WorldWideScience

Sample records for biomolecular reaction networks

  1. Cellular automata modelling of biomolecular networks dynamics.

    Science.gov (United States)

    Bonchev, D; Thomas, S; Apte, A; Kier, L B

    2010-01-01

    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  2. Duplication and Divergence Effect on Network Motifs in Undirected Bio-Molecular Networks.

    Science.gov (United States)

    Pei Wang; Jinhu Lu; Xinghuo Yu; Zengrong Liu

    2015-06-01

    Duplication and divergence are two basic evolutionary mechanisms of bio-molecular networks. Real-world bio-molecular networks and their statistical characteristics can be well mimicked by artificial algorithms based on the two mechanisms. Bio-molecular networks consist of network motifs, which act as building blocks of large-scale networks. A fundamental question is how network motifs are evolved from long time evolution and natural selection. By considering the effect of various duplication and divergence strategies, we find that the underlying duplication scheme of the real-world undirected bio-molecular networks would rather follow the anti-preference strategy than the random one. The anti-preference duplication mechanism and the dimerization processes can lead to the formation of various motifs, and robustly conserve proper quantities of motifs in the artificial networks as that in the real-world ones. Furthermore, the anti-preference mechanism and edge deletion divergence can robustly preserve the sparsity of the networks. The investigations reveal the possible evolutionary mechanisms of network motifs in real-world bio-molecular networks, and have potential implications in the design, synthesis and reengineering of biological networks for biomedical purpose. PMID:25203993

  3. The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

    Science.gov (United States)

    Caravagna, Giulio; Mauri, Giancarlo; d'Onofrio, Alberto

    2013-01-01

    After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i) the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii) a model of enzymatic futile cycle and (iii) a genetic toggle switch. In (ii) and (iii) we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises. PMID:23437034

  4. The interplay of intrinsic and extrinsic bounded noises in biomolecular networks.

    Directory of Open Access Journals (Sweden)

    Giulio Caravagna

    Full Text Available After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a biomolecular network. The influence of intrinsic and extrinsic noises on biomolecular networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: (i the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, (ii a model of enzymatic futile cycle and (iii a genetic toggle switch. In (ii and (iii we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possible functional role of bounded noises.

  5. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    DEFF Research Database (Denmark)

    Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

    2008-01-01

    use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results: Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with...... transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...... Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes. Conclusion: Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that...

  6. An optics-based variable-temperature assay system for characterizing thermodynamics of biomolecular reactions on solid support

    Energy Technology Data Exchange (ETDEWEB)

    Fei, Yiyan; Landry, James P.; Zhu, X. D., E-mail: xdzhu@physics.ucdavis.edu [Department of Physics, University of California, One Shields Avenue, Davis, California 95616 (United States); Li, Yanhong; Yu, Hai; Lau, Kam; Huang, Shengshu; Chokhawala, Harshal A.; Chen, Xi [Department of Chemistry, University of California, One Shields Avenue, Davis, California 95616 (United States)

    2013-11-15

    A biological state is equilibrium of multiple concurrent biomolecular reactions. The relative importance of these reactions depends on physiological temperature typically between 10 °C and 50 °C. Experimentally the temperature dependence of binding reaction constants reveals thermodynamics and thus details of these biomolecular processes. We developed a variable-temperature opto-fluidic system for real-time measurement of multiple (400–10 000) biomolecular binding reactions on solid supports from 10 °C to 60 °C within ±0.1 °C. We illustrate the performance of this system with investigation of binding reactions of plant lectins (carbohydrate-binding proteins) with 24 synthetic glycans (i.e., carbohydrates). We found that the lectin-glycan reactions in general can be enthalpy-driven, entropy-driven, or both, and water molecules play critical roles in the thermodynamics of these reactions.

  7. Evaluation of stochastic effects on biomolecular networks using the generalised Nyquist stability criterion

    OpenAIRE

    Kim, J; Bates, D. G.; Postlethwaite, I.

    2008-01-01

    Abstract—Stochastic differential equations are now commonly used to model biomolecular networks in systems biology, and much recent research has been devoted to the development of methods to analyse their stability properties. Stability analysis of such systems may be performed using the Laplace transform, which requires the calculation of the exponential matrix involving time symbolically. However, the calculation of the symbolic exponential matrix is not feasible for problems of even mod...

  8. Autocatalysis in reaction networks.

    Science.gov (United States)

    Deshpande, Abhishek; Gopalkrishnan, Manoj

    2014-10-01

    The persistence conjecture is a long-standing open problem in chemical reaction network theory. It concerns the behavior of solutions to coupled ODE systems that arise from applying mass-action kinetics to a network of chemical reactions. The idea is that if all reactions are reversible in a weak sense, then no species can go extinct. A notion that has been found useful in thinking about persistence is that of "critical siphon." We explore the combinatorics of critical siphons, with a view toward the persistence conjecture. We introduce the notions of "drainable" and "self-replicable" (or autocatalytic) siphons. We show that: Every minimal critical siphon is either drainable or self-replicable; reaction networks without drainable siphons are persistent; and nonautocatalytic weakly reversible networks are persistent. Our results clarify that the difficulties in proving the persistence conjecture are essentially due to competition between drainable and self-replicable siphons. PMID:25245394

  9. Modeling stochasticity in biochemical reaction networks

    Science.gov (United States)

    Constantino, P. H.; Vlysidis, M.; Smadbeck, P.; Kaznessis, Y. N.

    2016-03-01

    Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts.

  10. A simple knowledge-based mining method for exploring hidden key molecules in a human biomolecular network

    Directory of Open Access Journals (Sweden)

    Tsuji Shingo

    2012-09-01

    Full Text Available Abstract Background In the functional genomics analysis domain, various methodologies are available for interpreting the results produced by high-throughput biological experiments. These methods commonly use a list of genes as an analysis input, and most of them produce a more complicated list of genes or pathways as the results of the analysis. Although there are several network-based methods, which detect key nodes in the network, the results tend to include well-studied, major hub genes. Results To mine the molecules that have biological meaning but to fewer degrees than major hubs, we propose, in this study, a new network-based method for selecting these hidden key molecules based on virtual information flows circulating among the input list of genes. The human biomolecular network was constructed from the Pathway Commons database, and a calculation method based on betweenness centrality was newly developed. We validated the method with the ErbB pathway and applied it to practical cancer research data. We were able to confirm that the output genes, despite having fewer edges than major hubs, have biological meanings that were able to be invoked by the input list of genes. Conclusions The developed method, named NetHiKe (Network-based Hidden Key molecule miner, was able to detect potential key molecules by utilizing the human biomolecular network as a knowledge base. Thus, it is hoped that this method will enhance the progress of biological data analysis in the whole-genome research era.

  11. Bend-twist-stretch model for coarse elastic network simulation of biomolecular motion

    Science.gov (United States)

    Stember, Joseph N.; Wriggers, Willy

    2009-08-01

    The empirical harmonic potential function of elastic network models (ENMs) is augmented by three- and four-body interactions as well as by a parameter-free connection rule. In the new bend-twist-stretch (BTS) model the complexity of the parametrization is shifted from the spatial level of detail to the potential function, enabling an arbitrary coarse graining of the network. Compared to distance cutoff-based Hookean springs, the approach yields a more stable parametrization of coarse-grained ENMs for biomolecular dynamics. Traditional ENMs give rise to unbounded zero-frequency vibrations when (pseudo)atoms are connected to fewer than three neighbors. A large cutoff is therefore chosen in an ENM (about twice the average nearest-neighbor distance), resulting in many false-positive connections that reduce the spatial detail that can be resolved. More importantly, the required three-neighbor connectedness also limits the coarse graining, i.e., the network must be dense, even in the case of low-resolution structures that exhibit few spatial features. The new BTS model achieves such coarse graining by extending the ENM potential to include three-and four-atom interactions (bending and twisting, respectively) in addition to the traditional two-atom stretching. Thus, the BTS model enables reliable modeling of any three-dimensional graph irrespective of the atom connectedness. The additional potential terms were parametrized using continuum elastic theory of elastic rods, and the distance cutoff was replaced by a competitive Hebb connection rule, setting all free parameters in the model. We validate the approach on a carbon-alpha representation of adenylate kinase and illustrate its use with electron microscopy maps of E. coli RNA polymerase, E. coli ribosome, and eukaryotic chaperonin containing T-complex polypeptide 1, which were difficult to model with traditional ENMs. For adenylate kinase, we find excellent reproduction (>90% overlap) of the ENM modes and B factors

  12. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  13. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

    Directory of Open Access Journals (Sweden)

    Arjun Verma

    2016-07-01

    Full Text Available We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed.

  14. Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications.

    Science.gov (United States)

    Verma, Arjun; Fratto, Brian E; Privman, Vladimir; Katz, Evgeny

    2016-01-01

    We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

  15. Modelling of biochemical reaction networks

    OpenAIRE

    Gloppen Jørgensen, Arne Gunnar

    2011-01-01

    This report investigates signalling in reaction kinetic networks. The main topic is signalling between a substance being controlled by another substance and how this can be related to control theory. Different types of so-called natural controllers are compared and certain properties are investigated. Natural controllers are models on how a catalyst enzyme controls, for example the concentration, of a substance. There are sixteen different combinations of signalling between these substanc...

  16. Programming in Biomolecular Computation:

    DEFF Research Database (Denmark)

    Hartmann, Lars; Jones, Neil; Simonsen, Jakob Grue;

    2011-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem...... conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined...... by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways...

  17. Programmability of Chemical Reaction Networks

    Science.gov (United States)

    Cook, Matthew; Soloveichik, David; Winfree, Erik; Bruck, Jehoshua

    Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and Boolean Logic Circuits, Vector Addition Systems, Petri nets, Gate Implementability, Primitive Recursive Functions, Register Machines, Fractran, and Turing Machines. A theme to these investigations is the thin line between decidable and undecidable questions about SCRN behavior.

  18. The Interplay of Intrinsic and Extrinsic Bounded Noises in Biomolecular Networks

    OpenAIRE

    Caravagna, G; Mauri, G; D'Onofrio, A.

    2013-01-01

    After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbation...

  19. Modeling and Analysis of Abnormality Detection in Biomolecular Nano-Networks

    OpenAIRE

    Ghavami, Siavash; Lahouti, Farshad; Masoudi-Nejad, Ali

    2012-01-01

    A scheme for detection of abnormality in molecular nano-networks is proposed. This is motivated by the fact that early diagnosis, classification and detection of diseases such as cancer play a crucial role in their successful treatment. The proposed nano-abnormality detection scheme (NADS) comprises of a two-tier network of sensor nano-machines (SNMs) in the first tier and a data gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells as abnormality that is captured...

  20. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Directory of Open Access Journals (Sweden)

    Recep Colak

    Full Text Available BACKGROUND: Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. METHODOLOGY/PRINCIPAL FINDINGS: We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. CONCLUSION/SIGNIFICANCE: We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze

  1. Modeling and Analysis of Abnormality Detection in Biomolecular Nano-Networks

    CERN Document Server

    Ghavami, Siavash; Masoudi-Nejad, Ali

    2012-01-01

    A scheme for detection of abnormality in molecular nano-networks is proposed. This is motivated by the fact that early diagnosis, classification and detection of diseases such as cancer play a crucial role in their successful treatment. The proposed nano-abnormality detection scheme (NADS) comprises of a two-tier network of sensor nano-machines (SNMs) in the first tier and a data gathering node (DGN) at the sink. The SNMs detect the presence of competitor cells as abnormality that is captured by variations in parameters of a nano-communications channel. In the second step, the SNMs transmit micro-scale messages over a noisy micro communications channel (MCC) to the DGN, where a decision is made upon fusing the received signals. The detection performance of each SNM is analyzed by setting up a Neyman-Pearson test. Next, taking into account the effect of the MCC, the overall performance of the proposed NADS is quantified in terms of probabilities of misdetection and false alarm. A design problem is formulated, ...

  2. Network theory approach for data evaluation in the dynamic force spectroscopy of biomolecular interactions

    Science.gov (United States)

    Živković, J.; Mitrović, M.; Janssen, L.; Heus, H. A.; Tadić, B.; Speller, S.

    2010-03-01

    Investigations of bonds between single molecules and molecular complexes by dynamic force spectroscopy are subject to large fluctuations at nanoscale and possible aspecific binding, which mask the experimental output. Big efforts are devoted to develop methods for the effective selection of the relevant experimental data, before the quantitative analysis of bond parameters. Here we present a methodology which is based on the application of graph theory. The force-distance curves corresponding to repeated pulling events are mapped onto their correlation network (mathematical graph). On these graphs the groups of similar curves appear as topological modules, which are identified using the spectral analysis of graphs. We demonstrate the approach by analyzing a large ensemble of the force-distance curves measured on: ssDNA-ssDNA, peptide-RNA (from HIV1), and peptide-Au surface systems. Within our data sets the methodology systematically separates subgroups of curves which are related to different types of intermolecular interactions and to spatial arrangements in which the molecules are brought together and/or pulling speeds. This demonstrates the sensitivity of the method to the spatial degrees of freedom, suggesting potential applications in the case of large molecular complexes and situations with multiple binding sites.

  3. Genetic Recombination as a Chemical Reaction Network

    OpenAIRE

    Müller, Stefan; Hofbauer, Josef

    2015-01-01

    The process of genetic recombination can be seen as a chemical reaction network with mass-action kinetics. We review the known results on existence, uniqueness, and global stability of an equilibrium in every compatibility class and for all rate constants, from both the population genetics and the reaction networks point of view.

  4. Stochastic thermodynamics of chemical reaction networks

    OpenAIRE

    Schmiedl, Tim; Seifert, Udo

    2006-01-01

    For chemical reaction networks described by a master equation, we define energy and entropy on a stochastic trajectory and develop a consistent nonequilibrium thermodynamic description along a single stochastic trajectory of reaction events. A first-law like energy balance relates internal energy, applied (chemical) work and dissipated heat for every single reaction. Entropy production along a single trajectory involves a sum over changes in the entropy of the network itself and the entropy o...

  5. A network dynamics approach to chemical reaction networks

    NARCIS (Netherlands)

    van der Schaft, Abraham; Rao, S.; Jayawardhana, B.

    2016-01-01

    A treatment of chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a ve

  6. Limits for Stochastic Reaction Networks

    DEFF Research Database (Denmark)

    Cappelletti, Daniele

    Reaction systems have been introduced in the 70s to model biochemical systems. Nowadays their range of applications has increased and they are fruitfully used in dierent elds. The concept is simple: some chemical species react, the set of chemical reactions form a graph and a rate function is...... associated with each reaction. Such functions describe the speed of the dierent reactions, or their propensities. Two modelling regimes are then available: the evolution of the dierent species concentrations can be deterministically modelled through a system of ODE, while the counts of the dierent species at...... a certain time are stochastically modelled by means of a continuous-time Markov chain. Our work concerns primarily stochastic reaction systems, and their asymptotic properties. In Paper I, we consider a reaction system with intermediate species, i.e. species that are produced and fast degraded along...

  7. Multilayer Network Analysis of Nuclear Reactions.

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, (4)He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  8. Multilayer Network Analysis of Nuclear Reactions

    Science.gov (United States)

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  9. Multilayer network analysis of nuclear reactions

    CERN Document Server

    Zhu, Liang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, $^4$He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the $\\beta$-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart.

  10. Programming in Biomolecular Computation

    DEFF Research Database (Denmark)

    Hartmann, Lars; Jones, Neil; Simonsen, Jakob Grue

    2010-01-01

    Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We introduce a model of computation that is evidently programmable......, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only...... in a strong sense: a universal algorithm exists, that is able to execute any program, and is not asymptotically inefficient. A prototype model has been implemented (for now in silico on a conventional computer). This work opens new perspectives on just how computation may be specified at the biological level....

  11. Law of Localization in Chemical Reaction Networks

    Science.gov (United States)

    Okada, Takashi; Mochizuki, Atsushi

    2016-07-01

    In living cells, chemical reactions are connected by sharing their products and substrates, and form complex networks, e.g., metabolic pathways. Here we developed a theory to predict the sensitivity, i.e., the responses of concentrations and fluxes to perturbations of enzymes, from network structure alone. Nonzero response patterns turn out to exhibit two characteristic features, localization and hierarchy. We present a general theorem connecting sensitivity with network topology that explains these characteristic patterns. Our results imply that network topology is an origin of biological robustness. Finally, we suggest a strategy to determine real networks from experimental measurements.

  12. Law of localization in chemical reaction networks

    CERN Document Server

    Okada, Takashi

    2016-01-01

    In living cells, chemical reactions are connected by sharing their products and substrates, and form complex networks, e.g. metabolic pathways. Here we developed a theory to predict the sensitivity, i.e. the responses of concentrations and fluxes to perturbations of enzymes, from network structure alone. Responses turn out to exhibit two characteristic patterns, $localization$ and $hierarchy$. We present a general theorem connecting sensitivity with network topology that explains these characteristic patterns. Our results imply that network topology is an origin of biological robustness. Finally, we suggest a strategy to determine real networks from experimental measurements.

  13. Markovian Dynamics on Complex Reaction Networks

    CERN Document Server

    Goutsias, John

    2012-01-01

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underling population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions, the computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating...

  14. Markovian dynamics on complex reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Goutsias, J., E-mail: goutsias@jhu.edu; Jenkinson, G., E-mail: jenkinson@jhu.edu

    2013-08-10

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

  15. Markovian dynamics on complex reaction networks

    Science.gov (United States)

    Goutsias, J.; Jenkinson, G.

    2013-08-01

    Complex networks, comprised of individual elements that interact with each other through reaction channels, are ubiquitous across many scientific and engineering disciplines. Examples include biochemical, pharmacokinetic, epidemiological, ecological, social, neural, and multi-agent networks. A common approach to modeling such networks is by a master equation that governs the dynamic evolution of the joint probability mass function of the underlying population process and naturally leads to Markovian dynamics for such process. Due however to the nonlinear nature of most reactions and the large size of the underlying state-spaces, computation and analysis of the resulting stochastic population dynamics is a difficult task. This review article provides a coherent and comprehensive coverage of recently developed approaches and methods to tackle this problem. After reviewing a general framework for modeling Markovian reaction networks and giving specific examples, the authors present numerical and computational techniques capable of evaluating or approximating the solution of the master equation, discuss a recently developed approach for studying the stationary behavior of Markovian reaction networks using a potential energy landscape perspective, and provide an introduction to the emerging theory of thermodynamic analysis of such networks. Three representative problems of opinion formation, transcription regulation, and neural network dynamics are used as illustrative examples.

