynthetic pathway, signal transduction, ecological environment and metabolic engineering of the formation of the secondary metabolites of medicinal plants, and in building secondary metabolite biosynthesis gene expression and regulation system model, in order to explain the origin of the active ingredients of medicinal plants, formation mechanism of the Chinese herbs, metabolic engineering effecting active ingredients of medicinal plants, and the rational exploitation and utilization of resources of medicinal plants systematically.

  16. A systems biology approach reveals common metastatic pathways in osteosarcoma

    Directory of Open Access Journals (Sweden)

    Flores Ricardo J

    2012-05-01

    Full Text Available Abstract Background Osteosarcoma (OS is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest-path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the Sa

  17. Network Reconstruction of Dynamic Biological Systems

    OpenAIRE

    Asadi, Behrang

    2013-01-01

    Inference of network topology from experimental data is a central endeavor in biology, since knowledge of the underlying signaling mechanisms a requirement for understanding biological phenomena. As one of the most important tools in bioinformatics area, development of methods to reconstruct biological networks has attracted remarkable attention in the current decade. Integration of different data types can lead to remarkable improvements in our ability to identify the connectivity of differe...

  18. Systems biology of microbial exopolysaccharides production

    Directory of Open Access Journals (Sweden)

    Ozlem eAtes

    2015-12-01

    Full Text Available Exopolysaccharides (EPS produced by diverse group of microbial systems are rapidly emerging as new and industrially important biomaterials. Due to their unique and complex chemical structures and many interesting physicochemical and rheological properties with novel functionality, the microbial EPSs find wide range of commercial applications in various fields of the economy such as food, feed, packaging, chemical, textile, cosmetics and pharmaceutical industry, agriculture and medicine. EPSs are mainly associated with high-value applications and they have received considerable research attention over recent decades with their biocompatibility, biodegradability, and both environmental and human compatibility. However only a few microbial EPSs have achieved to be used commercially due to their high production costs. The emerging need to overcome economic hurdles and the increasing significance of microbial EPSs in industrial and medical biotechnology call for the elucidation of the interrelations between metabolic pathways and EPS biosynthesis mechanism in order to control and hence enhance its microbial productivity. Moreover a better understanding of biosynthesis mechanism is a significant issue for improvement of product quality and properties and also for the design of novel strains. Therefore a systems-based approach constitutes an important step towards understanding the interplay between metabolism and EPS biosynthesis and further enhances its metabolic performance for industrial application. In this review, primarily the microbial EPSs, their biosynthesis mechanism and important factors for their production will be discussed. After this brief introduction, recent literature on the application of omics technologies and systems biology tools for the improvement of production yields will be critically evaluated. Special focus will be given to EPSs with high market value such as xanthan, levan, pullulan and dextran.

  19. Systems Biology of Microbial Exopolysaccharides Production.

    Science.gov (United States)

    Ates, Ozlem

    2015-01-01

    Exopolysaccharides (EPSs) produced by diverse group of microbial systems are rapidly emerging as new and industrially important biomaterials. Due to their unique and complex chemical structures and many interesting physicochemical and rheological properties with novel functionality, the microbial EPSs find wide range of commercial applications in various fields of the economy such as food, feed, packaging, chemical, textile, cosmetics and pharmaceutical industry, agriculture, and medicine. EPSs are mainly associated with high-value applications, and they have received considerable research attention over recent decades with their biocompatibility, biodegradability, and both environmental and human compatibility. However, only a few microbial EPSs have achieved to be used commercially due to their high production costs. The emerging need to overcome economic hurdles and the increasing significance of microbial EPSs in industrial and medical biotechnology call for the elucidation of the interrelations between metabolic pathways and EPS biosynthesis mechanism in order to control and hence enhance its microbial productivity. Moreover, a better understanding of biosynthesis mechanism is a significant issue for improvement of product quality and properties and also for the design of novel strains. Therefore, a systems-based approach constitutes an important step toward understanding the interplay between metabolism and EPS biosynthesis and further enhances its metabolic performance for industrial application. In this review, primarily the microbial EPSs, their biosynthesis mechanism, and important factors for their production will be discussed. After this brief introduction, recent literature on the application of omics technologies and systems biology tools for the improvement of production yields will be critically evaluated. Special focus will be given to EPSs with high market value such as xanthan, levan, pullulan, and dextran.