  16. A network dynamics approach to chemical reaction networks

    Science.gov (United States)

    van der Schaft, A. J.; Rao, S.; Jayawardhana, B.

    2016-04-01

    A treatment of a chemical reaction network theory is given from the perspective of nonlinear network dynamics, in particular of consensus dynamics. By starting from the complex-balanced assumption, the reaction dynamics governed by mass action kinetics can be rewritten into a form which allows for a very simple derivation of a number of key results in the chemical reaction network theory, and which directly relates to the thermodynamics and port-Hamiltonian formulation of the system. Central in this formulation is the definition of a balanced Laplacian matrix on the graph of chemical complexes together with a resulting fundamental inequality. This immediately leads to the characterisation of the set of equilibria and their stability. Furthermore, the assumption of complex balancedness is revisited from the point of view of Kirchhoff's matrix tree theorem. Both the form of the dynamics and the deduced behaviour are very similar to consensus dynamics, and provide additional perspectives to the latter. Finally, using the classical idea of extending the graph of chemical complexes by a 'zero' complex, a complete steady-state stability analysis of mass action kinetics reaction networks with constant inflows and mass action kinetics outflows is given, and a unified framework is provided for structure-preserving model reduction of this important class of open reaction networks.

  17. Deciphering Time Scale Hierarchy in Reaction Networks.

    Science.gov (United States)

    Nagahata, Yutaka; Maeda, Satoshi; Teramoto, Hiroshi; Horiyama, Takashi; Taketsugu, Tetsuya; Komatsuzaki, Tamiki

    2016-03-01

    Markovian dynamics on complex reaction networks are one of the most intriguing subjects in a wide range of research fields including chemical reactions, biological physics, and ecology. To represent the global kinetics from one node (corresponding to a basin on an energy landscape) to another requires information on multiple pathways that directly or indirectly connect these two nodes through the entire network. In this paper we present a scheme to extract a hierarchical set of global transition states (TSs) over a discrete-time Markov chain derived from first-order rate equations. The TSs can naturally take into account the multiple pathways connecting any pair of nodes. We also propose a new type of disconnectivity graph (DG) to capture the hierarchical organization of different time scales of reactions that can capture changes in the network due to changes in the time scale of observation. The crux is the introduction of the minimum conductance cut (MCC) in graph clustering, corresponding to the dividing surface across the network having the "smallest" transition probability between two disjoint subnetworks (superbasins on the energy landscape) in the network. We present a new combinatorial search algorithm for finding this MCC. We apply our method to a reaction network of Claisen rearrangement of allyl vinyl ether that consists of 23 nodes and 66 links (saddles on the energy landscape) connecting them. We compare the kinetic properties of our DG to those of the transition matrix of the rate equations and show that our graph can properly reveal the hierarchical organization of time scales in a network. PMID:26641663

  18. An updated nuclear reaction network for BBN

    OpenAIRE

    Serpico, P. D.

    2004-01-01

    The key Standard-Physics inputs of the Big Bang Nucleosynthesis (BBN) are the light nuclei reaction rates. Both the network and the nuclear rates have been recently reanalyzed and updated, and cosmological and New-Physics constraints (taking into account the WMAP Cosmic Microwave Background anisotropies measurement) obtained with a new code are presented.

  19. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou

    2011-09-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

  20. Catalytic reaction dynamics in inhomogeneous networks.

    Science.gov (United States)

    Watanabe, Akitomo; Yakubo, Kousuke

    2014-05-01

    Biochemical reactions in a cell can be modeled by a catalytic reaction network (CRN). It has been reported that catalytic chain reactions occur intermittently in the CRN with a homogeneous random-graph topology and its avalanche-size distribution obeys a power law with the exponent 4/3 [A. Awazu and K. Kaneko, Phys. Rev. E 80, 010902(R) (2009)]. This fact indicates that the catalytic reaction dynamics in homogeneous CRNs exhibits self-organized criticality (SOC). Structures of actual CRNs are, however, known to be highly inhomogeneous. We study the influence of various types of inhomogeneities found in real-world metabolic networks on the universality class of SOC. Our numerical results clarify that SOC keeps its universality class even for networks possessing structural inhomogeneities such as the scale-free property, community structures, and degree correlations. In contrast, if the CRN has inhomogeneous catalytic functionality, the universality class of SOC depends on how widely distributed the number of reaction paths catalyzed by a single chemical species is. PMID:25353843

  1. Biomolecular Science (Fact Sheet)

    Energy Technology Data Exchange (ETDEWEB)

    2012-04-01

    A brief fact sheet about NREL Photobiology and Biomolecular Science. The research goal of NREL's Biomolecular Science is to enable cost-competitive advanced lignocellulosic biofuels production by understanding the science critical for overcoming biomass recalcitrance and developing new product and product intermediate pathways. NREL's Photobiology focuses on understanding the capture of solar energy in photosynthetic systems and its use in converting carbon dioxide and water directly into hydrogen and advanced biofuels.

  2. Performance Improvements for Nuclear Reaction Network Integration

    CERN Document Server

    Longland, Richard; José, Jordi

    2014-01-01

    Aims: The aim of this work is to compare the performance of three reaction network integration methods used in stellar nucleosynthesis calculations. These are the Gear's backward differentiation method, Wagoner's method (a 2nd-order Runge-Kutta method), and the Bader-Deuflehard semi-implicit multi-step method. Methods: To investigate the efficiency of each of the integration methods considered here, a test suite of temperature and density versus time profiles is used. This suite provides a range of situations ranging from constant temperature and density to the dramatically varying conditions present in white dwarf mergers, novae, and x-ray bursts. Some of these profiles are obtained separately from full hydrodynamic calculations. The integration efficiencies are investigated with respect to input parameters that constrain the desired accuracy and precision. Results: Gear's backward differentiation method is found to improve accuracy, performance, and stability in integrating nuclear reaction networks. For te...

  3. Neural Networks in Chemical Reaction Dynamics

    CERN Document Server

    Raff, Lionel; Hagan, Martin

    2011-01-01

    This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic

  4. Ubiquitous "glassy" relaxation in catalytic reaction networks

    OpenAIRE

    Awazu, Akinori; Kaneko, Kunihiko

    2009-01-01

    Study of reversible catalytic reaction networks is important not only as an issue for chemical thermodynamics but also for protocells. From extensive numerical simulations and theoretical analysis, slow relaxation dynamics to sustain nonequlibrium states are commonly observed. These dynamics show two types of salient behaviors that are reminiscent of glassy behavior: slow relaxation along with the logarithmic time dependence of the correlation function and the emergence of plateaus in the rel...

  5. Ubiquitous ``glassy'' relaxation in catalytic reaction networks

    Science.gov (United States)

    Awazu, Akinori; Kaneko, Kunihiko

    2009-10-01

    Study of reversible catalytic reaction networks is important not only as an issue for chemical thermodynamics but also for protocells. From extensive numerical simulations and theoretical analysis, slow relaxation dynamics to sustain nonequlibrium states are commonly observed. These dynamics show two types of salient behaviors that are reminiscent of glassy behavior: slow relaxation along with the logarithmic time dependence of the correlation function and the emergence of plateaus in the relaxation-time course. The former behavior is explained by the eigenvalue distribution of a Jacobian matrix around the equilibrium state that depends on the distribution of kinetic coefficients of reactions. The latter behavior is associated with kinetic constraints rather than metastable states and is due to the absence of catalysts for chemicals in excess and the negative correlation between two chemical species. Examples are given and generality is discussed with relevance to bottleneck-type dynamics in biochemical reactions as well.

  6. From Catalytic Reaction Networks to Protocells

    Science.gov (United States)

    Kaneko, Kunihiko

    2013-12-01

    In spite of recent advances, there still remains a large gape between a set of chemical reactions and a biological cell. Here we discuss several theoretical efforts to fill in the gap. The topics cover (i) slow relaxation to equilibrium due to glassy behavior in catalytic reaction networks (ii) consistency between molecule replication and cell growth, as well as energy metabolism (iii) control of a system by minority molecules in mutually catalytic system, which work as a carrier of genetic information, and leading to evolvability (iv) generation of a compartmentalized structure as a cluster of molecules centered around the minority molecule, and division of the cluster accompanied by the replication of minority molecule (v) sequential, logical process over several states from concurrent reaction dynamics, by taking advantage of discreteness in molecule number.

  7. The functional interactome of GSTP: A regulatory biomolecular network at the interface with the Nrf2 adaption response to oxidative stress.

    Science.gov (United States)

    Bartolini, Desirée; Galli, Francesco

    2016-04-15

    Glutathione S-transferase P (GSTP), and possibly other members of the subfamily of cytosolic GSTs, are increasingly proposed to have roles far beyond the classical GSH-dependent enzymatic detoxification of electrophilic metabolites and xenobiotics. Emerging evidence suggests that these are essential components of the redox sensing and signaling platform of cells. GSTP monomers physically interact with cellular proteins, such as other cytosolic GSTs, signaling kinases and the membrane peroxidase peroxiredoxin 6. Other interactions reported in literature include that with regulatory proteins such as Fanconi anemia complementation group C protein, transglutaminase 2 and several members of the keratin family of genes. Transcription factors downstream of inflammatory and oxidative stress pathways, namely STAT3 and Nrf2, were recently identified to be further components of this interactome. Together these pieces of evidence suggest the existence of a regulatory biomolecular network in which GSTP represents a node of functional convergence and coordination of signaling and transcription proteins, namely the "GSTP interactome", associated with key cellular processes such as cell cycle regulation and the stress response. These aspects and the methodological approach to explore the cellular interactome(s) are discussed in this review paper. PMID:26922696

  8. Graphical reduction of reaction networks by linear elimination of species

    DEFF Research Database (Denmark)

    Sáez, Meritxell; Wiuf, Carsten; Feliu, Elisenda

    2015-01-01

    We give a graphically based procedure to reduce a reaction network to a smaller reaction network with fewer species after linear elimination of a set of noninteracting species. We give a description of the reduced reaction network, its kinetics and conservations laws, and explore properties of the...

  9. Discreteness-Induced Criticality in Random Catalytic Reaction Networks

    OpenAIRE

    Awazu, Akinori; Kaneko, Kunihiko

    2009-01-01

    Universal intermittent dynamics in a random catalytic reaction network, induced by smallness in the molecule number is reported. Stochastic simulations for a random catalytic reaction network subject to a flow of chemicals show that the system undergoes a transition from a stationary to an intermittent reaction phase when the flow rate is decreased. In the intermittent reaction phase, two temporal regimes with active and halted reactions alternate. The number frequency of reaction events at e...

  10. Poisson-Nernst-Planck equations for simulating biomolecular diffusion-reaction processes II: size effects on ionic distributions and diffusion-reaction rates.

    Science.gov (United States)

    Lu, Benzhuo; Zhou, Y C

    2011-05-18

    The effects of finite particle size on electrostatics, density profiles, and diffusion have been a long existing topic in the study of ionic solution. The previous size-modified Poisson-Boltzmann and Poisson-Nernst-Planck models are revisited in this article. In contrast to many previous works that can only treat particle species with a single uniform size or two sizes, we generalize the Borukhov model to obtain a size-modified Poisson-Nernst-Planck (SMPNP) model that is able to treat nonuniform particle sizes. The numerical tractability of the model is demonstrated as well. The main contributions of this study are as follows. 1), We show that an (arbitrarily) size-modified PB model is indeed implied by the SMPNP equations under certain boundary/interface conditions, and can be reproduced through numerical solutions of the SMPNP. 2), The size effects in the SMPNP effectively reduce the densities of highly concentrated counterions around the biomolecule. 3), The SMPNP is applied to the diffusion-reaction process for the first time, to our knowledge. In the case of low substrate density near the enzyme reactive site, it is observed that the rate coefficients predicted by SMPNP model are considerably larger than those by the PNP model, suggesting both ions and substrates are subject to finite size effects. 4), An accurate finite element method and a convergent Gummel iteration are developed for the numerical solution of the completely coupled nonlinear system of SMPNP equations. PMID:21575582

  11. Poisson-Nernst-Planck Equations for Simulating Biomolecular Diffusion-Reaction Processes II: Size Effects on Ionic Distributions and Diffusion-Reaction Rates

    Science.gov (United States)

    Lu, Benzhuo; Zhou, Y.C.

    2011-01-01

    The effects of finite particle size on electrostatics, density profiles, and diffusion have been a long existing topic in the study of ionic solution. The previous size-modified Poisson-Boltzmann and Poisson-Nernst-Planck models are revisited in this article. In contrast to many previous works that can only treat particle species with a single uniform size or two sizes, we generalize the Borukhov model to obtain a size-modified Poisson-Nernst-Planck (SMPNP) model that is able to treat nonuniform particle sizes. The numerical tractability of the model is demonstrated as well. The main contributions of this study are as follows. 1), We show that an (arbitrarily) size-modified PB model is indeed implied by the SMPNP equations under certain boundary/interface conditions, and can be reproduced through numerical solutions of the SMPNP. 2), The size effects in the SMPNP effectively reduce the densities of highly concentrated counterions around the biomolecule. 3), The SMPNP is applied to the diffusion-reaction process for the first time, to our knowledge. In the case of low substrate density near the enzyme reactive site, it is observed that the rate coefficients predicted by SMPNP model are considerably larger than those by the PNP model, suggesting both ions and substrates are subject to finite size effects. 4), An accurate finite element method and a convergent Gummel iteration are developed for the numerical solution of the completely coupled nonlinear system of SMPNP equations. PMID:21575582

  12. Open complex-balanced mass action chemical reaction networks

    NARCIS (Netherlands)

    Rao, Shodhan; van der Schaft, Arjan; Jayawardhana, Bayu

    2014-01-01

    We consider open chemical reaction networks, i.e. ones with inflows and outflows. We assume that all the inflows to the network are constant and all outflows obey the mass action kinetics rate law. We define a complex-balanced open reaction network as one that admits a complex-balanced steady state.

  13. Nanoconfined β-sheets mechanically reinforce the supra-biomolecular network of robust squid Sucker Ring Teeth.

    Science.gov (United States)

    Guerette, Paul A; Hoon, Shawn; Ding, Dawei; Amini, Shahrouz; Masic, Admir; Ravi, Vydianathan; Venkatesh, Byrappa; Weaver, James C; Miserez, Ali

    2014-07-22

    The predatory efficiency of squid and cuttlefish (superorder Decapodiformes) is enhanced by robust Sucker Ring Teeth (SRT) that perform grappling functions during prey capture. Here, we show that SRT are composed entirely of related structural “suckerin” proteins whose modular designs enable the formation of nanoconfined β-sheet-reinforced polymer networks. Thirty-seven previously undiscovered suckerins were identified from transcriptomes assembled from three distantly related decapodiform cephalopods. Similarity in modular sequence design and exon–intron architecture suggests that suckerins are encoded by a multigene family. Phylogenetic analysis supports this view, revealing that suckerin genes originated in a common ancestor ~350 MYa and indicating that nanoconfined β-sheet reinforcement is an ancient strategy to create robust bulk biomaterials. X-ray diffraction, nanomechanical, and micro-Raman spectroscopy measurements confirm that the modular design of the suckerins facilitates the formation of β-sheets of precise nanoscale dimensions and enables their assembly into structurally robust supramolecular networks stabilized by cooperative hydrogen bonding. The suckerin gene family has likely played a key role in the evolutionary success of decapodiform cephalopods and provides a large molecular toolbox for biomimetic materials engineering. PMID:24911543

  14. New techniques for integrating nuclear reaction networks

    International Nuclear Information System (INIS)

    The development of high resolution stellar models in multiple dimensions has moved us one step closer to answering fundamental questions of how stars burn their fuel. These models rely on solving a computationally expensive set of conservation, transportation, and energy production equations, the latter of which is determined by a complex network of nuclear reactions. The size of this network is constrained by the nature of the stellar environment in question and whether detailed nucleosynthesis yields are required. Alternatively, the nucleosynthesis yields can be computed by decoupling the calculation into a post-processing nucleosynthesis part, which relies on the output of a simplified hydrodynamics-focused calculation. Here, we investigate improving post-processing calculation performance by using more advanced integration methods than those typically adopted in nuclear astrophysics research. These are the Bader-Deuflehard multi-step method and the Gear backward differentiation method, which are compared with the traditional Wagoner two-step method. Integration method performance is quantified for a range of stellar environment models including Novae, X-ray bursts, hydrostatic core helium burning, and explosive hydrogen-helium burning in white dwarf merger events. We show that by using these methods, nucleosynthesis integration accuracy can be greatly improved and computation time can be significantly reduced by up to two orders of magnitude. Applicability of the integration methods to full hydrodynamical models will also be outlined. (author)

  15. Role of biomolecular logic systems in biosensors and bioactuators

    Science.gov (United States)

    Mailloux, Shay; Katz, Evgeny

    2014-09-01

    An overview of recent advances in biosensors and bioactuators based on biocomputing systems is presented. Biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce an output in the form of a YES/NO response. Compared to traditional single-analyte sensing devices, the biocomputing approach enables high-fidelity multianalyte biosensing, which is particularly beneficial for biomedical applications. Multisignal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert medical personnel of medical emergencies together with immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly as exemplified for liver injury. Wide-ranging applications of multianalyte digital biosensors in medicine, environmental monitoring, and homeland security are anticipated. "Smart" bioactuators, for signal-triggered drug release, for example, were designed by interfacing switchable electrodes with biocomputing systems. Integration of biosensing and bioactuating systems with biomolecular information processing systems advances the potential for further scientific innovations and various practical applications.

  16. Biomolecular logic systems: applications to biosensors and bioactuators

    Science.gov (United States)

    Katz, Evgeny

    2014-05-01

    The paper presents an overview of recent advances in biosensors and bioactuators based on the biocomputing concept. Novel biosensors digitally process multiple biochemical signals through Boolean logic networks of coupled biomolecular reactions and produce output in the form of YES/NO response. Compared to traditional single-analyte sensing devices, biocomputing approach enables a high-fidelity multi-analyte biosensing, particularly beneficial for biomedical applications. Multi-signal digital biosensors thus promise advances in rapid diagnosis and treatment of diseases by processing complex patterns of physiological biomarkers. Specifically, they can provide timely detection and alert to medical emergencies, along with an immediate therapeutic intervention. Application of the biocomputing concept has been successfully demonstrated for systems performing logic analysis of biomarkers corresponding to different injuries, particularly exemplified for liver injury. Wide-ranging applications of multi-analyte digital biosensors in medicine, environmental monitoring and homeland security are anticipated. "Smart" bioactuators, for example for signal-triggered drug release, were designed by interfacing switchable electrodes and biocomputing systems. Integration of novel biosensing and bioactuating systems with the biomolecular information processing systems keeps promise for further scientific advances and numerous practical applications.

  17. Deterministic Function Computation with Chemical Reaction Networks

    CERN Document Server

    Chen, Ho-Lin; Soloveichik, David

    2012-01-01

    We study the deterministic computation of functions on tuples of natural numbers by chemical reaction networks (CRNs). CRNs have been shown to be efficiently Turing-universal when allowing for a small probability of error. CRNs that are guaranteed to converge on a correct answer, on the other hand, have been shown to decide only the semilinear predicates. We introduce the notion of function, rather than predicate, computation by representing the output of a function f:N^k --> N^l by a count of some molecular species, i.e., if the CRN starts with n_1,...,n_k molecules of some "input" species X_1,...,X_k, the CRN is guaranteed to converge to having f(n_1,...,n_k) molecules of the "output" species Y_1,...,Y_l. We show that a function f:N^k --> N^l is deterministically computed by a CRN if and only if its graph {(x,y) \\in N^k x N^l | f(x) = y} is a semilinear set. Finally, we show that each semilinear function f can be computed on input x in expected time O(polylog |x|).

  18. Mixture of experts models to exploit global sequence similarity on biomolecular sequence labeling

    OpenAIRE

    2009-01-01

    Background Identification of functionally important sites in biomolecular sequences has broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks. Experimental determination of such sites lags far behind the number of known biomolecular sequences. Hence, there is a need to develop reliable computational methods for identifying functionally important sites from biomolecular sequences. Results We present a mixture of experts approach to b...

  19. Membrane-based biomolecular smart materials

    International Nuclear Information System (INIS)

    Membrane-based biomolecular materials are a new class of smart material that feature networks of artificial lipid bilayers contained within durable synthetic substrates. Bilayers contained within this modular material platform provide an environment that can be tailored to host an enormous diversity of functional biomolecules, where the functionality of the global material system depends on the type(s) and organization(s) of the biomolecules that are chosen. In this paper, we review a series of biomolecular material platforms developed recently within the Leo Group at Virginia Tech and we discuss several novel coupling mechanisms provided by these hybrid material systems. The platforms developed demonstrate that the functions of biomolecules and the properties of synthetic materials can be combined to operate in concert, and the examples provided demonstrate how the formation and properties of a lipid bilayer can respond to a variety of stimuli including mechanical forces and electric fields

  20. Biomolecular EPR spectroscopy

    CERN Document Server

    Hagen, Wilfred Raymond

    2008-01-01

    Comprehensive, Up-to-Date Coverage of Spectroscopy Theory and its Applications to Biological SystemsAlthough a multitude of books have been published about spectroscopy, most of them only occasionally refer to biological systems and the specific problems of biomolecular EPR (bioEPR). Biomolecular EPR Spectroscopy provides a practical introduction to bioEPR and demonstrates how this remarkable tool allows researchers to delve into the structural, functional, and analytical analysis of paramagnetic molecules found in the biochemistry of all species on the planet. A Must-Have Reference in an Intrinsically Multidisciplinary FieldThis authoritative reference seamlessly covers all important bioEPR applications, including low-spin and high-spin metalloproteins, spin traps and spin lables, interaction between active sites, and redox systems. It is loaded with practical tricks as well as do's and don'ts that are based on the author's 30 years of experience in the field. The book also comes with an unprecedented set of...

  1. On the Complexity of Reconstructing Chemical Reaction Networks

    DEFF Research Database (Denmark)

    Fagerberg, Rolf; Flamm, Christoph; Merkle, Daniel;

    2013-01-01

    The analysis of the structure of chemical reaction networks is crucial for a better understanding of chemical processes. Such networks are well described as hypergraphs. However, due to the available methods, analyses regarding network properties are typically made on standard graphs derived from...... the full hypergraph description, e.g. on the so-called species and reaction graphs. However, a reconstruction of the underlying hypergraph from these graphs is not necessarily unique. In this paper, we address the problem of reconstructing a hypergraph from its species and reaction graph and show NP...

  2. Weber's Law in Autocatalytic Reaction Networks

    OpenAIRE

    Inoue, Masayo; Kaneko, Kunihiko

    2011-01-01

    Biological responses often obey Weber's law, according to which the magnitude of the response depends only on the fold change in the external input. In this study, we demonstrate that a system involving a simple autocatalytic reaction shows such response when a chemical is slowly synthesized by the reaction from a faster influx process. We also show that an autocatalytic reaction process occurring in series or in parallel can obey Weber's law with an oscillatory adaptive response. Considering...

  3. Neural networks for the prediction organic chemistry reactions

    CERN Document Server

    Wei, Jennifer N; Aspuru-Guzik, Alán

    2016-01-01

    Reaction prediction remains one of the great challenges for organic chemistry. Solving this problem computationally requires the programming of a vast amount of knowledge and intuition of the rules of organic chemistry and the development of algorithms for their application. It is desirable to develop algorithms that, like humans, "learn" from being exposed to examples of the application of the rules of organic chemistry. In this work, we introduce a novel algorithm for predicting the products of organic chemistry reactions using machine learning to first identify the reaction type. In particular, we trained deep convolutional neural networks to predict the outcome of reactions based example reactions, using a new reaction fingerprint model. Due to the flexibility of neural networks, the system can attempt to predict reactions outside the domain where it was trained. We test this capability on problems from a popular organic chemistry textbook.

  4. Output-input ratio in thermally fluctuating biomolecular machines.

    Science.gov (United States)

    Kurzynski, Michal; Torchala, Mieczyslaw; Chelminiak, Przemyslaw

    2014-01-01

    Biological molecular machines are proteins that operate under isothermal conditions and hence are referred to as free energy transducers. They can be formally considered as enzymes that simultaneously catalyze two chemical reactions: the free energy-donating (input) reaction and the free energy-accepting (output) one. Most if not all biologically active proteins display a slow stochastic dynamics of transitions between a variety of conformational substates composing their native state. This makes the description of the enzymatic reaction kinetics in terms of conventional rate constants insufficient. In the steady state, upon taking advantage of the assumption that each reaction proceeds through a single pair (the gate) of transition conformational substates of the enzyme-substrates complex, the degree of coupling between the output and the input reaction fluxes has been expressed in terms of the mean first-passage times on a conformational transition network between the distinguished substates. The theory is confronted with the results of random-walk simulations on the five-dimensional hypercube. The formal proof is given that, for single input and output gates, the output-input degree of coupling cannot exceed unity. As some experiments suggest such exceeding, looking for the conditions for increasing the degree of coupling value over unity challenges the theory. Performed simulations of random walks on several model networks involving more extended gates indicate that the case of the degree of coupling value higher than 1 is realized in a natural way on critical branching trees extended by long-range shortcuts. Such networks are scale-free and display the property of the small world. For short-range shortcuts, the networks are scale-free and fractal, representing a reasonable model for biomolecular machines displaying tight coupling, i.e., the degree of coupling equal exactly to unity. A hypothesis is stated that the protein conformational transition networks, as

  5. DNA reaction networks: Providing a panoramic view

    Science.gov (United States)

    Wang, Fei; Fan, Chunhai

    2016-08-01

    A quantitative understanding of the functional landscape of a biochemical circuit can reveal the design rules required to optimize the circuit. Now, a high-throughput droplet-based microfluidic platform has been developed which enables high-resolution mapping of bifurcation diagrams for two nonlinear DNA networks.

  6. Analyzing biomolecular interactions by variable angle ellipsometry

    Science.gov (United States)

    Wu, Jiun-Yan; Lee, Chih-Kung; Lee, J. H.; Shiue, Shuen-Chen; Lee, Shu-Sheng; Lin, Shiming

    2001-10-01

    In this paper, an innovative ellipsometer is developed and applied to metrology of the biomolecular interaction on a protein biochip. Both the theory, optical and opto-mechanical configurations of this newly developed ellipsometer and methodologies adopted in system design to improve the system performance are presented. It will be shown that by measuring the ellipsometric parameters, the corresponding concentration variation in biochemical reaction can be calculated according to stoichiometry analysis. By applying the variable angle ellipsometry to analysis of a multi-layered sample, the thickness and concentration are resolved. It is believed that the newly developed ellipsometer biosensor is able to undertake an accurate measurement on biomedical interaction.

  7. Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

    Science.gov (United States)

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis. PMID:26495292

  8. Turing instability in reaction-diffusion models on complex networks

    Science.gov (United States)

    Ide, Yusuke; Izuhara, Hirofumi; Machida, Takuya

    2016-09-01

    In this paper, the Turing instability in reaction-diffusion models defined on complex networks is studied. Here, we focus on three types of models which generate complex networks, i.e. the Erdős-Rényi, the Watts-Strogatz, and the threshold network models. From analysis of the Laplacian matrices of graphs generated by these models, we numerically reveal that stable and unstable regions of a homogeneous steady state on the parameter space of two diffusion coefficients completely differ, depending on the network architecture. In addition, we theoretically discuss the stable and unstable regions in the cases of regular enhanced ring lattices which include regular circles, and networks generated by the threshold network model when the number of vertices is large enough.

  9. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen; Ülgen, Kutlu Özergin; Kirdar, Betül; Nielsen, Jens

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

  10. Cellular Metabolic Network Analysis: Discovering Important Reactions in Treponema pallidum

    OpenAIRE

    Xueying Chen; Min Zhao; Hong Qu

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pall...

  11. ARWAR: A network approach for predicting Adverse Drug Reactions.

    Science.gov (United States)

    Rahmani, Hossein; Weiss, Gerhard; Méndez-Lucio, Oscar; Bender, Andreas

    2016-01-01

    Predicting novel drug side-effects, or Adverse Drug Reactions (ADRs), plays an important role in the drug discovery process. Existing methods consider mainly the chemical and biological characteristics of each drug individually, thereby neglecting information hidden in the relationships among drugs. Complementary to the existing individual methods, in this paper, we propose a novel network approach for ADR prediction that is called Augmented Random-WAlk with Restarts (ARWAR). ARWAR, first, applies an existing method to build a network of highly related drugs. Then, it augments the original drug network by adding new nodes and new edges to the network and finally, it applies Random Walks with Restarts to predict novel ADRs. Empirical results show that the ARWAR method presented here outperforms the existing network approach by 20% with respect to average Fmeasure. Furthermore, ARWAR is capable of generating novel hypotheses about drugs with respect to novel and biologically meaningful ADR. PMID:26638149

  12. On the steady states of weakly reversible chemical reaction networks

    OpenAIRE

    Deng, Jian; Jones, Christopher; Feinberg, Martin; Nachman, Adrian

    2011-01-01

    A natural condition on the structure of the underlying chemical reaction network, namely weak reversibility, is shown to guarantee the existence of an equilibrium (steady state) in each positive stoichiometric compatibility class for the associated mass-action system. Furthermore, an index formula is given for the set of equilibria in a given stoichiometric compatibility class.

  13. Injectivity, multiple zeros, and multistationarity in reaction networks

    DEFF Research Database (Denmark)

    Feliu, Elisenda

    2015-01-01

    Polynomial dynamical systems are widely used to model and study real phenomena. In biochemistry, they are the preferred choice for modelling the concentration of chemical species in reaction networks with mass-action kinetics. These systems are typically parametrized by many (unknown) parameters....

  14. Molecular codes in biological and chemical reaction networks.

    Directory of Open Access Journals (Sweden)

    Dennis Görlich

    Full Text Available Shannon's theory of communication has been very successfully applied for the analysis of biological information. However, the theory neglects semantic and pragmatic aspects and thus cannot directly be applied to distinguish between (bio- chemical systems able to process "meaningful" information from those that do not. Here, we present a formal method to assess a system's semantic capacity by analyzing a reaction network's capability to implement molecular codes. We analyzed models of chemical systems (martian atmosphere chemistry and various combustion chemistries, biochemical systems (gene expression, gene translation, and phosphorylation signaling cascades, an artificial chemistry, and random reaction networks. Our study suggests that different chemical systems possess different semantic capacities. No semantic capacity was found in the model of the martian atmosphere chemistry, the studied combustion chemistries, and highly connected random networks, i.e. with these chemistries molecular codes cannot be implemented. High semantic capacity was found in the studied biochemical systems and in random reaction networks where the number of second order reactions is twice the number of species. We conclude that our approach can be applied to evaluate the information processing capabilities of a chemical system and may thus be a useful tool to understand the origin and evolution of meaningful information, e.g. in the context of the origin of life.

  15. Complex and detailed balancing of chemical reaction networks revisited

    NARCIS (Netherlands)

    van der Schaft, Abraham; Rao, Shodhan; Jayawardhana, Bayu

    2015-01-01

    The characterization of the notions of complex and detailed balancing for mass action kinetics chemical reaction networks is revisited from the perspective of algebraic graph theory, in particular Kirchhoff’s Matrix Tree theorem for directed weighted graphs. This yields an elucidation of previously

  16. Chemical reaction network approaches to Biochemical Systems Theory.

    Science.gov (United States)

    Arceo, Carlene Perpetua P; Jose, Editha C; Marin-Sanguino, Alberto; Mendoza, Eduardo R

    2015-11-01

    This paper provides a framework to represent a Biochemical Systems Theory (BST) model (in either GMA or S-system form) as a chemical reaction network with power law kinetics. Using this representation, some basic properties and the application of recent results of Chemical Reaction Network Theory regarding steady states of such systems are shown. In particular, Injectivity Theory, including network concordance [36] and the Jacobian Determinant Criterion [43], a "Lifting Theorem" for steady states [26] and the comprehensive results of Müller and Regensburger [31] on complex balanced equilibria are discussed. A partial extension of a recent Emulation Theorem of Cardelli for mass action systems [3] is derived for a subclass of power law kinetic systems. However, it is also shown that the GMA and S-system models of human purine metabolism [10] do not display the reactant-determined kinetics assumed by Müller and Regensburger and hence only a subset of BST models can be handled with their approach. Moreover, since the reaction networks underlying many BST models are not weakly reversible, results for non-complex balanced equilibria are also needed. PMID:26363083

  17. Stochastic analysis of complex reaction networks using binomial moment equations.

    Science.gov (United States)

    Barzel, Baruch; Biham, Ofer

    2012-09-01

    The stochastic analysis of complex reaction networks is a difficult problem because the number of microscopic states in such systems increases exponentially with the number of reactive species. Direct integration of the master equation is thus infeasible and is most often replaced by Monte Carlo simulations. While Monte Carlo simulations are a highly effective tool, equation-based formulations are more amenable to analytical treatment and may provide deeper insight into the dynamics of the network. Here, we present a highly efficient equation-based method for the analysis of stochastic reaction networks. The method is based on the recently introduced binomial moment equations [Barzel and Biham, Phys. Rev. Lett. 106, 150602 (2011)]. The binomial moments are linear combinations of the ordinary moments of the probability distribution function of the population sizes of the interacting species. They capture the essential combinatorics of the reaction processes reflecting their stoichiometric structure. This leads to a simple and transparent form of the equations, and allows a highly efficient and surprisingly simple truncation scheme. Unlike ordinary moment equations, in which the inclusion of high order moments is prohibitively complicated, the binomial moment equations can be easily constructed up to any desired order. The result is a set of equations that enables the stochastic analysis of complex reaction networks under a broad range of conditions. The number of equations is dramatically reduced from the exponential proliferation of the master equation to a polynomial (and often quadratic) dependence on the number of reactive species in the binomial moment equations. The aim of this paper is twofold: to present a complete derivation of the binomial moment equations; to demonstrate the applicability of the moment equations for a representative set of example networks, in which stochastic effects play an important role. PMID:23030885

  18. Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry

    OpenAIRE

    Rappoport, Dmitrij; Galvin, Cooper J.; Zubarev, Dmitry; Aspuru-Guzik, Alan

    2014-01-01

    While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reacti...

  19. Graphical reduction of reaction networks by linear elimination of species

    OpenAIRE

    Sáez, Meritxell; Wiuf, Carsten; Feliu, Elisenda

    2015-01-01

    The quasi-steady state approximation and time-scale separation are commonly applied methods to simplify models of biochemical reaction networks based on ordinary differential equations (ODEs). The concentrations of the "fast" species are assumed effectively to be at steady state with respect to the "slow" species. Under this assumption the steady state equations can be used to eliminate the "fast" variables and a new ODE system with only the slow species can be obtained. We interpret a reduce...

  20. Variable elimination in chemical reaction networks with mass action kinetics

    OpenAIRE

    Feliu, Elisenda; Wiuf, Carsten

    2011-01-01

    We consider chemical reaction networks taken with mass action kinetics. The steady states of such a system are solutions to a system of polynomial equations. Even for small systems the task of finding the solutions is daunting. We develop an algebraic framework and procedure for linear elimination of variables. The procedure reduces the variables in the system to a set of "core" variables by eliminating variables corresponding to a set of non-interacting species. The steady states are paramet...

  1. A chemical reaction network solver for the astrophysics code NIRVANA

    Science.gov (United States)

    Ziegler, U.