  20. Applying systems biology methods to the study of human physiology in extreme environments.

    Science.gov (United States)

    Edwards, Lindsay M; Thiele, Ines

    2013-03-22

    Systems biology is defined in this review as 'an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems'. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is extremely limited and principally comprises exercise, nutrition, infusions (e.g. Intralipid), some drugs and altered environment. Thus, we argue that systems biology and environmental physiology are natural symbionts for those interested in a system-level understanding of human biology. However, despite excellent progress in high-altitude genetics and several proteomics studies, systems biology research into human adaptation to extreme environments is in its infancy. A brief description and overview of systems biology in its current guise is given, followed by a mini review of computational methods used for modelling biological systems. Special attention is given to high-altitude research, metabolic network reconstruction and constraint-based modelling.

  1. METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

    Directory of Open Access Journals (Sweden)

    Paula Jouhten

    2012-10-01

    Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

  2. Biology meets Physics: Reductionism and Multi-scale Modeling of Morphogenesis

    DEFF Research Database (Denmark)

    Green, Sara; Batterman, Robert

    2017-01-01

    from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom......-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the “tyranny of scales” problem present a challenge to reductive explanations in both physics and biology. The problem refers to the scale......-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions. Analyzing the ways in which different models are combined in multi-scale modeling also has implications for the relation between physics...

  3. Efficient Estimation of the Robustness Region of Biological Models with Oscillatory Behavior

    NARCIS (Netherlands)

    Apri, M.; Molenaar, J.; Gee, de M.; Voorn, van G.A.K.

    2010-01-01

    Robustness is an essential feature of biological systems, and any mathematical model that describes such a system should reflect this feature. Especially, persistence of oscillatory behavior is an important issue. A benchmark model for this phenomenon is the Laub-Loomis model, a nonlinear model for

  4. Toward university modeling instruction--biology: adapting curricular frameworks from physics to biology.

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-06-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence.

  5. Toward University Modeling Instruction—Biology: Adapting Curricular Frameworks from Physics to Biology

    Science.gov (United States)

    Manthey, Seth; Brewe, Eric

    2013-01-01

    University Modeling Instruction (UMI) is an approach to curriculum and pedagogy that focuses instruction on engaging students in building, validating, and deploying scientific models. Modeling Instruction has been successfully implemented in both high school and university physics courses. Studies within the physics education research (PER) community have identified UMI's positive impacts on learning gains, equity, attitudinal shifts, and self-efficacy. While the success of this pedagogical approach has been recognized within the physics community, the use of models and modeling practices is still being developed for biology. Drawing from the existing research on UMI in physics, we describe the theoretical foundations of UMI and how UMI can be adapted to include an emphasis on models and modeling for undergraduate introductory biology courses. In particular, we discuss our ongoing work to develop a framework for the first semester of a two-semester introductory biology course sequence by identifying the essential basic models for an introductory biology course sequence. PMID:23737628

  6. A Comprehensive Web-based Platform For Domain-Specific Biological Models

    Czech Academy of Sciences Publication Activity Database

    Klement, M.; Šafránek, D.; Děd, J.; Pejznoch, A.; Nedbal, Ladislav; Steuer, Ralf; Červený, Jan; Müller, Stefan

    2013-01-01

    Roč. 299, 25 Dec (2013), s. 61-67 ISSN 1571-0661 R&D Projects: GA MŠk(CZ) EE2.3.20.0256 Institutional support: RVO:67179843 Keywords : biological models * model annotation * systems biology * simulation * database Subject RIV: EH - Ecology, Behaviour

  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. Computerised modelling for developmental biology : an exploration with case studies

    NARCIS (Netherlands)

    Bertens, Laura M.F.