    2016-02-01

    Context. Chemistry often plays an important role in astrophysical gases. It regulates thermal properties by changing species abundances and via ionization processes. This way, time-dependent cooling mechanisms and other chemistry-related energy sources can have a profound influence on the dynamical evolution of an astrophysical system. Modeling those effects with the underlying chemical kinetics in realistic magneto-gasdynamical simulations provide the basis for a better link to observations. Aims: The present work describes the implementation of a chemical reaction network solver into the magneto-gasdynamical code NIRVANA. For this purpose a multispecies structure is installed, and a new module for evolving the rate equations of chemical kinetics is developed and coupled to the dynamical part of the code. A small chemical network for a hydrogen-helium plasma was constructed including associated thermal processes which is used in test problems. Methods: Evolving a chemical network within time-dependent simulations requires the additional solution of a set of coupled advection-reaction equations for species and gas temperature. Second-order Strang-splitting is used to separate the advection part from the reaction part. The ordinary differential equation (ODE) system representing the reaction part is solved with a fourth-order generalized Runge-Kutta method applicable for stiff systems inherent to astrochemistry. Results: A series of tests was performed in order to check the correctness of numerical and technical implementation. Tests include well-known stiff ODE problems from the mathematical literature in order to confirm accuracy properties of the solver used as well as problems combining gasdynamics and chemistry. Overall, very satisfactory results are achieved. Conclusions: The NIRVANA code is now ready to handle astrochemical processes in time-dependent simulations. An easy-to-use interface allows implementation of complex networks including thermal processes

  2. Spreading out of perturbations in reversible reaction networks.

    Science.gov (United States)

    Maslov, Sergei; Sneppen, Kim; Ispolatov, I

    2007-08-17

    Using an example of physical interactions between proteins, we study how a perturbation propagates in the equilibrium of a network of reversible reactions governed by the law of mass action. We introduce a matrix formalism to describe the linear response of all equilibrium concentrations to shifts in total abundances of individual reactants, and reveal its heuristic analogy to the flow of electric current in a network of resistors. Our main conclusion is that, on average, the induced changes in equilibrium concentrations decay exponentially as a function of network distance from the source of perturbation. We analyze how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. We find that the minimal branching of the network, small values of dissociation constants, and low equilibrium free (unbound) concentrations of reacting substances all decrease the decay constant and thus increase the range of propagation. Exact analytic expressions for the decay constant are obtained for the case of equally strong interactions and uniform as well as oscillating concentrations on the Bethe lattice. Our general findings are illustrated using a real network of protein-protein interactions in baker's yeast with experimentally determined protein concentrations. PMID:18046464

  3. Spreading out of perturbations in reversible reaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Maslov, Sergei [Department of Condensed Matter Physics, Brookhaven National Laboratory, Upton, NY 11973 (United States); Sneppen, Kim [Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100 Copenhagen Oe (Denmark); Ispolatov, I [Ariadne Genomics Inc., 9430 Key West Ave. 113 Rockville, MD 20850 (United States)

    2007-08-15

    Using an example of physical interactions between proteins, we study how a perturbation propagates in the equilibrium of a network of reversible reactions governed by the law of mass action. We introduce a matrix formalism to describe the linear response of all equilibrium concentrations to shifts in total abundances of individual reactants, and reveal its heuristic analogy to the flow of electric current in a network of resistors. Our main conclusion is that, on average, the induced changes in equilibrium concentrations decay exponentially as a function of network distance from the source of perturbation. We analyze how this decay is influenced by such factors as the topology of a network, binding strength, and correlations between concentrations of neighboring nodes. We find that the minimal branching of the network, small values of dissociation constants, and low equilibrium free (unbound) concentrations of reacting substances all decrease the decay constant and thus increase the range of propagation. Exact analytic expressions for the decay constant are obtained for the case of equally strong interactions and uniform as well as oscillating concentrations on the Bethe lattice. Our general findings are illustrated using a real network of protein-protein interactions in baker's yeast with experimentally determined protein concentrations.

  4. Reduced models of networks of coupled enzymatic reactions

    CERN Document Server

    Kumar, Ajit

    2011-01-01

    The Michaelis-Menten equation has played a central role in our understanding of biochemical processes. It has long been understood how this equation approximates the dynamics of irreversible enzymatic reactions. However, a similar approximation in the case of networks, where the product of one reaction can act as an enzyme in another, has not been fully developed. Here we rigorously derive such an approximation in a class of coupled enzymatic networks where the individual interactions are of Michaelis-Menten type. We show that the sufficient conditions for the validity of the total quasi steady state assumption (tQSSA), obtained in a single protein case by Borghans, de Boer and Segel can be extended to sufficient conditions for the validity of the tQSSA in a large class of enzymatic networks. Secondly, we derive reduced equations that approximate the network's dynamics and involve only protein concentrations. This significantly reduces the number of equations necessary to model such systems. We prove the vali...

  5. Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

    Directory of Open Access Journals (Sweden)

    St Laurent Georges

    2010-03-01

    signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology, but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space.

  6. Storing and analysing biomolecular contacts

    OpenAIRE

    Walter, Peter

    2011-01-01

    Biomolecular contacts play a crucial role in all areas of life. In particular, protein-protein (PP) interactions are essential for most processes in biological cells. Antigen-antibody recognition, enzyme substrate binding, hormone receptor binding, RNA splicing, DNA replication and signal transduction are just some examples for the rich variety of PP interactions. In the last years modern proteomic methods have helped to get a better understanding of the complexity within living cell and orga...

  7. Models for solvated biomolecular structures

    OpenAIRE

    Cerutti, David

    2007-01-01

    Methods for estimating the structure and energetics of water around biomolecules are presented with the objective of improving the treatment of the biomolecular simulation environment as well as facilitating the use of complex, rigorous water models in the context of structure prediction problems that demand cheap solutions. Salt solutions around biomolecules are studied using an implicit solvent model with explicitly represented ions, revealing that the structure of the ion atmosphere is muc...

  8. Bosonic reaction-diffusion processes on scale-free networks

    Science.gov (United States)

    Baronchelli, Andrea; Catanzaro, Michele; Pastor-Satorras, Romualdo

    2008-07-01

    Reaction-diffusion processes can be adopted to model a large number of dynamics on complex networks, such as transport processes or epidemic outbreaks. In most cases, however, they have been studied from a fermionic perspective, in which each vertex can be occupied by at most one particle. While still useful, this approach suffers from some drawbacks, the most important probably being the difficulty to implement reactions involving more than two particles simultaneously. Here we develop a general framework for the study of bosonic reaction-diffusion processes on complex networks, in which there is no restriction on the number of interacting particles that a vertex can host. We describe these processes theoretically by means of continuous-time heterogeneous mean-field theory and divide them into two main classes: steady-state and monotonously decaying processes. We analyze specific examples of both behaviors within the class of one-species processes, comparing the results (whenever possible) with the corresponding fermionic counterparts. We find that the time evolution and critical properties of the particle density are independent of the fermionic or bosonic nature of the process, while differences exist in the functional form of the density of occupied vertices in a given degree class k . We implement a continuous-time Monte Carlo algorithm, well suited for general bosonic simulations, which allows us to confirm the analytical predictions formulated within mean-field theory. Our results, at both the theoretical and numerical levels, can be easily generalized to tackle more complex, multispecies, reaction-diffusion processes and open a promising path for a general study and classification of this kind of dynamical systems on complex networks.

  9. Recent developments in research on catalytic reaction networks

    Directory of Open Access Journals (Sweden)

    Roberto Serra

    2013-09-01

    Full Text Available Over the last years, analyses performed on a stochastic model of catalytic reaction networks have provided some indications about the reasons why wet-lab experiments hardly ever comply with the phase transition typically predicted by theoretical models with regard to the emergence of collectively self-replicating sets of molecule (also defined as autocatalytic sets, ACSs, a phenomenon that is often observed in nature and that is supposed to have played a major role in the emergence of the primitive forms of life. The model at issue has allowed to reveal that the emerging ACSs are characterized by a general dynamical fragility, which might explain the difficulty to observe them in lab experiments. In this work, the main results of the various analyses are reviewed, with particular regard to the factors able to affect the generic properties of catalytic reactions network, for what concerns, not only the probability of ACSs to be observed, but also the overall activity of the system, in terms of production of new species, reactions and matter.

  10. A self-regulating biomolecular comparator for processing oscillatory signals.

    Science.gov (United States)

    Agrawal, Deepak K; Franco, Elisa; Schulman, Rebecca

    2015-10-01

    While many cellular processes are driven by biomolecular oscillators, precise control of a downstream on/off process by a biochemical oscillator signal can be difficult: over an oscillator's period, its output signal varies continuously between its amplitude limits and spends a significant fraction of the time at intermediate values between these limits. Further, the oscillator's output is often noisy, with particularly large variations in the amplitude. In electronic systems, an oscillating signal is generally processed by a downstream device such as a comparator that converts a potentially noisy oscillatory input into a square wave output that is predominantly in one of two well-defined on and off states. The comparator's output then controls downstream processes. We describe a method for constructing a synthetic biochemical device that likewise produces a square-wave-type biomolecular output for a variety of oscillatory inputs. The method relies on a separation of time scales between the slow rate of production of an oscillatory signal molecule and the fast rates of intermolecular binding and conformational changes. We show how to control the characteristics of the output by varying the concentrations of the species and the reaction rates. We then use this control to show how our approach could be applied to process different in vitro and in vivo biomolecular oscillators, including the p53-Mdm2 transcriptional oscillator and two types of in vitro transcriptional oscillators. These results demonstrate how modular biomolecular circuits could, in principle, be combined to build complex dynamical systems. The simplicity of our approach also suggests that natural molecular circuits may process some biomolecular oscillator outputs before they are applied downstream. PMID:26378119

  11. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  12. Structural parameter identifiability analysis for dynamic reaction networks

    DEFF Research Database (Denmark)

    Davidescu, Florin Paul; Jørgensen, Sten Bay

    2008-01-01

    A fundamental problem in model identification is to investigate whether unknown parameters in a given model structure potentially can be uniquely recovered from experimental data. This issue of global or structural identifiability is essential during nonlinear first principles model development...... where for a given set of measured variables it is desirable to investigate which parameters may be estimated prior to spending computational effort on the actual estimation. This contribution addresses the structural parameter identifiability problem for the typical case of reaction network models. The...

  13. Switching dynamics in reaction networks induced by molecular discreteness

    International Nuclear Information System (INIS)

    To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentrations on the system size, which is caused by transitions to discreteness-induced novel states

  14. Adaptive hybrid simulations for multiscale stochastic reaction networks

    International Nuclear Information System (INIS)

    The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest

  15. COEL: A Cloud-based Reaction Network Simulator

    Directory of Open Access Journals (Sweden)

    Peter eBanda

    2016-04-01

    Full Text Available Chemical Reaction Networks (CRNs are a formalism to describe the macroscopic behavior of chemical systems. We introduce COEL, a web- and cloud-based CRN simulation framework that does not require a local installation, runs simulations on a large computational grid, provides reliable database storage, and offers a visually pleasing and intuitive user interface. We present an overview of the underlying software, the technologies, and the main architectural approaches employed. Some of COEL's key features include ODE-based simulations of CRNs and multicompartment reaction networks with rich interaction options, a built-in plotting engine, automatic DNA-strand displacement transformation and visualization, SBML/Octave/Matlab export, and a built-in genetic-algorithm-based optimization toolbox for rate constants.COEL is an open-source project hosted on GitHub (http://dx.doi.org/10.5281/zenodo.46544, which allows interested research groups to deploy it on their own sever. Regular users can simply use the web instance at no cost at http://coel-sim.org. The framework is ideally suited for a collaborative use in both research and education.

  16. Exact results for noise power spectra in linear biochemical reaction networks

    OpenAIRE

    Warren, Patrick B.; Tanase-Nicola, Sorin; Wolde, Pieter Rein ten

    2005-01-01

    We present a simple method for determining the exact noise power spectra in linear chemical reaction networks. We apply the method to networks which are representative of biochemical processes such as gene expression and signal detection. Our results clarify how noise is transmitted by signal detection motifs, and indicate how to coarse-grain networks by the elimination of fast reactions.

  17. Experimental (Network) and Evaluated Nuclear Reaction Data at NDS

    International Nuclear Information System (INIS)

    Dr Simakov of Nuclear Data Services Unit in the Nuclear Data Section (NDS) gave a brief overview of the data compilation and evaluation activities in the nuclear data community: experimental nuclear reaction data (EXFOR, http://www-nds.iaea.org/exfor/) and evaluated nuclear reaction data (ENDF, http://www-nds.iaea.org/endf). The International Network of Nuclear Reaction Data Centres (NRDC) coordinated by NDS includes 14 Centres in 8 Countries (China, Hungary, India, Japan, Korea, Russian, Ukraine, USA) and 2 International Organizations (NEA, IAEA). It had the first meeting of four core centres (Brookhaven, Saclay, Obninsk, Vienna) in 1966 and the EXFOR was adopted as an official data exchange format. In 2000, IAEA implemented the EXFOR database as a relational multiform database and the EXFOR is a trusted, increasing and living database with 19100 experimental works (as of September 2011) and 141600 data tables. The EXFOR provides a compilation control system for selection of articles and compilation of data and the NRDC home page provides manuals, documents and codes. The nuclear data can be retrieved by the web-retrieval system or distributed on a DVD on request. The EXFOR data play a critical role in the development of evaluated nuclear reaction data. There are several major general purpose libraries: ENDF (US), CENDL (China), JEFF (EU), JENDL (Japan) and RUSFOND (Russia). In addition, there are special libraries for particular applications: EAF (European Activation File), FENDL (Fusion Evaluated Nuclear Data Library for ITER neutronics), IBANDL (Ion Beam Analysis Nuclear Data Library for surface analysis of solids), IRDF, DXS (Dosimetry, radiation damage and gas production data) and Medical portal. Dr V. Zerkin of NDS demonstrated the data retrieval from the EXFOR database and the ENDF library.

  18. Variable elimination in chemical reaction networks with mass action kinetics

    CERN Document Server

    Feliu, Elisenda

    2011-01-01

    We consider chemical reaction networks taken with mass action kinetics. The steady states of such a system are solutions to a system of polynomial equations. Even for small systems the task of finding the solutions is daunting. We develop an algebraic framework and procedure for linear elimination of variables. The procedure reduces the variables in the system to a set of "core" variables by eliminating variables corresponding to a set of non-interacting species. The steady states are parameterized algebraically by the core variables, and a graphical condition is given for when a steady state with positive core variables necessarily have all variables positive. Further, we characterize graphically the sets of eliminated variables that are constrained by a conservation law and show that this conservation law takes a specific form.

  19. Integrative NMR for biomolecular research.

    Science.gov (United States)

    Lee, Woonghee; Cornilescu, Gabriel; Dashti, Hesam; Eghbalnia, Hamid R; Tonelli, Marco; Westler, William M; Butcher, Samuel E; Henzler-Wildman, Katherine A; Markley, John L

    2016-04-01

    NMR spectroscopy is a powerful technique for determining structural and functional features of biomolecules in physiological solution as well as for observing their intermolecular interactions in real-time. However, complex steps associated with its practice have made the approach daunting for non-specialists. We introduce an NMR platform that makes biomolecular NMR spectroscopy much more accessible by integrating tools, databases, web services, and video tutorials that can be launched by simple installation of NMRFAM software packages or using a cross-platform virtual machine that can be run on any standard laptop or desktop computer. The software package can be downloaded freely from the NMRFAM software download page ( http://pine.nmrfam.wisc.edu/download_packages.html ), and detailed instructions are available from the Integrative NMR Video Tutorial page ( http://pine.nmrfam.wisc.edu/integrative.html ). PMID:27023095

  20. Microwave spectroscopy of biomolecular building blocks.

    Science.gov (United States)

    Alonso, José L; López, Juan C

    2015-01-01

    Microwave spectroscopy, considered as the most definitive gas phase structural probe, is able to distinguish between different conformational structures of a molecule, because they have unique spectroscopic constants and give rise to distinct individual rotational spectra.Previously, application of this technique was limited to molecular specimens possessing appreciable vapor pressures, thus discarding the possibility of studying many other molecules of biological importance, in particular those with high melting points, which had a tendency to undergo thermal reactions, and ultimately degradation, upon heating.Nowadays, the combination of laser ablation with Fourier transform microwave spectroscopy techniques, in supersonic jets, has enabled the gas-phase study of such systems. In this chapter, these techniques, including broadband spectroscopy, as well as results of their application into the study of the conformational panorama and structure of biomolecular building blocks, such as amino acids, nucleic bases, and monosaccharides, are briefly discussed, and with them, the tools for conformational assignation - rotational constants, nuclear quadrupole coupling interaction, and dipole moment. PMID:25721775

  1. Biomolecular transport and separation in nanotubular networks.

    Energy Technology Data Exchange (ETDEWEB)

    Stachowiak, Jeanne C.; Stevens, Mark Jackson (Sandia National Laboratories, Albuquerque, NM); Robinson, David B.; Branda, Steven S.; Zendejas, Frank; Meagher, Robert J.; Sasaki, Darryl Yoshio; Bachand, George David (Sandia National Laboratories, Albuquerque, NM); Hayden, Carl C.; Sinha, Anupama; Abate, Elisa; Wang, Julia; Carroll-Portillo, Amanda (Sandia National Laboratories, Albuquerque, NM); Liu, Haiqing (Sandia National Laboratories, Albuquerque, NM)

    2010-09-01

    Cell membranes are dynamic substrates that achieve a diverse array of functions through multi-scale reconfigurations. We explore the morphological changes that occur upon protein interaction to model membrane systems that induce deformation of their planar structure to yield nanotube assemblies. In the two examples shown in this report we will describe the use of membrane adhesion and particle trajectory to form lipid nanotubes via mechanical stretching, and protein adsorption onto domains and the induction of membrane curvature through steric pressure. Through this work the relationship between membrane bending rigidity, protein affinity, and line tension of phase separated structures were examined and their relationship in biological membranes explored.

  2. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A.; Pantazis, Yannis

    2015-01-01

    Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in “sloppy” systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over

  3. [Advances in biomolecular machine: methane monooxygenases].

    Science.gov (United States)

    Lu, Jixue; Wang, Shizhen; Fang, Baishan

    2015-07-01

    Methane monooxygenases (MMO), regarded as "an amazing biomolecular machine", catalyze the oxidation of methane to methanol under aerobic conditions. MMO catalyze the oxidation of methane elaborately, which is a novel way to catalyze methane to methanol. Furthermore, MMO can inspire the biomolecular machine design. In this review, we introduced MMO including structure, gene and catalytic mechanism. The history and the taxonomy of MMO were also introduced. PMID:26647577

  4. Defect reaction network in Si-doped InAs. Numerical predictions.

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, Peter A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-05-01

    This Report characterizes the defects in the def ect reaction network in silicon - doped, n - type InAs predicted with first principles density functional theory. The reaction network is deduced by following exothermic defect reactions starting with the initially mobile interstitial defects reacting with common displacement damage defects in Si - doped InAs , until culminating in immobile reaction p roducts. The defect reactions and reaction energies are tabulated, along with the properties of all the silicon - related defects in the reaction network. This Report serves to extend the results for the properties of intrinsic defects in bulk InAs as colla ted in SAND 2013 - 2477 : Simple intrinsic defects in InAs : Numerical predictions to include Si - containing simple defects likely to be present in a radiation - induced defect reaction sequence . This page intentionally left blank

  5. On the Mathematical Structure of Balanced Chemical Reaction Networks Governed by Mass Action Kinetics

    OpenAIRE

    der Schaft, Arjan van; Rao, Shodhan; Jayawardhana, Bayu

    2011-01-01

    Motivated by recent progress on the interplay between graph theory, dynamics, and systems theory, we revisit the analysis of chemical reaction networks described by mass action kinetics. For reaction networks possessing a thermodynamic equilibrium we derive a compact formulation exhibiting at the same time the structure of the complex graph and the stoichiometry of the network, and which admits a direct thermodynamical interpretation. This formulation allows us to easily characterize the set ...