    2012-01-01

    Many studies in developmental biology rely on the construction and analysis of models. This research presents a broad view of modelling approaches for developmental biology, with a focus on computational methods. An overview of modelling techniques is given, followed by several case studies. Using

  9. Systems biology: properties of reconstructed networks

    National Research Council Canada - National Science Library

    Palsson, Bernhard

    2006-01-01

    ... between the mathematical ideas and biological processes are made clear, the book reflects the irreversible trend of increasing mathematical content in biology education. Therefore to assist both teacher and student, Palsson provides problem sets, projects, and PowerPoint slides in an associated web site and keeps the presentation in the book concrete with illustrat...

  10. Isotopic fractionation of tritium in biological systems.

    Science.gov (United States)

    Le Goff, Pierre; Fromm, Michel; Vichot, Laurent; Badot, Pierre-Marie; Guétat, Philippe

    2014-04-01

    Isotopic fractionation of tritium is a highly relevant issue in radiation protection and requires certain radioecological considerations. Sound evaluation of this factor is indeed necessary to determine whether environmental compartments are enriched/depleted in tritium or if tritium is, on the contrary, isotopically well-distributed in a given system. The ubiquity of tritium and the standard analytical methods used to assay it may induce biases in both the measurement and the signification that is accorded to the so-called fractionation: based on an exhaustive review of the literature, we show how, sometimes large deviations may appear. It is shown that when comparing the non-exchangeable fraction of organically bound tritium (neOBT) to another fraction of tritium (e.g. tritiated water) the preparation of samples and the measurement of neOBT reported frequently led to underestimation of the ratio of tritium to hydrogen (T/H) in the non-exchangeable compartment by a factor of 5% to 50%. In the present study, corrections are proposed for most of the biological matrices studied so far. Nevertheless, the values of isotopic fractionation reported in the literature remain difficult to compare with each other, especially since the physical quantities and units often vary between authors. Some improvements are proposed to better define what should encompass the concepts of exchangeable and non-exchangeable fractions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

    Directory of Open Access Journals (Sweden)

    Banga Julio R

    2006-11-01

    Full Text Available Abstract Background We consider the problem of parameter estimation (model calibration in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector. In order to surmount these difficulties, global optimization (GO methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. Results We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown structure (i.e. black-box models. In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned successful methods. Conclusion Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously

  12. Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems.

    Science.gov (United States)

    Rodriguez-Fernandez, Maria; Egea, Jose A; Banga, Julio R

    2006-11-02

    We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness. We have developed a new procedure based on the scatter search methodology for nonlinear optimization of dynamic models of arbitrary (or even unknown) structure (i.e. black-box models). In this contribution, we describe and apply this novel metaheuristic, inspired by recent developments in the field of operations research, to a set of complex identification problems and we make a critical comparison with respect to the previous (above mentioned) successful methods. Robust and efficient methods for parameter estimation are of key importance in systems biology and related areas. The new metaheuristic presented in this paper aims to ensure the proper solution of these problems by adopting a global optimization approach, while keeping the computational effort under reasonable values. This new metaheuristic was applied to a set of three challenging parameter estimation problems of nonlinear dynamic biological systems, outperforming very significantly all the methods previously used for these benchmark problems.