  6. Properties of Random Complex Chemical Reaction Networks and Their Relevance to Biological Toy Models

    OpenAIRE

    Bigan, Erwan; Steyaert, Jean-Marc; Douady, Stéphane

    2013-01-01

    We investigate the properties of large random conservative chemical reaction networks composed of elementary reactions endowed with either mass-action or saturating kinetics, assigning kinetic parameters in a thermodynamically-consistent manner. We find that such complex networks exhibit qualitatively similar behavior when fed with external nutrient flux. The nutrient is preferentially transformed into one specific chemical that is an intrinsic property of the network. We propose a self-consi...

  7. Evolutionary origin of power-laws in Biochemical Reaction Network; embedding abundance distribution into topology

    OpenAIRE

    Furusawa, Chikara; Kaneko, Kunihiko

    2005-01-01

    The evolutionary origin of universal statistics in biochemical reaction network is studied, to explain the power-law distribution of reaction links and the power-law distributions of chemical abundances. Using cell models with catalytic reaction network, we find evidence that the power-law distribution in abundances of chemicals emerges by the selection of cells with higher growth speeds. Through the further evolution, this inhomogeneity in chemical abundances is shown to be embedded in the d...

  8. From Correlation to Causality: Statistical Approaches to Learning Regulatory Relationships in Large-Scale Biomolecular Investigations.

    Science.gov (United States)

    Ness, Robert O; Sachs, Karen; Vitek, Olga

    2016-03-01

    Causal inference, the task of uncovering regulatory relationships between components of biomolecular pathways and networks, is a primary goal of many high-throughput investigations. Statistical associations between observed protein concentrations can suggest an enticing number of hypotheses regarding the underlying causal interactions, but when do such associations reflect the underlying causal biomolecular mechanisms? The goal of this perspective is to provide suggestions for causal inference in large-scale experiments, which utilize high-throughput technologies such as mass-spectrometry-based proteomics. We describe in nontechnical terms the pitfalls of inference in large data sets and suggest methods to overcome these pitfalls and reliably find regulatory associations. PMID:26731284

  9. Sensitivity of chemical reaction networks: a structural approach 3. Regular multimolecular systems

    CERN Document Server

    Brehm, Bernhard

    2016-01-01

    We present a systematic mathematical analysis of the qualitative steady-state response to rate perturbations in large classes of reaction networks. This includes multimolecular reactions and allows for catalysis, enzymatic reactions, multiple reaction products, nonmonotone rate functions, and non-closed autonomous systems. Our structural sensitivity analysis is based on the stoichiometry of the reaction network, only. It does not require numerical data on reaction rates. Instead, we impose mild and generic nondegeneracy conditions of algebraic type. From the structural data, only, we derive which steady-state concentrations are sensitive to, and hence influenced by, changes of any particular reaction rate - and which are not. We also establish transitivity properties for influences involving rate perturbations. This allows us to derive an influence graph which globally summarizes the influence pattern of the given network. The influence graph allows the computational, but meaningful, automatic identification ...

  10. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis.

    Directory of Open Access Journals (Sweden)

    Ketki D Verkhedkar

    Full Text Available BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a

  11. Analysis of weblike network structures of directed graphs for chemical reactions in methane plasmas

    International Nuclear Information System (INIS)

    Chemical reactions of molecular gases like methane are so complicated that a chart of decomposed and/or synthesized species originating from molecules in plasma resembles a weblike network in which we write down species and reactions among them. Here we consider properties of the network structures of chemical reactions in methane plasmas. In the network, atoms/molecules/radical species are assumed to form nodes and chemical reactions correspond to directed edges in the terminology of graph theory. Investigation of the centrality index reveals importance of CH3 in the global chemical reaction, and difference of an index for each radical species between cases with and without electrons clarifies that the electrons are at an influential position to tighten the network structure

  12. Reduction of dynamical biochemical reactions networks in computational biology

    OpenAIRE

    Radulescu, O.; Gorban, A.N.; Zinovyev, A.; Noel, V.

    2012-01-01

    Biochemical networks are used in computational biology, to model mechanistic details of systems involved in cell signaling, metabolism, and regulation of gene expression. Parametric and structural uncertainty, as well as combinatorial explosion are strong obstacles against analyzing the dynamics of large models of this type. Multiscaleness, an important property of these networks, can be used to get past some of these obstacles. Networks with many well separated time scales, can be reduced to...

  13. Conducting polymer based biomolecular electronic devices

    Indian Academy of Sciences (India)

    B D Malhotra; Rahul Singhal

    2003-08-01

    Biomolecular electronics is rapidly evolving from physics, chemistry, biology, electronics and information technology. Organic materials such as proteins, pigments and conducting polymers have been considered as alternatives for carrying out the functions that are presently being performed by semiconductor silicon. Conducting polymers such as polypyrroles, polythiophenes and polyanilines have been projected for applications for a wide range of biomolecular electronic devices such as optical, electronic, drug-delivery, memory and biosensing devices. Our group has been actively working towards the application of conducting polymers to Schottky diodes, metal–insulator–semiconductor (MIS) devices and biosensors for the past 10 years. This paper is a review of some of the results obtained at our laboratory in the area of conducting polymer biomolecular electronics.

  14. Unravelling the Maillard reaction network by multiresponse kinetic modelling

    OpenAIRE

    Martins, S.I.F.S.

    2003-01-01

    The Maillard reaction is an important reaction in food industry. It is responsible for the formation of colour and aroma, as well as toxic compounds as the recent discovered acrylamide. The knowledge of kinetic parameters, such as rate constants and activation energy, is necessary to predict its extent and, consequently, to optimise it. Each of the chapters presented in this thesis can be seen as a necessary step to succeed in applying multiresponse kinetic modelling in a complex reaction, su...

  15. Markov propagation of allosteric effects in biomolecular systems: application to GroEL–GroES

    OpenAIRE

    Chennubhotla, Chakra; Bahar, Ivet

    2006-01-01

    We introduce a novel approach for elucidating the potential pathways of allosteric communication in biomolecular systems. The methodology, based on Markov propagation of ‘information' across the structure, permits us to partition the network of interactions into soft clusters distinguished by their coherent stochastics. Probabilistic participation of residues in these clusters defines the communication patterns inherent to the network architecture. Application to bacterial chaperonin complex ...

  16. Boundedness and exponential stability for nonautonomous cellular neural networks with reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China); Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)]. E-mail: btcui@sohu.com

    2007-07-15

    Employing Lyapunov functional method, we analyze the ultimate boundedness and global exponential stability of a class of reaction-diffusion cellular neural networks with time-varying delays. Some new criteria are obtained to ensure ultimate boundedness and global exponential stability of delayed reaction-diffusion cellular neural networks (DRCNNs). Without assuming that the activation functions f {sub ijl}(.) are bounded, the results extend and improve the earlier publications.

  17. Ion irradiation and biomolecular radiation damage II. Indirect effect

    CERN Document Server

    Wang, Wei; Su, Wenhui

    2010-01-01

    It has been reported that damage of genome in a living cell by ionizing radiation is about one-third direct and two-thirds indirect. The former which has been introduced in our last paper, concerns direct energy deposition and ionizing reactions in the biomolecules; the latter results from radiation induced reactive species (mainly radicals) in the medium (mainly water) surrounding the biomolecules. In this review, a short description of ion implantation induced radical formation in water is presented. Then we summarize the aqueous radical reaction chemistry of DNA, protein and their components, followed by a brief introduction of biomolecular damage induced by secondary particles (ions and electron). Some downstream biological effects are also discussed.

  18. On the graph and systems analysis of reversible chemical reaction networks with mass action kinetics

    NARCIS (Netherlands)

    Rao, Shodhan; Jayawardhana, Bayu; Schaft, Arjan van der

    2012-01-01

    Motivated by the recent progresses on the interplay between the graph theory and systems theory, we revisit the analysis of reversible chemical reaction networks described by mass action kinetics by reformulating it using the graph knowledge of the underlying networks. Based on this formulation, we

  19. Perspective: Coarse-grained models for biomolecular systems

    Science.gov (United States)

    Noid, W. G.

    2013-09-01

    By focusing on essential features, while averaging over less important details, coarse-grained (CG) models provide significant computational and conceptual advantages with respect to more detailed models. Consequently, despite dramatic advances in computational methodologies and resources, CG models enjoy surging popularity and are becoming increasingly equal partners to atomically detailed models. This perspective surveys the rapidly developing landscape of CG models for biomolecular systems. In particular, this review seeks to provide a balanced, coherent, and unified presentation of several distinct approaches for developing CG models, including top-down, network-based, native-centric, knowledge-based, and bottom-up modeling strategies. The review summarizes their basic philosophies, theoretical foundations, typical applications, and recent developments. Additionally, the review identifies fundamental inter-relationships among the diverse approaches and discusses outstanding challenges in the field. When carefully applied and assessed, current CG models provide highly efficient means for investigating the biological consequences of basic physicochemical principles. Moreover, rigorous bottom-up approaches hold great promise for further improving the accuracy and scope of CG models for biomolecular systems.

  20. Advances in integrative modeling of biomolecular complexes

    NARCIS (Netherlands)

    Karaca, E.; Bonvin, A.M.J.J.

    2013-01-01

    High-resolution structural information is needed in order to unveil the underlying mechanistic of biomolecular function. Due to the technical limitations or the nature of the underlying complexes, acquiring atomic resolution information is difficult for many challenging systems, while, often, low-re

  1. Flourescence from Gas-Phase Biomolecular Ions

    DEFF Research Database (Denmark)

    Nielsen, Steen Brøndsted

    2013-01-01

    This chapter deals with measurements of fluorescence from electronically excited biomolecular ions where there are no interactions with an external environment. Biomolecules with no natural fluorophores are labelled with a dye for such experiments. First, some of the advantages, but also difficul...

  2. Programming in Biomolecular Computation: Programs, Self-Interpretation and Visualisation

    Directory of Open Access Journals (Sweden)

    J.G. Simonsen

    2011-01-01

    Full Text Available Our goal is to provide a top-down approach to biomolecular computation. In spite of widespread discussion about connections between biology and computation, one question seems notable by its absence: Where are the programs? We identify a number of common features in programming that seem conspicuously absent from the literature on biomolecular computing; to partially redress this absence, we introduce a model of computation that is evidently programmable, by programs reminiscent of low-level computer machine code; and at the same time biologically plausible: its functioning is defined by a single and relatively small set of chemical-like reaction rules. Further properties: the model is stored-program: programs are the same as data, so programs are not only executable, but are also compilable and interpretable. It is universal: all computable functions can be computed (in natural ways and without arcane encodings of data and algorithm; it is also uniform: new ``hardware'' is not needed to solve new problems; and (last but not least it is Turing complete in a strong sense: a universal algorithm exists, that is able to execute any program, and is not asymptotically inefficient.

  3. Turing-Hopf instability in biochemical reaction networks arising from pairs of subnetworks.

    Science.gov (United States)

    Mincheva, Maya; Roussel, Marc R

    2012-11-01

    Network conditions for Turing instability in biochemical systems with two biochemical species are well known and involve autocatalysis or self-activation. On the other hand general network conditions for potential Turing instabilities in large biochemical reaction networks are not well developed. A biochemical reaction network with any number of species where only one species moves is represented by a simple digraph and is modeled by a reaction-diffusion system with non-mass action kinetics. A graph-theoretic condition for potential Turing-Hopf instability that arises when a spatially homogeneous equilibrium loses its stability via a single pair of complex eigenvalues is obtained. This novel graph-theoretic condition is closely related to the negative cycle condition for oscillations in ordinary differential equation models and its generalizations, and requires the existence of a pair of subnetworks, each containing an even number of positive cycles. The technique is illustrated with a double-cycle Goodwin type model. PMID:22698892

  4. Preclusion of switch behavior in reaction networks with mass-action kinetics

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, C.

    2012-01-01

    We study networks taken with mass-action kinetics and provide a Jacobian criterion that applies to an arbitrary network to preclude the existence of multiple positive steady states within any stoichiometric class for any choice of rate constants. We are concerned with the characterization of...... injective networks, that is, networks for which the species formation rate function is injective in the interior of the positive orthant within each stoichiometric class. We show that a network is injective if and only if the determinant of the Jacobian of a certain function does not vanish. The function...... precludes the existence of degenerate steady states. Further, we relate injectivity of a network to that of the network obtained by adding outflow, or degradation, reactions for all species....

  5. Reaction-Diffusion Processes on Random and Scale-Free Networks

    Science.gov (United States)

    Banerjee, Subhasis; Mallick, Shrestha Basu; Bose, Indrani

    We study the discrete Gierer-Meinhardt model of reaction-diffusion on three different types of networks: regular, random and scale-free. The model dynamics lead to the formation of stationary Turing patterns in the steady state in certain parameter regions. Some general features of the patterns are studied through numerical simulation. The results for the random and scale-free networks show a marked difference from those in the case of the regular network. The difference may be ascribed to the small world character of the first two types of networks.

  6. Open chemical reaction networks, steady-state loads and Braess-like paradox

    CERN Document Server

    Banerjee, Kinshuk

    2014-01-01

    Open chemical reaction systems involve matter-exchange with the surroundings. As a result, species can accumulate inside a system during the course of the reaction. We study the role of network topology in governing the concentration build-up inside a fixed reaction volume at steady state, particularly focusing on the effect of additional paths. The problem is akin to that in traffic networks where an extra route, surprisingly, can increase the overall travel time. This is known as the Braess' paradox. Here, we report chemical analogues of such a paradox in suitably chosen reaction networks, where extra reaction step(s) can inflate the total concentration, denoted as `load', at steady state. It is shown that, such counter-intuitive behavior emerges in a qualitatively similar pattern in networks of varying complexities. We then explore how such extra routes affect the load in a biochemical scheme of uric acid degradation. From a thorough analysis of this network, we propose a functional role of some decomposit...

  7. Minimal metabolic pathway structure is consistent with associated biomolecular interactions.

    Science.gov (United States)

    Bordbar, Aarash; Nagarajan, Harish; Lewis, Nathan E; Latif, Haythem; Ebrahim, Ali; Federowicz, Stephen; Schellenberger, Jan; Palsson, Bernhard O

    2014-01-01

    Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pathways better describe multiple independent pathway-associated biomolecular interaction datasets suggesting a functional organization for metabolism based on parsimonious use of cellular components. We use the inherent predictive capability of these pathways to experimentally discover novel transcriptional regulatory interactions in Escherichia coli metabolism for three transcription factors, effectively doubling the known regulatory roles for Nac and MntR. This study suggests an underlying and fundamental principle in the evolutionary selection of pathway structures; namely, that pathways may be minimal, independent, and segregated. PMID:24987116

  8. The US nuclear reaction data network. Summary of the first meeting, March 13 & 14 1996

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    The first meeting of the US Nuclear Reaction Data Network (USNRDN) was held at the Colorado School of Mines, March 13-14, 1996 chaired by F. Edward Cecil. The Agenda of the meeting is attached. The Network, its mission, products and services; related nuclear data and data networks, members, and organization are described in Attachment 1. The following progress reports from the members of the USNRDN were distributed prior to the meeting and are given as Attachment 2. (1) Measurements and Development of Analytic Techniques for Basic Nuclear Physics and Nuclear Applications; (2) Nuclear Reaction Data Activities at the National Nuclear Data Center; (3) Studies of nuclear reactions at very low energies; (4) Nuclear Reaction Data Activities, Nuclear Data Group; (5) Progress in Neutron Physics at Los Alamos - Experiments; (6) Nuclear Reaction Data Activities in Group T2; (7) Progress Report for the US Nuclear Reaction Data Network Meeting; (8) Nuclear Astrophysics Research Group (ORNL); (9) Progress Report from Ohio University; (10) Exciton Model Phenomenology; and (11) Progress Report for Coordination Meeting USNRDN.

  9. The US nuclear reaction data network. Summary of the first meeting, March 13 ampersand 14 1996

    International Nuclear Information System (INIS)

    The first meeting of the US Nuclear Reaction Data Network (USNRDN) was held at the Colorado School of Mines, March 13-14, 1996 chaired by F. Edward Cecil. The Agenda of the meeting is attached. The Network, its mission, products and services; related nuclear data and data networks, members, and organization are described in Attachment 1. The following progress reports from the members of the USNRDN were distributed prior to the meeting and are given as Attachment 2. (1) Measurements and Development of Analytic Techniques for Basic Nuclear Physics and Nuclear Applications; (2) Nuclear Reaction Data Activities at the National Nuclear Data Center; (3) Studies of nuclear reactions at very low energies; (4) Nuclear Reaction Data Activities, Nuclear Data Group; (5) Progress in Neutron Physics at Los Alamos - Experiments; (6) Nuclear Reaction Data Activities in Group T2; (7) Progress Report for the US Nuclear Reaction Data Network Meeting; (8) Nuclear Astrophysics Research Group (ORNL); (9) Progress Report from Ohio University; (10) Exciton Model Phenomenology; and (11) Progress Report for Coordination Meeting USNRDN

  10. PREFACE: Radiation Damage in Biomolecular Systems (RADAM07)

    Science.gov (United States)

    McGuigan, Kevin G.

    2008-03-01

    , which include: theoretical, experimental, medical and computational physicists, radiation chemists, radiation biologists and microbiologists, among others. An important aspect of the previous 3 conferences in this series was to remove barriers between the different working groups and to encourage a more interdisciplinary approach to research collaborations. During RADAM_07 we could observe the success of these efforts. A large number of presentations were based on new collaborations, many funded under the COST STSM programme, and all presentations led to lively discussions. It is clear from the discussions following many of the presentations and at the poster sessions that Radiation Damage in Biomolecular Systems remains a topic of increasing interest, relevance and importance. The success of this conference as well as of the whole RADAM conference series reflects the growing international interest in the area of interactions of ionizing radiation with biomolecules. Despite the scheduled conclusion in September 2007 of COST Action P9 which has part-funded this, and previous RADAM meetings, the nature of the cross-disciplinary interactions and opportunities for collaborative research was deemed so successful and valuable by the assembled delegates that it was agreed that another such meeting should be held in Debrecen in Hungary from 13-15 June 2008 http://www.isa.au.dk/meetings/radam2008/programme.html. Additional information about RADAM07 programme is available on the conference web-page http://www.isa.au.dk/networks/cost/radam07/index.html. The Organizing Committee would like to thank all speakers, contributors, session chairs, referees and meeting staff for their efforts in making the RADAM07 successful. The local Organization Committee would like to thank Lorraine Monard and Margaret Nolan for their invaluable expertise in conference management. We also gratefully acknowledge the financial support of our sponsors - The Royal, College of Surgeons in Ireland (RCSI

  11. Improvements in continuum modeling for biomolecular systems

    CERN Document Server

    Qiao, Yu

    2015-01-01

    Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson-Boltzmann (PB)/Poisson-Nernst-Planck (PNP) equations has made great contributions towards simulation of these processes. However, the model has shortcomings in its commonly used form and cannot capture (or cannot accurately capture) some important physical properties of biological systems. Considerable efforts have been made to improve the continuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulation. This review will summarize recent main improvements in continuum modeling for biomolecular systems, with focus on the size-modified models, the coupling of the classical density functional theory and PNP equations, the coupling of polar and nonpolar interactions, and numerical progress.