  13. Unmanned Aircraft Systems complement biologging in spatial ecology studies.

    Science.gov (United States)

    Mulero-Pázmány, Margarita; Barasona, Jose Ángel; Acevedo, Pelayo; Vicente, Joaquín; Negro, Juan José

    2015-11-01

    The knowledge about the spatial ecology and distribution of organisms is important for both basic and applied science. Biologging is one of the most popular methods for obtaining information about spatial distribution of animals, but requires capturing the animals and is often limited by costs and data retrieval. Unmanned Aircraft Systems (UAS) have proven their efficacy for wildlife surveillance and habitat monitoring, but their potential contribution to the prediction of animal distribution patterns and abundance has not been thoroughly evaluated. In this study, we assess the usefulness of UAS overflights to (1) get data to model the distribution of free-ranging cattle for a comparison with results obtained from biologged (GPS-GSM collared) cattle and (2) predict species densities for a comparison with actual density in a protected area. UAS and biologging derived data models provided similar distribution patterns. Predictions from the UAS model overestimated cattle densities, which may be associated with higher aggregated distributions of this species. Overall, while the particular researcher interests and species characteristics will influence the method of choice for each study, we demonstrate here that UAS constitute a noninvasive methodology able to provide accurate spatial data useful for ecological research, wildlife management and rangeland planning.

  14. Applying systems biology methods to the study of human physiology in extreme environments

    Science.gov (United States)

    2013-01-01

    Systems biology is defined in this review as ‘an iterative process of computational model building and experimental model revision with the aim of understanding or simulating complex biological systems’. We propose that, in practice, systems biology rests on three pillars: computation, the omics disciplines and repeated experimental perturbation of the system of interest. The number of ethical and physiologically relevant perturbations that can be used in experiments on healthy humans is extremely limited and principally comprises exercise, nutrition, infusions (e.g. Intralipid), some drugs and altered environment. Thus, we argue that systems biology and environmental physiology are natural symbionts for those interested in a system-level understanding of human biology. However, despite excellent progress in high-altitude genetics and several proteomics studies, systems biology research into human adaptation to extreme environments is in its infancy. A brief description and overview of systems biology in its current guise is given, followed by a mini review of computational methods used for modelling biological systems. Special attention is given to high-altitude research, metabolic network reconstruction and constraint-based modelling. PMID:23849719

  15. The Promise of Systems Biology for Diabetic Kidney Disease.

    Science.gov (United States)

    Brosius, Frank C; Ju, Wenjun

    2018-03-01

    Diabetic kidney disease (DKD) has a complex and prolonged pathogenesis involving many cell types in the kidney as well as extrarenal factors. It is clinically silent for many years after the onset of diabetes and usually progresses over decades. Given this complexity, a comprehensive and unbiased molecular approach is best suited to help identify the most critical mechanisms responsible for progression of DKD and those most suited for targeted intervention. Systems biological investigations provide such an approach since they examine the entire network of molecular changes that occur in a disease process in a comprehensive way instead of focusing on a single abnormal molecule or pathway. Systems biological studies can also start with analysis of the disease in humans, not in animal or cell culture models that often poorly reproduce the changes in human DKD. Indeed, in the last decade, systems biological approaches have led to the identification of critical molecular abnormalities in DKD and have directly led to development of new biomarkers and potential treatments for DKD. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  16. 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....

  17. Interactive analysis of systems biology molecular expression data

    OpenAIRE

    Prabhakar Sunil; Salt David E; Kane Michael D; Stephenson Alan; Ouyang Qi; Zhang Mingwu; Burgner John; Buck Charles; Zhang Xiang

    2008-01-01

    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 preferr...

  18. 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

  19. 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

  20. Stochastic differential equations and a biological system

    DEFF Research Database (Denmark)

    Wang, Chunyan

    1994-01-01

    . The simulated results are compared with the experimental data, and it is found that the Euler method is the most simple end efficient method for the stochastic growth model considered. Estimation of the parameters of the growth model is based on the stochastic Kalman filter and a continuous Markov process......The purpose of this Ph.D. study is to explore the property of a growth process. The study includes solving and simulating of the growth process which is described in terms of stochastic differential equations. The identification of the growth and variability parameters of the process based...... been developed. Their properties and the relationship between them are discussed. The evolution of a dynamic system or process is usually of great practical interest. In order to simulate the evolution of the process, alternative methods are used to get numerical solutions. In this study, Euler...

  1. Hepatocellular carcinoma: a systems biology perspective

    Directory of Open Access Journals (Sweden)

    Lorenza Alice D'alessandro

    2013-02-01

    Full Text Available Hepatocellular carcinomas (HCC have different etiology and heterogenic genomic alterations lead to high complexity. The molecular features of HCC have largely been studied by gene expression and proteome profiling focusing on the correlations between the expression of specific markers and clinical data. Integration of the increasing amounts of data in databases has facilitated the link of genomic and proteomic profiles of HCC to disease state and clinical outcome. Despite the current knowledge, specific molecular markers remain to be identified and new strategies are required to establish novel targeted therapies. In the last years, mathematical models reconstructing gene and protein networks based on experimental data of HCC have been developed providing powerful tools to predict candidate interactions and potential targets for therapy. Furthermore, the combination of dynamic and logical mathematical models with quantitative data allows detailed mechanistic insights into system properties. To address effects at the organ level, mathematical models reconstructing the three-dimensional organization of liver lobules were developed. In the future, integration of different modeling approaches capturing the effects at the cellular up to the organ level is required to address the complex properties of HCC and to enable the discovery of new targets for HCC prevention or treatment.

  2. Application of enriched stable isotopes as tracers in biological systems

    DEFF Research Database (Denmark)

    Stürup, Stefan; Hansen, Helle Rüsz; Gammelgaard, Bente

    2008-01-01

    The application of enriched stable isotopes of minerals and trace elements as tracers in biological systems is a rapidly growing research field that benefits from the many new developments in inorganic mass spectrometric instrumentation, primarily within inductively coupled plasma mass spectrometry...... (ICP-MS) instrumentation, such as reaction/collision cell ICP-MS and multicollector ICP-MS with improved isotope ratio measurement and interference removal capabilities. Adaptation and refinement of radioisotope tracer experiment methodologies for enriched stable isotope experiments......, and the development of new methodologies coupled with more advanced compartmental and mathematical models for the distribution of elements in living organisms has enabled a broader use of enriched stable isotope experiments in the biological sciences. This review discusses the current and future uses of enriched...

  3. Breeding system and pollination biology of the semidomesticated ...

    African Journals Online (AJOL)

    Breeding system and pollination biology of the semidomesticated fruit tree, Tamarindus indica L. (Leguminosae: Caesalpinioideae ): Implications for fruit production, selective breeding, and conservation of genetic resources.

  4. What it takes to understand and cure a living system: computational systems biology and a systems biology-driven pharmacokinetics-pharmacodynamics platform

    NARCIS (Netherlands)

    Swat, Maciej; Kiełbasa, Szymon M.; Polak, Sebastian; Olivier, Brett; Bruggeman, Frank J.; Tulloch, Mark Quinton; Snoep, Jacky L.; Verhoeven, Arthur J.; Westerhoff, Hans V.

    2011-01-01

    The utility of model repositories is discussed in the context of systems biology (SB). It is shown how such repositories, and in particular their live versions, can be used for computational SB: we calculate the robustness of the yeast glycolytic network with respect to perturbations of one of its

  5. Systems biology in physiology: the vasopressin signaling network in kidney.

    Science.gov (United States)