  12. A cascade reaction network mimicking the basic functional steps of adaptive immune response

    Science.gov (United States)

    Han, Da; Wu, Cuichen; You, Mingxu; Zhang, Tao; Wan, Shuo; Chen, Tao; Qiu, Liping; Zheng, Zheng; Liang, Hao; Tan, Weihong

    2015-10-01

    Biological systems use complex ‘information-processing cores’ composed of molecular networks to coordinate their external environment and internal states. An example of this is the acquired, or adaptive, immune system (AIS), which is composed of both humoral and cell-mediated components. Here we report the step-by-step construction of a prototype mimic of the AIS that we call an adaptive immune response simulator (AIRS). DNA and enzymes are used as simple artificial analogues of the components of the AIS to create a system that responds to specific molecular stimuli in vitro. We show that this network of reactions can function in a manner that is superficially similar to the most basic responses of the vertebrate AIS, including reaction sequences that mimic both humoral and cellular responses. As such, AIRS provides guidelines for the design and engineering of artificial reaction networks and molecular devices.

  13. Lyapunov Functions, Stationary Distributions, and Non-equilibrium Potential for Reaction Networks

    DEFF Research Database (Denmark)

    Anderson, David F.; Craciun, Gheorghe; Gopalkrishnan, Manoj; Wiuf, Carsten Henrik

    2015-01-01

    We consider the relationship between stationary distributions for stochastic models of reaction systems and Lyapunov functions for their deterministic counterparts. Specifically, we derive the well-known Lyapunov function of reaction network theory as a scaling limit of the non-equilibrium potent......We consider the relationship between stationary distributions for stochastic models of reaction systems and Lyapunov functions for their deterministic counterparts. Specifically, we derive the well-known Lyapunov function of reaction network theory as a scaling limit of the non......-equilibrium potential of the stationary distribution of stochastically modeled complex balanced systems. We extend this result to general birth–death models and demonstrate via example that similar scaling limits can yield Lyapunov functions even for models that are not complex or detailed balanced, and may even have...

  14. Report on the IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting), held at the Japan Nuclear Reaction Data Centre, Hokkaido University, Sapporo, Japan, from 20 - 23 April 2010. The meeting was attended by 27 participants from 12 cooperating data centres of seven Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, the lists of working papers and presentations presented at the meeting. This report summarizes the IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting), held at the Japan Nuclear Reaction Data Centre, Hokkaido University, Sapporo, Japan, from 20 - 23 April 2010. The meeting was attended by 27 participants from 12 cooperating data centres of seven Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, the lists of working papers and presentations presented at the meeting. (author)

  15. The origin of large molecules in primordial autocatalytic reaction networks

    CERN Document Server

    Giri, Varun

    2011-01-01

    Large molecules such as proteins and nucleic acids are crucial for life, yet their primordial origin remains a major puzzle. The production of large molecules, as we know it today, requires good catalysts, and the only good catalysts we know that can accomplish this task consist of large molecules. Thus the origin of large molecules is a chicken and egg problem in chemistry. Here we present a mechanism, based on autocatalytic sets (ACSs), that is a possible solution to this problem. We discuss a mathematical model describing the population dynamics of molecules in a stylized but prebiotically plausible chemistry. Large molecules can be produced in this chemistry by the coalescing of smaller ones, with the smallest molecules, the `food set', being buffered. Some of the reactions can be catalyzed by molecules within the chemistry with varying catalytic strengths. Normally the concentrations of large molecules in such a scenario are very small, diminishing exponentially with their size. ACSs, if present in the c...

  16. Optimization Models for Reaction Networks: Information Divergence, Quadratic Programming and Kirchhoff’s Laws

    OpenAIRE

    Julio Michael Stern; Fabio Nakano

    2014-01-01

    This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of...

  17. On the graph and systems analysis of reversible chemical reaction networks with mass action kinetics

    OpenAIRE

    Rao, Shodhan; Jayawardhana, Bayu; der Schaft, Arjan van

    2012-01-01

    Motivated by the recent progresses on the interplay between the graph theory and systems theory, we revisit the analysis of reversible chemical reaction networks described by mass action kinetics by reformulating it using the graph knowledge of the underlying networks. Based on this formulation, we can characterize the space of equilibrium points and provide simple dynamical analysis on the state space modulo the space of equilibrium points.

  18. The cost and capacity of signaling in the Escherichia coli protein reaction network

    International Nuclear Information System (INIS)

    In systems biology new ways are required to analyze the large amount of existing data on regulation of cellular processes. Recent work can be roughly classified into either dynamical models of well-described subsystems, or coarse-grained descriptions of the topology of the molecular networks at the scale of the whole organism. In order to bridge these two disparate approaches one needs to develop simplified descriptions of dynamics and topological measures which address the propagation of signals in molecular networks. Transmission of a signal across a reaction node depends on the presence of other reactants. It will typically be more demanding to transmit a signal across a reaction node with more input links. Sending signals along a path with several subsequent reaction nodes also increases the constraints on the presence of other proteins in the overall network. Therefore counting in and out links along reactions of a potential pathway can give insight into the signaling properties of a particular molecular network. Here, we consider the directed network of protein regulation in E. coli, characterizing its modularity in terms of its potential to transmit signals. We demonstrate that the simplest measure based on identifying subnetworks of strong components, within which each node could send a signal to every other node, does indeed partition the network into functional modules. We suggest that the total number of reactants needed to send a signal between two nodes in the network can be considered as the cost associated with transmitting this signal. Similarly we define spread as the number of reaction products that could be influenced by transmission of a successful signal. Our considerations open for a new class of network measures that implicitly utilize the constrained repertoire of chemical modifications of any biological molecule. The counting of cost and spread connects the topology of networks to the specificity of signaling across the network. Thereby, we

  19. New Approach to the Stability of Chemical Reaction Networks: Piecewise Linear in Rates Lyapunov Functions

    OpenAIRE

    Al-Radhawi, M. Ali; Angeli, David

    2014-01-01

    Piecewise-Linear in Rates (PWLR) Lyapunov functions are introduced for a class of Chemical Reaction Networks (CRNs). In addition to their simple structure, these functions are robust with respect to arbitrary monotone reaction rates, of which mass-action is a special case. The existence of such functions ensures the convergence of trajectories towards equilibria, and guarantee their asymptotic stability with respect to the corresponding stoichiometric compatibility class. We give the definiti...

  20. BRUSLIB and NETGEN: the Brussels nuclear reaction rate library and nuclear network generator for astrophysics

    OpenAIRE

    Aikawa, M.; Arnould, M.; Goriely, S.; Jorissen, A.; Takahashi, K.

    2005-01-01

    Nuclear reaction rates are quantities of fundamental importance in astrophysics. Substantial efforts have been devoted in the last decades to measure or calculate them. The present paper presents for the first time a detailed description of the Brussels nuclear reaction rate library BRUSLIB and of the nuclear network generator NETGEN so as to make these nuclear data packages easily accessible to astrophysicists for a large variety of applications. BRUSLIB is made of two parts. The first one c...

  1. Growth states of catalytic reaction networks exhibiting energy metabolism

    Science.gov (United States)

    Kondo, Yohei; Kaneko, Kunihiko

    2011-07-01

    All cells derive nutrition by absorbing some chemical and energy resources from the environment; these resources are used by the cells to reproduce the chemicals within them, which in turn leads to an increase in their volume. In this study we introduce a protocell model exhibiting catalytic reaction dynamics, energy metabolism, and cell growth. Results of extensive simulations of this model show the existence of four phases with regard to the rates of both the influx of resources and cell growth. These phases include an active phase with high influx and high growth rates, an inefficient phase with high influx but low growth rates, a quasistatic phase with low influx and low growth rates, and a death phase with negative growth rate. A mean field model well explains the transition among these phases as bifurcations. The statistical distribution of the active phase is characterized by a power law, and that of the inefficient phase is characterized by a nearly equilibrium distribution. We also discuss the relevance of the results of this study to distinct states in the existing cells.

  2. Toward a self-consistent and unitary reaction network for big bang nucleosynthesis

    International Nuclear Information System (INIS)

    Unitarity, the mathematical expression of the conservation of probability in multichannel reactions, is an essential ingredient in the development of accurate nuclear reaction networks appropriate for nucleosynthesis in a variety of environments. We describe our ongoing program to develop a 'unitary reaction network' for the big-bang nucleosynthesis environment and look at an example of the need and power of unitary parametrizations of nuclear scattering and reaction data. Recent attention has been focused on the possible role of the 9B compound nuclear system in the resonant destruction of 7Li during primordial nucleosynthesis. We have studied reactions in the 9B compound system with a multichannel, two-body unitary R-matrix code (EDA) using the known elastic and reaction data, in a four-channel treatment. The data include elastic 6Li(3He,3He)6Li differential cross sections from 0.7 to 2.0 MeV, integrated reaction cross sections for energies from 0.7 to 5.0 MeV for 6Li(3He,p)8Be* and from 0.4 to 5.0 MeV for the 6Li(3He,γ)7Be reaction. Capture data have been added to the previous analysis with integrated cross section measurements from 0.7 to 0.825 MeV for 6Li(3He,γ)9B. The resulting resonance parameters are compared with tabulated values from TUNL Nuclear Data Group analyses. Previously unidentified resonances are noted and the relevance of this analysis and a unitary reaction network for big-bang nucleosynthesis are emphasized. (author)

  3. Adaptive exponential synchronization of delayed neural networks with reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Sheng Li [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China); Yang Huizhong [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: victory8209@yahoo.com.cn; Lou Xuyang [School of Communication and Control Engineering, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)

    2009-04-30

    This paper presents an exponential synchronization scheme for a class of neural networks with time-varying and distributed delays and reaction-diffusion terms. An adaptive synchronization controller is derived to achieve the exponential synchronization of the drive-response structure of neural networks by using the Lyapunov stability theory. At the same time, the update laws of parameters are proposed to guarantee the synchronization of delayed neural networks with all parameters unknown. It is shown that the approaches developed here extend and improve the ideas presented in recent literatures.

  4. Coupling switches and oscillators as a means to shape cellular signals in biomolecular systems

    International Nuclear Information System (INIS)

    To understand how a complex biomolecular network functions, a decomposition or a reconstruction process of the network is often needed so as to provide new insights into the regulatory mechanisms underlying various dynamical behaviors and also to gain qualitative knowledge of the network. Unfortunately, it seems that there are still no general rules on how to decompose a complex network into simple modules. An alternative resolution is to decompose a complex network into small modules or subsystems with specified functions such as switches and oscillators and then integrate them by analyzing the interactions between them. The main idea of this approach can be illustrated by considering a bidirectionally coupled network in this paper, i.e., coupled Toggle switch and Repressilator, and analyzing the occurrence of various dynamics, although the theoretical principle may hold for a general class of networks. We show that various biomolecular signals can be shaped by regulating the coupling between the subsystems. The approach presented here can be expected to simplify and analyze even more complex biological networks

  5. A computational framework for the automated construction of glycosylation reaction networks.

    Directory of Open Access Journals (Sweden)

    Gang Liu

    Full Text Available Glycosylation is among the most common and complex post-translational modifications identified to date. It proceeds through the catalytic action of multiple enzyme families that include the glycosyltransferases that add monosaccharides to growing glycans, and glycosidases which remove sugar residues to trim glycans. The expression level and specificity of these enzymes, in part, regulate the glycan distribution or glycome of specific cell/tissue systems. Currently, there is no systematic method to describe the enzymes and cellular reaction networks that catalyze glycosylation. To address this limitation, we present a streamlined machine-readable definition for the glycosylating enzymes and additional methodologies to construct and analyze glycosylation reaction networks. In this computational framework, the enzyme class is systematically designed to store detailed specificity data such as enzymatic functional group, linkage and substrate specificity. The new classes and their associated functions enable both single-reaction inference and automated full network reconstruction, when given a list of reactants and/or products along with the enzymes present in the system. In addition, graph theory is used to support functions that map the connectivity between two or more species in a network, and that generate subset models to identify rate-limiting steps regulating glycan biosynthesis. Finally, this framework allows the synthesis of biochemical reaction networks using mass spectrometry (MS data. The features described above are illustrated using three case studies that examine: i O-linked glycan biosynthesis during the construction of functional selectin-ligands; ii automated N-linked glycosylation pathway construction; and iii the handling and analysis of glycomics based MS data. Overall, the new computational framework enables automated glycosylation network model construction and analysis by integrating knowledge of glycan structure and enzyme

  6. BRUSLIB and NETGEN: the Brussels nuclear reaction rate library and nuclear network generator for astrophysics

    CERN Document Server

    Aikawa, M; Goriely, S; Jorissen, A; Takahashi, K

    2005-01-01

    Nuclear reaction rates are quantities of fundamental importance in astrophysics. Substantial efforts have been devoted in the last decades to measure or calculate them. The present paper presents for the first time a detailed description of the Brussels nuclear reaction rate library BRUSLIB and of the nuclear network generator NETGEN so as to make these nuclear data packages easily accessible to astrophysicists for a large variety of applications. BRUSLIB is made of two parts. The first one contains the 1999 NACRE compilation based on experimental data for 86 reactions with (mainly) stable targets up to Si. The second part of BRUSLIB concerns nuclear reaction rate predictions calculated within a statistical Hauser-Feshbach approximation, which limits the reliability of the rates to reactions producing compound nuclei with a high enough level density. These calculations make use of global and coherent microscopic nuclear models for the quantities entering the rate calculations. The use of such models is utterl...

  7. Integration of biomolecular logic gates with field-effect transducers

    International Nuclear Information System (INIS)

    Highlights: → Enzyme-based AND/OR logic gates are integrated with a capacitive field-effect sensor. → The AND/OR logic gates compose of multi-enzyme system immobilised on sensor surface. → Logic gates were activated by different combinations of chemical inputs (analytes). → The logic output (pH change) produced by the enzymes was read out by the sensor. - Abstract: The integration of biomolecular logic gates with field-effect devices - the basic element of conventional electronic logic gates and computing - is one of the most attractive and promising approaches for the transformation of biomolecular logic principles into macroscopically useable electrical output signals. In this work, capacitive field-effect EIS (electrolyte-insulator-semiconductor) sensors based on a p-Si-SiO2-Ta2O5 structure modified with a multi-enzyme membrane have been used for electronic transduction of biochemical signals processed by enzyme-based OR and AND logic gates. The realised OR logic gate composes of two enzymes (glucose oxidase and esterase) and was activated by ethyl butyrate or/and glucose. The AND logic gate composes of three enzymes (invertase, mutarotase and glucose oxidase) and was activated by two chemical input signals: sucrose and dissolved oxygen. The developed integrated enzyme logic gates produce local pH changes at the EIS sensor surface as a result of biochemical reactions activated by different combinations of chemical input signals, while the pH value of the bulk solution remains unchanged. The pH-induced charge changes at the gate-insulator (Ta2O5) surface of the EIS transducer result in an electronic signal corresponding to the logic output produced by the immobilised enzymes. The logic output signals have been read out by means of a constant-capacitance method.

  8. Variable elimination in chemical reaction networks with mass-action kinetics

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Wiuf, C.

    2012-01-01

    We consider chemical reaction networks taken with mass-action kinetics. The steady states of such a system are solutions to a system of polynomial equations. Even for small systems the task of finding the solutions is daunting. We develop an algebraic framework and procedure for linear elimination...

  9. Global asymptotic stability of BAM neural networks with distributed delays and reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122 (China)] e-mail: btcui@sohu.com; Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Rd., Wuxi, Jiangsu 214122 (China)

    2006-03-01

    The global asymptotic stability of bi-directional associative memory neural networks with distributed delays and reaction-diffusion terms are studied by using the analysis technique and Lyapunov functional. A sufficient condition is proposed. Two numerical examples are given to show the correctness of our analysis.

  10. MSU SINP CDFE nuclear data activities in the nuclear reaction data centres network

    International Nuclear Information System (INIS)

    This paper is the progress report of the Centre for Photonuclear Experiments Data, Moscow. It is a short review of the works carried out by the CDFE concerning the IAEA nuclear reaction data centers network activities from May 2001 until May 2002. and the description of the main results obtained. (a.n.)

  11. Summary report on [IAEA] technical meeting of the International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres was held at the IAEA Headquarters in Vienna from 25 to 26 May 2009. The meeting was attended by 23 participants from 13 cooperating data centres. A summary of the meeting is given in this report, along with the conclusions, actions, and status report of the participating data centres. (author)

  12. Biomolecular Assembly of Gold Nanocrystals

    Energy Technology Data Exchange (ETDEWEB)

    Micheel, Christine Marya

    2005-05-20

    Over the past ten years, methods have been developed to construct discrete nanostructures using nanocrystals and biomolecules. While these frequently consist of gold nanocrystals and DNA, semiconductor nanocrystals as well as antibodies and enzymes have also been used. One example of discrete nanostructures is dimers of gold nanocrystals linked together with complementary DNA. This type of nanostructure is also known as a nanocrystal molecule. Discrete nanostructures of this kind have a number of potential applications, from highly parallel self-assembly of electronics components and rapid read-out of DNA computations to biological imaging and a variety of bioassays. My research focused in three main areas. The first area, the refinement of electrophoresis as a purification and characterization method, included application of agarose gel electrophoresis to the purification of discrete gold nanocrystal/DNA conjugates and nanocrystal molecules, as well as development of a more detailed understanding of the hydrodynamic behavior of these materials in gels. The second area, the development of methods for quantitative analysis of transmission electron microscope data, used computer programs written to find pair correlations as well as higher order correlations. With these programs, it is possible to reliably locate and measure nanocrystal molecules in TEM images. The final area of research explored the use of DNA ligase in the formation of nanocrystal molecules. Synthesis of dimers of gold particles linked with a single strand of DNA possible through the use of DNA ligase opens the possibility for amplification of nanostructures in a manner similar to polymerase chain reaction. These three areas are discussed in the context of the work in the Alivisatos group, as well as the field as a whole.