    Knepper, Mark A

    2012-12-01

    Over the past 80 years, physiological research has moved progressively in a reductionist direction, providing mechanistic information on a smaller and smaller scale. This trend has culminated in the present focus on "molecular physiology," which deals with the function of single molecules responsible for cellular function. There is a need to assemble the information from the molecular level into models that explain physiological function at cellular, tissue, organ, and whole organism levels. Such integration is the major focus of an approach called "systems biology." The genome sequencing projects provide a basis for a new kind of systems biology called "data-rich" systems biology that is based on large-scale data acquisition methods including protein mass spectrometry, DNA microarrays, and deep sequencing of nucleic acids. These techniques allow investigators to measure thousands of variables simultaneously in response to an external stimulus. My laboratory is applying such an approach to the question: "How does the peptide hormone vasopressin regulate water permeability in the renal collecting duct?" We are using protein mass spectrometry to identify and quantify the phosphoproteome of collecting duct cells. The response to vasopressin, presented in the form of a network model, includes a general downregulation of proline-directed kinases (MAP kinases and cyclin-dependent kinases) and upregulation of basophilic kinases (ACG kinases and calmodulin-dependent kinases). Further progress depends on characterization and localization of candidate protein kinases in these families. The ultimate goal is to use multivariate statistical techniques and differential equations to obtain predictive models describing vasopressin signaling in the renal collecting duct.

  6. Dynamic Modeling of ALS Systems

    Science.gov (United States)

    Jones, Harry

    2002-01-01

    The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.

  7. Experimental "evolutional machines": mathematical and experimental modeling of biological evolution

    Science.gov (United States)

    Brilkov, A. V.; Loginov, I. A.; Morozova, E. V.; Shuvaev, A. N.; Pechurkin, N. S.

    Experimentalists possess model systems of two major types for study of evolution continuous cultivation in the chemostat and long-term development in closed laboratory microecosystems with several trophic structure If evolutionary changes or transfer from one steady state to another in the result of changing qualitative properties of the system take place in such systems the main characteristics of these evolution steps can be measured By now this has not been realized from the point of view of methodology though a lot of data on the work of both types of evolutionary machines has been collected In our experiments with long-term continuous cultivation we used the bacterial strains containing in plasmids the cloned genes of bioluminescence and green fluorescent protein which expression level can be easily changed and controlled In spite of the apparent kinetic diversity of evolutionary transfers in two types of systems the general mechanisms characterizing the increase of used energy flow by populations of primer producent can be revealed at their study According to the energy approach at spontaneous transfer from one steady state to another e g in the process of microevolution competition or selection heat dissipation characterizing the rate of entropy growth should increase rather then decrease or maintain steady as usually believed The results of our observations of experimental evolution require further development of thermodynamic theory of open and closed biological systems and further study of general mechanisms of biological

  8. From experimental systems to evolutionary biology: an impossible journey?

    Science.gov (United States)

    Morange, Michel

    2013-01-01

    The historical approach to the sciences has undergone a sea change during recent decades. Maybe the major contribution of Hans-Jörg Rheinberger to this movement was his demonstration of the importance of experimental systems, and of their transformations, in the development of the sciences. To describe these transformations, Hans-Jörg borrows metaphors from evolutionary biology. I want to argue that evolutionary biologists can find in these recent historical studies plenty of models and concepts to address unresolved issues in their discipline. At a time when transdisciplinarity is highly praised, it is useful to provide a precise description of the obstacles that have so far prevented this exchange.

  9. Evaluation of a commercial biologically based IMRT treatment planning system

    International Nuclear Information System (INIS)

    Semenenko, Vladimir A.; Reitz, Bodo; Day, Ellen; Qi, X. Sharon; Miften, Moyed; Li, X. Allen

    2008-01-01

    A new inverse treatment planning system (TPS) for external beam radiation therapy with high energy photons is commercially available that utilizes both dose-volume-based cost functions and a selection of cost functions which are based on biological models. The purpose of this work is to evaluate quality of intensity-modulated radiation therapy (IMRT) plans resulting from the use of biological cost functions in comparison to plans designed using a traditional TPS employing dose-volume-based optimization. Treatment planning was performed independently at two institutions. For six cancer patients, including head and neck (one case from each institution), prostate, brain, liver, and rectal cases, segmental multileaf collimator IMRT plans were designed using biological cost functions and compared with clinically used dose-based plans for the same patients. Dose-volume histograms and dosimetric indices, such as minimum, maximum, and mean dose, were extracted and compared between the two types of treatment plans. Comparisons of the generalized equivalent uniform dose (EUD), a previously proposed plan quality index (fEUD), target conformity and heterogeneity indices, and the number of segments and monitor units were also performed. The most prominent feature of the biologically based plans was better sparing of organs at risk (OARs). When all plans from both institutions were combined, the biologically based plans resulted in smaller EUD values for 26 out of 33 OARs by an average of 5.6 Gy (range 0.24 to 15 Gy). Owing to more efficient beam segmentation and leaf sequencing tools implemented in the biologically based TPS compared to the dose-based TPS, an estimated treatment delivery time was shorter in most (five out of six) cases with some plans showing up to 50% reduction. The biologically based plans were generally characterized by a smaller conformity index, but greater heterogeneity index compared to the dose-based plans. Overall, compared to plans based on dose

  10. A Magnetic Sensor System for Biological Detection

    KAUST Repository

    Li, Fuquan

    2015-05-01

    Magnetic biosensors detect biological targets through sensing the stray field of magnetic beads which label the targets. Commonly, magnetic biosensors employ the “sandwich” method to immobilize biological targets, i.e., the targets are sandwiched between a bio-functionalized sensor surface and bio-functionalized magnetic beads. This method has been used very successfully in different application, but its execution requires a rather elaborate procedure including several washing and incubation steps. This dissertation investigates a new magnetic biosensor concept, which enables a simple and effective detection of biological targets. The biosensor takes advantage of the size difference between bare magnetic beads and compounds of magnetic beads and biological targets. First, the detection of super-paramagnetic beads via magnetic tunnel junction (MTJ) sensors is implemented. Frequency modulation is used to enhance the signal-to-noise ratio, enabling the detection of a single magnetic bead. Second, the concept of the magnetic biosensor is investigated theoretically. The biosensor consists of an MTJ sensor, which detects the stray field of magnetic beads inside of a trap on top of the MTJ. A microwire between the trap and the MTJ is used to attract magnetic beads to the trapping well by applying a current to it. The MTJ sensor’s output depends on the number of beads inside the trap. If biological targets are in the sample solution, the beads will form bead compounds consisting of beads linked to the biological targets. Since bead compounds are larger than bare beads, the number of beads inside the trapping well will depend on the presence of biological targets. Hence, the output of the MTJ sensor will depend on the biological targets. The dependences of sensor signals on the sizes of the MTJ sensor, magnetic beads and biological targets are studied to find the optimum constellations for the detection of specific biological targets. The optimization is demonstrated

  11. 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.

  12. Human pluripotent stem cells: an emerging model in developmental biology.

    Science.gov (United States)

    Zhu, Zengrong; Huangfu, Danwei

    2013-02-01

    Developmental biology has long benefited from studies of classic model organisms. Recently, human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, have emerged as a new model system that offers unique advantages for developmental studies. Here, we discuss how studies of hPSCs can complement classic approaches using model organisms, and how hPSCs can be used to recapitulate aspects of human embryonic development 'in a dish'. We also summarize some of the recently developed genetic tools that greatly facilitate the interrogation of gene function during hPSC differentiation. With the development of high-throughput screening technologies, hPSCs have the potential to revolutionize gene discovery in mammalian development.

  13. Digital Learning Material for Model Building in Molecular Biology

    Science.gov (United States)

    Aegerter-Wilmsen, Tinri; Janssen, Fred; Hartog, Rob; Bisseling, Ton

    2005-01-01

    Building models to describe processes forms an essential part of molecular biology research. However, in molecular biology curricula little attention is generally being paid to the development of this skill. In order to provide students the opportunity to improve their model building skills, we decided to develop a number of digital cases about…

  14. A conceptual review on systems biology in health and diseases: from biological