  13. Pinning Control Strategies for Synchronization of Linearly Coupled Neural Networks With Reaction-Diffusion Terms.

    Science.gov (United States)

    Wang, Jin-Liang; Wu, Huai-Ning; Huang, Tingwen; Ren, Shun-Yan

    2016-04-01

    Two types of coupled neural networks with reaction-diffusion terms are considered in this paper. In the first one, the nodes are coupled through their states. In the second one, the nodes are coupled through the spatial diffusion terms. For the former, utilizing Lyapunov functional method and pinning control technique, we obtain some sufficient conditions to guarantee that network can realize synchronization. In addition, considering that the theoretical coupling strength required for synchronization may be much larger than the needed value, we propose an adaptive strategy to adjust the coupling strength for achieving a suitable value. For the latter, we establish a criterion for synchronization using the designed pinning controllers. It is found that the coupled reaction-diffusion neural networks with state coupling under the given linear feedback pinning controllers can realize synchronization when the coupling strength is very large, which is contrary to the coupled reaction-diffusion neural networks with spatial diffusion coupling. Moreover, a general criterion for ensuring network synchronization is derived by pinning a small fraction of nodes with adaptive feedback controllers. Finally, two examples with numerical simulations are provided to demonstrate the effectiveness of the theoretical results. PMID:25955852

  14. On a theory of stability for nonlinear stochastic chemical reaction networks

    International Nuclear Information System (INIS)

    We present elements of a stability theory for small, stochastic, nonlinear chemical reaction networks. Steady state probability distributions are computed with zero-information (ZI) closure, a closure algorithm that solves chemical master equations of small arbitrary nonlinear reactions. Stochastic models can be linearized around the steady state with ZI-closure, and the eigenvalues of the Jacobian matrix can be readily computed. Eigenvalues govern the relaxation of fluctuation autocorrelation functions at steady state. Autocorrelation functions reveal the time scales of phenomena underlying the dynamics of nonlinear reaction networks. In accord with the fluctuation-dissipation theorem, these functions are found to be congruent to response functions to small perturbations. Significant differences are observed in the stability of nonlinear reacting systems between deterministic and stochastic modeling formalisms

  15. Nanoarchitectonics of biomolecular assemblies for functional applications

    Science.gov (United States)

    Avinash, M. B.; Govindaraju, T.

    2014-10-01

    The stringent processes of natural selection and evolution have enabled extraordinary structure-function properties of biomolecules. Specifically, the archetypal designs of biomolecules, such as amino acids, nucleobases, carbohydrates and lipids amongst others, encode unparalleled information, selectivity and specificity. The integration of biomolecules either with functional molecules or with an embodied functionality ensures an eclectic approach for novel and advanced nanotechnological applications ranging from electronics to biomedicine, besides bright prospects in systems chemistry and synthetic biology. Given this intriguing scenario, our feature article intends to shed light on the emerging field of functional biomolecular engineering.

  16. Nanotube-Based Chemical and Biomolecular Sensors

    Institute of Scientific and Technical Information of China (English)

    J.Koh; B.Kim; S.Hong; H.Lim; H.C.Choi

    2008-01-01

    We present a brief review about recent results regarding carbon nanotube (CNT)-based chemical and biomolecular sensors. For the fabrication of CNT-based sensors, devices containing CNT channels between two metal electrodes are first fabricated usually via chemical vapor deposition (CVD) process or "surface programmed assembly" method. Then, the CNT surfaces are often functionalized to enhance the selectivity of the sensors. Using this process, highly-sensitive CNT-based sensors can be fabricated for the selective detection of various chemical and biological molecules such as hydrogen, ammonia, carbon monoxide, chlorine gas, DNA, glucose, alcohol, and proteins.

  17. Scalable Molecular Dynamics for Large Biomolecular Systems

    Directory of Open Access Journals (Sweden)

    Robert K. Brunner

    2000-01-01

    Full Text Available We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

  18. Micro and Nanotechnologies Enhanced Biomolecular Sensing

    Directory of Open Access Journals (Sweden)

    Tza-Huei Wang

    2013-07-01

    Full Text Available This editorial summarizes some of the recent advances of micro and nanotechnology-based tools and devices for biomolecular detection. These include the incorporation of nanomaterials into a sensor surface or directly interfacing with molecular probes to enhance target detection via more rapid and sensitive responses, and the use of self-assembled organic/inorganic nanocomposites that inhibit exceptional spectroscopic properties to enable facile homogenous assays with efficient binding kinetics. Discussions also include some insight into microfluidic principles behind the development of an integrated sample preparation and biosensor platform toward a miniaturized and fully functional system for point of care applications.

  19. HRSSA - Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

    Science.gov (United States)

    Marchetti, Luca; Priami, Corrado; Thanh, Vo Hong

    2016-07-01

    This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

  20. Improvements in continuum modeling for biomolecular systems

    Science.gov (United States)

    Yu, Qiao; Ben-Zhuo, Lu

    2016-01-01

    Modeling of biomolecular systems plays an essential role in understanding biological processes, such as ionic flow across channels, protein modification or interaction, and cell signaling. The continuum model described by the Poisson- Boltzmann (PB)/Poisson-Nernst-Planck (PNP) equations has made great contributions towards simulation of these processes. However, the model has shortcomings in its commonly used form and cannot capture (or cannot accurately capture) some important physical properties of the biological systems. Considerable efforts have been made to improve the continuum model to account for discrete particle interactions and to make progress in numerical methods to provide accurate and efficient simulations. This review will summarize recent main improvements in continuum modeling for biomolecular systems, with focus on the size-modified models, the coupling of the classical density functional theory and the PNP equations, the coupling of polar and nonpolar interactions, and numerical progress. Project supported by the National Natural Science Foundation of China (Grant No. 91230106) and the Chinese Academy of Sciences Program for Cross & Cooperative Team of the Science & Technology Innovation.

  1. Coassembly of aromatic dipeptides into biomolecular necklaces.

    Science.gov (United States)

    Yuran, Sivan; Razvag, Yair; Reches, Meital

    2012-11-27

    This paper describes the formation of complex peptide-based structures by the coassembly of two simple peptides, the diphenylalanine peptide and its tert-butyl dicarbonate (Boc) protected analogue. Each of these peptides can self-assemble into a distinct architecture: the diphenylalanine peptide into tubular structures and its analogue into spheres. Integrated together, these peptides coassemble into a construction of beaded strings, where spherical assemblies are connected by elongated elements. Electron and scanning force microscopy demonstrated the morphology of these structures, which we termed "biomolecular necklaces". Additional experiments indicated the reversibility of the coassembly process and the stability of the structures. Furthermore, we suggest a possible mechanism of formation for the biomolecular necklaces. Our suggestion is based on the necklace model for polyelectrolyte chains, which proposes that a necklace structure appears as a result of counterion condensation on the backbone of a polyelectrolyte. Overall, the approach of coassembly, demonstrated using aromatic peptides, can be adapted to any peptides and may lead to the development and discovery of new self-assembled architectures formed by peptides and other biomolecules. PMID:23061818

  2. Water formation at low temperatures by surface O2 hydrogenation II: the reaction network

    CERN Document Server

    Cuppen, H M; Romanzin, C; Linnartz, H; 10.1039/C0CP00251H

    2010-01-01

    Water is abundantly present in the Universe. It is the main component of interstellar ice mantles and a key ingredient for life. Water in space is mainly formed through surface reactions. Three formation routes have been proposed in the past: hydrogenation of surface O, O2, and O3. In a previous paper [Ioppolo et al., Astrophys. J., 2008, 686, 1474] we discussed an unexpected non-standard zeroth-order H2O2 production behaviour in O2 hydrogenation experiments, which suggests that the proposed reaction network is not complete, and that the reaction channels are probably more interconnected than previously thought. In this paper we aim to derive the full reaction scheme for O2 surface hydrogenation and to constrain the rates of the individual reactions. This is achieved through simultaneous H-atom and O2 deposition under ultra-high vacuum conditions for astronomically relevant temperatures. Different H/O2 ratios are used to trace different stages in the hydrogenation network. The chemical changes in the forming ...

  3. Global exponential stability of Hopfield reaction-diffusion neural networks with time-varying delays

    Institute of Scientific and Technical Information of China (English)

    王林山; 徐道义

    2003-01-01

    The authors analyze the existence of the equilibrium point and global exponential stability for Hopfield reaction-diffusion neural networks with time-varying delays by means of the topological degree theory and generalized Halanay inequality. Since the diffusion phenomena and time delay could not be ignored in neural networks and electric circuits, the model presented here is close to the actual systems, and the sufficient conditions on global exponential stability established in this paper,which are easily verifiable, have a wider adaptive range.

  4. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting), held at the Brookhaven National Laboratory, Upton, NY, USA from 4-7 October 2004. The meeting was attended by 20 participants from 11 co-operating data centres of six Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, status reports of the participating data centres, and a revised technical protocol for the cooperation of the network. (author)

  5. Deterministic characterization of phase noise in biomolecular oscillators

    International Nuclear Information System (INIS)

    On top of the many external perturbations, cellular oscillators also face intrinsic perturbations due the randomness of chemical kinetics. Biomolecular oscillators, distinct in their parameter sets or distinct in their architecture, show different resilience with respect to such intrinsic perturbations. Assessing this resilience can be done by ensemble stochastic simulations. These are computationally costly and do not permit further insights into the mechanistic cause of the observed resilience. For reaction systems operating at a steady state, the linear noise approximation (LNA) can be used to determine the effect of molecular noise. Here we show that methods based on LNA fail for oscillatory systems and we propose an alternative ansatz. It yields an asymptotic expression for the phase diffusion coefficient of stochastic oscillators. Moreover, it allows us to single out the noise contribution of every reaction in an oscillatory system. We test the approach on the one-loop model of the Drosophila circadian clock. Our results are consistent with those obtained through stochastic simulations with a gain in computational efficiency of about three orders of magnitude

  6. Coupling sample paths to the partial thermodynamic limit in stochastic chemical reaction networks

    CERN Document Server

    Levien, Ethan

    2016-01-01

    We present a new technique for reducing the variance in Monte Carlo estimators of stochastic chemical reaction networks. Our method makes use of the fact that many stochastic reaction networks converge to piecewise deterministic Markov processes in the large system-size limit. The statistics of the piecewise deterministic process can be obtained much more efficiently than those of the exact process. By coupling sample paths of the exact model to the piecewise deterministic process we are able to reduce the variance, and hence the computational complexity of the Monte Carlo estimator. In addition to rigorous results concerning the asymptotic behavior of our method, numerical simulations are performed on some simple biological models suggesting that significant computational gains are made for even moderate system-sizes.

  7. Pd-PEG-PU polymer networks: A convenient catalyst for hydrogenation and Suzuki coupling reactions

    International Nuclear Information System (INIS)

    Polyethyleneglycol-polyurethane (PEG-PU) polymer network films with sodium tetrachloropalladate were fabricated by solution casting technique. The incorporated palladium ions were reduced using sodium borohydride to obtain zero-valent (metallic) palladium in the films. These films were characterized by X-ray diffraction, Fourier transform-infra red spectroscopy, atomic absorption spectroscopy and X-ray photoelectron spectroscopy for their structure and chemical composition. The films containing palladium metal are found to be highly efficient toward hydrogenation of a number of unsaturated organic compounds and Suzuki coupling reactions of haloarenes. The novelty of this catalyst system is the incorporation of palladium in the polymer network that renders the catalyst system's reusability because there is no leaching of the metal from the polymer matrix and as the catalyst system is in the form of a compact film it can be easily separated from the reaction mixture and can be reused.

  8. Doubly Periodic Traveling Waves in a Cellular Neural Network with Linear Reaction

    Directory of Open Access Journals (Sweden)

    Lin JianJhong

    2009-01-01

    Full Text Available Szekeley observed that the dynamic pattern of the locomotion of salamanders can be explained by periodic vector sequences generated by logical neural networks. Such sequences can mathematically be described by "doubly periodic traveling waves" and therefore it is of interest to propose dynamic models that may produce such waves. One such dynamic network model is built here based on reaction-diffusion principles and a complete discussion is given for the existence of doubly periodic waves as outputs. Since there are 2 parameters in our model and 4 a priori unknown parameters involved in our search of solutions, our results are nontrivial. The reaction term in our model is a linear function and hence our results can also be interpreted as existence criteria for solutions of a nontrivial linear problem depending on 6 parameters.

  9. INFLUENCE OF NOISE AND DELAY ON REACTION-DIFFUSION RECURRENT NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Li Wu

    2006-01-01

    In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks (RNNs) with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria.

  10. Report on the IAEA technical meeting of the International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting of the International Network of Nuclear Reaction Data Centres was held at IAEA Headquarters, Vienna, Austria, from 8 to 10 October 2007. The meeting was attended by 19 participants from 11 cooperating data centres of six Member States and two international organizations. A summary of the meeting is given in this report, along with the conclusions, actions, and status reports of the participating data centres. (author)

  11. Report on the IAEA technical meeting on the network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    Results of the IAEA Technical meeting on the Network of Nuclear Reaction Data Centres held at the IAEA Headquarters, Vienna, Austria, 12 to 14 October 2005, are summarized in this report. The meeting was attended by 16 participants from 11 co-operating data centres of six Member States and two International Organizations. The report contains a summary of the meeting, the conclusions and actions, and status reports of the participating data centres. (author)

  12. Product-form stationary distributions for deficiency zero chemical reaction networks

    OpenAIRE

    Anderson, David F.; Craciun, Gheorghe; Kurtz, Thomas G.

    2008-01-01

    We consider stochastically modeled chemical reaction systems with mass-action kinetics and prove that a product-form stationary distribution exists for each closed, irreducible subset of the state space if an analogous deterministically modeled system with mass-action kinetics admits a complex balanced equilibrium. Feinberg's deficiency zero theorem then implies that such a distribution exists so long as the corresponding chemical network is weakly reversible and has a deficiency of zero. The...

  13. Report on the IAEA advisory group meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Advisory Group Meeting (AGM) on Network of Nuclear Reaction Data Centres, hold at the Institute of Physics and Power Engineering, Obninsk, Russia, 15 to 19 May 2000. The meeting was attended by 28 participants from 13 co-operating data centres from seven Member States and two International Organizations. The report contains a meeting summary, the conclusions and actions, progress and status reports of the participating data centres and working papers considered at the meeting. (author)

  14. Summary Report of the Technical Meeting on International Network of Nuclear Reaction Data Centres

    International Nuclear Information System (INIS)

    This report summarizes the IAEA Technical Meeting on the International Network of Nuclear Reaction Data Centres, held at the IAEA Headquarters in Vienna, Austria from 23 to 25 April 2013. The meeting was attended by 24 participants representing 13 cooperative centres from 8 Member States and 2 International Organisations. A summary of the meeting is given in this report along with the conclusions and actions. (author)

  15. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (and the biennial Data Centre Heads' Meeting) was held at the OECD Nuclear Energy Agency, Issy-les-Moulineaux (near Paris), France, from 27 to 30 May 2002. The meeting was attended by 21 participants from 12 co-operating data centres of six Member States and two international organizations. This report contains the meeting summary, conclusions and actions, status reports of the participating data centres, and working papers considered. (author)

  16. Report on the IAEA technical meeting on network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    An IAEA Technical Meeting on the Network of Nuclear Reaction Data Centres (biennial Data Centre Heads Meeting) was held at IAEA Headquarters, Vienna, Austria, from 25 to 28 September 2006. The meeting was attended by 19 participants from 10 cooperating data centres of six Member States and two international organizations. A summary of the meeting is given in this report, along with the conclusions, actions, and status reports of the participating data centres. (author)

  17. A reaction-diffusion model of ROS-induced ROS release in a mitochondrial network.

    Directory of Open Access Journals (Sweden)

    Lufang Zhou

    2010-01-01

    Full Text Available Loss of mitochondrial function is a fundamental determinant of cell injury and death. In heart cells under metabolic stress, we have previously described how the abrupt collapse or oscillation of the mitochondrial energy state is synchronized across the mitochondrial network by local interactions dependent upon reactive oxygen species (ROS. Here, we develop a mathematical model of ROS-induced ROS release (RIRR based on reaction-diffusion (RD-RIRR in one- and two-dimensional mitochondrial networks. The nodes of the RD-RIRR network are comprised of models of individual mitochondria that include a mechanism of ROS-dependent oscillation based on the interplay between ROS production, transport, and scavenging; and incorporating the tricarboxylic acid (TCA cycle, oxidative phosphorylation, and Ca(2+ handling. Local mitochondrial interaction is mediated by superoxide (O2.- diffusion and the O2.(--dependent activation of an inner membrane anion channel (IMAC. In a 2D network composed of 500 mitochondria, model simulations reveal DeltaPsi(m depolarization waves similar to those observed when isolated guinea pig cardiomyocytes are subjected to a localized laser-flash or antioxidant depletion. The sensitivity of the propagation rate of the depolarization wave to O(2.- diffusion, production, and scavenging in the reaction-diffusion model is similar to that observed experimentally. In addition, we present novel experimental evidence, obtained in permeabilized cardiomyocytes, confirming that DeltaPsi(m depolarization is mediated specifically by O2.-. The present work demonstrates that the observed emergent macroscopic properties of the mitochondrial network can be reproduced in a reaction-diffusion model of RIRR. Moreover, the findings have uncovered a novel aspect of the synchronization mechanism, which is that clusters of mitochondria that are oscillating can entrain mitochondria that would otherwise display stable dynamics. The work identifies the

  18. On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

    International Nuclear Information System (INIS)

    Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency

  19. Pattern formation on networks with reactions: A continuous-time random-walk approach

    Science.gov (United States)

    Angstmann, C. N.; Donnelly, I. C.; Henry, B. I.

    2013-03-01

    We derive the generalized master equation for reaction-diffusion on networks from an underlying stochastic process, the continuous time random walk (CTRW). The nontrivial incorporation of the reaction process into the CTRW is achieved by splitting the derivation into two stages. The reactions are treated as birth-death processes and the first stage of the derivation is at the single particle level, taking into account the death process, while the second stage considers an ensemble of these particles including the birth process. Using this model we have investigated different types of pattern formation across the vertices on a range of networks. Importantly, the CTRW defines the Laplacian operator on the network in a non-ad hoc manner and the pattern formation depends on the structure of this Laplacian. Here we focus attention on CTRWs with exponential waiting times for two cases: one in which the rate parameter is constant for all vertices and the other where the rate parameter is proportional to the vertex degree. This results in nonsymmetric and symmetric CTRW Laplacians, respectively. In the case of symmetric Laplacians, pattern formation follows from the Turing instability. However in nonsymmetric Laplacians, pattern formation may be possible with or without a Turing instability.

  20. On the rejection-based algorithm for simulation and analysis of large-scale reaction networks

    Science.gov (United States)

    Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado

    2015-06-01

    Stochastic simulation for in silico studies of large biochemical networks requires a great amount of computational time. We recently proposed a new exact simulation algorithm, called the rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)], to improve simulation performance by postponing and collapsing as much as possible the propensity updates. In this paper, we analyze the performance of this algorithm in detail, and improve it for simulating large-scale biochemical reaction networks. We also present a new algorithm, called simultaneous RSSA (SRSSA), which generates many independent trajectories simultaneously for the analysis of the biochemical behavior. SRSSA improves simulation performance by utilizing a single data structure across simulations to select reaction firings and forming trajectories. The memory requirement for building and storing the data structure is thus independent of the number of trajectories. The updating of the data structure when needed is performed collectively in a single operation across the simulations. The trajectories generated by SRSSA are exact and independent of each other by exploiting the rejection-based mechanism. We test our new improvement on real biological systems with a wide range of reaction networks to demonstrate its applicability and efficiency.

  1. Biomolecular Structure Determination with Divide and Concur

    Science.gov (United States)

    Kallus, Yoav; Elser, Veit

    2009-03-01

    Divide and concur (D-C) is a general computational approach, designed for the solution of highly frustrated problems. Recently applied to the problems of disk packing, the kissing number problem, and 3-SAT, it was competitive or outperformed special-purpose methods.ootnotetextS. Gravel and V. Elser, Phys. Rev. E 78, 036706 (2008) We present a method for applying the D-C framework to the problem of biomolecular structure determination. From a list of geometric constraints on groups of atoms in the molecule, we construct a deterministic iterative map that efficiently searches for structures simultaneously satisfying all constraints. As our method eschews an energy function and its minimization to focus on geometric constraints, it can very naturally integrate with the geometric constraints due to chemistry and physics, experimental constraints due to NMR data or many other experimental or biological hints. We present some results of our method.

  2. Ensemble based convergence assessment of biomolecular trajectories

    CERN Document Server

    Lyman, E; Lyman, Edward; Zuckerman, Daniel M.

    2006-01-01

    Assessing the convergence of a biomolecular simulation is an essential part of any computational investigation. This is because many important quantities (e.g., free energy differences) depend on the relative populations of different conformers; insufficient convergence translates into systematic errors. Here we present a simple method to self-consistently assess the convergence of a simulation. Standard clustering methods first generate a set of reference structures to any desired precision. The trajectory is then classified by proximity to the reference structures, yielding a one-dimensional histogram of structurally distinct populations. Comparing ensembles of different trajectories (or different parts of the same trajectory) built with the same reference structures provides a sensitive, quantitative measure of convergence. Please note: this is a preliminary manuscript, and should be read as such. Comments are most welcome, especially regarding pertinent prior work.

  3. Micro- and nanodevices integrated with biomolecular probes.

    Science.gov (United States)

    Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A

    2015-12-01

    Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. PMID:26363089

  4. Micro- and nanodevices integrated with biomolecular probes

    Science.gov (United States)

    Alapan, Yunus; Icoz, Kutay; Gurkan, Umut A.

    2016-01-01

    Understanding how biomolecules, proteins and cells interact with their surroundings and other biological entities has become the fundamental design criterion for most biomedical micro- and nanodevices. Advances in biology, medicine, and nanofabrication technologies complement each other and allow us to engineer new tools based on biomolecules utilized as probes. Engineered micro/nanosystems and biomolecules in nature have remarkably robust compatibility in terms of function, size, and physical properties. This article presents the state of the art in micro- and nanoscale devices designed and fabricated with biomolecular probes as their vital constituents. General design and fabrication concepts are presented and three major platform technologies are highlighted: microcantilevers, micro/nanopillars, and microfluidics. Overview of each technology, typical fabrication details, and application areas are presented by emphasizing significant achievements, current challenges, and future opportunities. PMID:26363089

  5. Biomolecular Markers in Cancer of the Tongue

    Directory of Open Access Journals (Sweden)

    Daris Ferrari

    2009-01-01

    Full Text Available The incidence of tongue cancer is increasing worldwide, and its aggressiveness remains high regardless of treatment. Genetic changes and the expression of abnormal proteins have been frequently reported in the case of head and neck cancers, but the little information that has been published concerning tongue tumours is often contradictory. This review will concentrate on the immunohistochemical expression of biomolecular markers and their relationships with clinical behaviour and prognosis. Most of these proteins are associated with nodal stage, tumour progression and metastases, but there is still controversy concerning their impact on disease-free and overall survival, and treatment response. More extensive clinical studies are needed to identify the patterns of molecular alterations and the most reliable predictors in order to develop tailored anti-tumour strategies based on the targeting of hypoxia markers, vascular and lymphangiogenic factors, epidermal growth factor receptors, intracytoplasmatic signalling and apoptosis.

  6. A unified biological modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2013-12-01

    In order to understand the biological response in a cell, a researcher has to create a biological network and design an experiment to prove it. Although biological knowledge has been accumulated, we still don't have enough biological models to explain complex biological phenomena. If a new biological network is to be created, integrated modeling software supporting various biological models is required. In this research, we design and implement a unified biological modeling and simulation system, called ezBioNet, for analyzing biological reaction networks. ezBioNet designs kinetic and Boolean network models and simulates the biological networks using a server-side simulation system with Object Oriented Parallel Accelerator Library framework. The main advantage of ezBioNet is that a user can create a biological network by using unified modeling canvas of kinetic and Boolean models and perform massive simulations, including Ordinary Differential Equation analyses, sensitivity analyses, parameter estimates and Boolean network analysis. ezBioNet integrates useful biological databases, including the BioModels database, by connecting European Bioinformatics Institute servers through Web services Application Programming Interfaces. In addition, we employ Eclipse Rich Client Platform, which is a powerful modularity framework to allow various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool and a simulation system for understanding the control mechanism by monitoring the change of each component in a biological network. The simulation result can be managed and visualized on ezBioNet, which is available free of charge at http://ezbionet.sourceforge.net or http://ezbionet.cbnu.ac.kr.

  7. FERN – a Java framework for stochastic simulation and evaluation of reaction networks

    Science.gov (United States)

    Erhard, Florian; Friedel, Caroline C; Zimmer, Ralf

    2008-01-01

    Background Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a) do not provide the most efficient simulation algorithms and are difficult to extend, b) cannot be easily integrated into other applications or c) do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. Results In this article, we present FERN (Framework for Evaluation of Reaction Networks), a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. Conclusion FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward way both as a stand

  8. FERN – a Java framework for stochastic simulation and evaluation of reaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2008-08-01

    Full Text Available Abstract Background Stochastic simulation can be used to illustrate the development of biological systems over time and the stochastic nature of these processes. Currently available programs for stochastic simulation, however, are limited in that they either a do not provide the most efficient simulation algorithms and are difficult to extend, b cannot be easily integrated into other applications or c do not allow to monitor and intervene during the simulation process in an easy and intuitive way. Thus, in order to use stochastic simulation in innovative high-level modeling and analysis approaches more flexible tools are necessary. Results In this article, we present FERN (Framework for Evaluation of Reaction Networks, a Java framework for the efficient simulation of chemical reaction networks. FERN is subdivided into three layers for network representation, simulation and visualization of the simulation results each of which can be easily extended. It provides efficient and accurate state-of-the-art stochastic simulation algorithms for well-mixed chemical systems and a powerful observer system, which makes it possible to track and control the simulation progress on every level. To illustrate how FERN can be easily integrated into other systems biology applications, plugins to Cytoscape and CellDesigner are included. These plugins make it possible to run simulations and to observe the simulation progress in a reaction network in real-time from within the Cytoscape or CellDesigner environment. Conclusion FERN addresses shortcomings of currently available stochastic simulation programs in several ways. First, it provides a broad range of efficient and accurate algorithms both for exact and approximate stochastic simulation and a simple interface for extending to new algorithms. FERN's implementations are considerably faster than the C implementations of gillespie2 or the Java implementations of ISBJava. Second, it can be used in a straightforward

  9. Biomolecular detection employing the Interferometric Reflectance Imaging Sensor (IRIS).

    Science.gov (United States)

    Lopez, Carlos A; Daaboul, George G; Ahn, Sunmin; Reddington, Alexander P; Monroe, Margo R; Zhang, Xirui; Irani, Rostem J; Yu, Chunxiao; Genco, Caroline A; Cretich, Marina; Chiari, Marcella; Goldberg, Bennett B; Connor, John H; Ünlü, M Selim

    2011-01-01

    The sensitive measurement of biomolecular interactions has use in many fields and industries such as basic biology and microbiology, environmental/agricultural/biodefense monitoring, nanobiotechnology, and more. For diagnostic applications, monitoring (detecting) the presence, absence, or abnormal expression of targeted proteomic or genomic biomarkers found in patient samples can be used to determine treatment approaches or therapy efficacy. In the research arena, information on molecular affinities and specificities are useful for fully characterizing the systems under investigation. Many of the current systems employed to determine molecular concentrations or affinities rely on the use of labels. Examples of these systems include immunoassays such as the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR) techniques, gel electrophoresis assays, and mass spectrometry (MS). Generally, these labels are fluorescent, radiological, or colorimetric in nature and are directly or indirectly attached to the molecular target of interest. Though the use of labels is widely accepted and has some benefits, there are drawbacks which are stimulating the development of new label-free methods for measuring these interactions. These drawbacks include practical facets such as increased assay cost, reagent lifespan and usability, storage and safety concerns, wasted time and effort in labelling, and variability among the different reagents due to the labelling processes or labels themselves. On a scientific research basis, the use of these labels can also introduce difficulties such as concerns with effects on protein functionality/structure due to the presence of the attached labels and the inability to directly measure the interactions in real time. Presented here is the use of a new label-free optical biosensor that is amenable to microarray studies, termed the Interferometric Reflectance Imaging Sensor (IRIS), for detecting proteins, DNA, antigenic material

  10. ezBioNet: A modeling and simulation system for analyzing biological reaction networks

    Science.gov (United States)

    Yu, Seok Jong; Tung, Thai Quang; Park, Junho; Lim, Jongtae; Yoo, Jaesoo

    2012-10-01

    To achieve robustness against living environments, a living organism is composed of complicated regulatory mechanisms ranging from gene regulations to signal transduction. If such life phenomena are to be understand, an integrated analysis tool that should have modeling and simulation functions for biological reactions, as well as new experimental methods for measuring biological phenomena, is fundamentally required. We have designed and implemented modeling and simulation software (ezBioNet) for analyzing biological reaction networks. The software can simultaneously perform an integrated modeling of various responses occurring in cells, ranging from gene expressions to signaling processes. To support massive analysis of biological networks, we have constructed a server-side simulation system (VCellSim) that can perform ordinary differential equations (ODE) analysis, sensitivity analysis, and parameter estimates. ezBioNet integrates the BioModel database by connecting the european bioinformatics institute (EBI) servers through Web services APIs and supports the handling of systems biology markup language (SBML) files. In addition, we employed eclipse RCP (rich client platform) which is a powerful modularity framework allowing various functional expansions. ezBioNet is intended to be an easy-to-use modeling tool, as well as a simulation system, to understand the control mechanism by monitoring the change of each component in a biological network. A researcher may perform the kinetic modeling and execute the simulation. The simulation result can be managed and visualized on ezBioNet, which is freely available at http://ezbionet.cbnu.ac.kr.

  11. Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text

    OpenAIRE

    Garg, Sahil; Galstyan, Aram; Hermjakob, Ulf; Marcu, Daniel

    2015-01-01

    We advance the state of the art in biomolecular interaction extraction with three contributions: (i) We show that deep, Abstract Meaning Representations (AMR) significantly improve the accuracy of a biomolecular interaction extraction system when compared to a baseline that relies solely on surface- and syntax-based features; (ii) In contrast with previous approaches that infer relations on a sentence-by-sentence basis, we expand our framework to enable consistent predictions over sets of sen...

  12. Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales

    Directory of Open Access Journals (Sweden)

    Kaihong Zhao

    2010-01-01

    Full Text Available The existence of equilibrium solutions to reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales is proved by the topological degree theory and M-matrix method. Under some sufficient conditions, we obtain the uniqueness and global exponential stability of equilibrium solution to reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales by constructing suitable Lyapunov functional and inequality skills. One example is given to illustrate the effectiveness of our results.

  13. Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality

    Science.gov (United States)

    Grytskyy, Dmytro; Diesmann, Markus; Helias, Moritz

    2016-06-01

    Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate-based model neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the nonlinearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime metastable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated.

  14. Residual analysis of ground reaction forces simulation during gait using neural networks with different configurations.

    Science.gov (United States)

    Leporace, Gustavo; Batista, Luiz Alberto; Metsavaht, Leonardo; Nadal, Jurandir

    2015-08-01

    The aim of the study was to analyze and compare the residuals obtained from ground reaction force (GRF) models developed using two different neural network configurations (one network with three outputs; and three networks with one output each), based on accelerometer data. Seventeen healthy subjects walked along a walkway, with a force plate embedded, with a three dimensional accelerometer attached to the shank. Multilayer perceptron networks (MLP) models were developed with the 3D accelerometer data as inputs to predict the GRF. The residuals of these models were evaluated graphically and numerically to verify the fitting. A visual analysis of the simulated signals suggests the model was able to adequately predict the GRF. The errors and correlations found in the MLP models for the 3D GRF is at least similar to other studies, although some of them showed higher errors. There was not difference between the two MLP configurations. However, despite the high correlation coefficient and closeness to a normal probability distribution, the residual analysis still presented a higher kurtosis and skewness, suggesting that the inclusion of other variables and the increase of the validation sample size could increase the fitting of the simulation. PMID:26736876

  15. Biomolecular surface construction by PDE transform.

    Science.gov (United States)

    Zheng, Qiong; Yang, Siyang; Wei, Guo-Wei

    2012-03-01

    This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a

  16. Combined Geometric and Neural Network Approach to Generic Fault Diagnosis in Satellite Reaction Wheels

    DEFF Research Database (Denmark)

    Baldi, P.; Blanke, Mogens; Castaldi, P.; Mimmo, N.; Simani, S.

    2015-01-01

    This paper suggests a novel diagnosis scheme for detection, isolation and estimation of faults affecting satellite reaction wheels. Both spin rate measurements and actuation torque defects are dealt with. The proposed system consists of a fault detection and isolation module composed by a bank of...... residual filters organized in a generalized scheme, followed by a fault estimation module consisting of a bank of adaptive estimation filters. The residuals are decoupled from aerodynamic disturbances thanks to the Nonlinear Geometric Approach. The use of Radial Basis Function Neural Networks is shown to...... allow design of generalized fault estimation filters, which do not need a priori information about the faults internal model. Simulation results with a detailed nonlinear spacecraft model, which includes disturbances, show that the proposed diagnosis scheme can deal with faults affecting both reaction...

  17. Elucidation of Diels-Alder Reaction Network of 2,5-Dimethylfuran and Ethylene on HY Zeolite Catalyst

    Energy Technology Data Exchange (ETDEWEB)

    Do, Phuong T. M. [Univ. of Delaware, Newark, DE (United States); McAtee, Jesse R. [Univ. of Delaware, Newark, DE (United States); Watson, Donald A. [Univ. of Delaware, Newark, DE (United States); Lobo, Raul F. [Univ. of Delaware, Newark, DE (United States)

    2012-12-12

    The reaction of 2,5-dimethylfuran and ethylene to produce p-xylene represents a potentially important route for the conversion of biomass to high-value organic chemicals. Current preparation methods suffer from low selectivity and produce a number of byproducts. Using modern separation and analytical techniques, the structures of many of the byproducts produced in this reaction when HY zeolite is employed as a catalyst have been identified. From these data, a detailed reaction network is proposed, demonstrating that hydrolysis and electrophilic alkylation reactions compete with the desired Diels–Alder/dehydration sequence. This information will allow the rational identification of more selective catalysts and more selective reaction conditions.

  18. Integrated Spintronic Platforms for Biomolecular Recognition Detection

    Science.gov (United States)

    Martins, V. C.; Cardoso, F. A.; Loureiro, J.; Mercier, M.; Germano, J.; Cardoso, S.; Ferreira, R.; Fonseca, L. P.; Sousa, L.; Piedade, M. S.; Freitas, P. P.

    2008-06-01

    This paper covers recent developments in magnetoresistive based biochip platforms fabricated at INESC-MN, and their application to the detection and quantification of pathogenic waterborn microorganisms in water samples for human consumption. Such platforms are intended to give response to the increasing concern related to microbial contaminated water sources. The presented results concern the development of biological active DNA chips and protein chips and the demonstration of the detection capability of the present platforms. Two platforms are described, one including spintronic sensors only (spin-valve based or magnetic tunnel junction based), and the other, a fully scalable platform where each probe site consists of a MTJ in series with a thin film diode (TFD). Two microfluidic systems are described, for cell separation and concentration, and finally, the read out and control integrated electronics are described, allowing the realization of bioassays with a portable point of care unit. The present platforms already allow the detection of complementary biomolecular target recognition with 1 pM concentration.

  19. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  20. Biochemical Filter with Sigmoidal Response: Increasing the Complexity of Biomolecular Logic

    CERN Document Server

    Privman, Vladimir; Arugula, Mary A; Melnikov, Dmitriy; Bocharova, Vera; Katz, Evgeny

    2010-01-01

    The first realization of a designed, rather than natural, biochemical filter process is reported and analyzed as a promising network component for increasing the complexity of biomolecular logic systems. Key challenge in biochemical logic research has been achieving scalability for complex network designs. Various logic gates have been realized, but a "toolbox" of analog elements for interconnectivity and signal processing has remained elusive. Filters are important as network elements that allow control of noise in signal transmission and conversion. We report a versatile biochemical filtering mechanism designed to have sigmoidal response in combination with signal-conversion process. Horseradish peroxidase-catalyzed oxidation of chromogenic electron donor by hydrogen peroxide, was altered by adding ascorbate, allowing to selectively suppress the output signal, modifying the response from convex to sigmoidal. A kinetic model was developed for evaluation of the quality of filtering. The results offer improved...

  1. Simulation and Statistical Inference of Stochastic Reaction Networks with Applications to Epidemic Models

    KAUST Repository

    Moraes, Alvaro

    2015-01-01

    Epidemics have shaped, sometimes more than wars and natural disasters, demo- graphic aspects of human populations around the world, their health habits and their economies. Ebola and the Middle East Respiratory Syndrome (MERS) are clear and current examples of potential hazards at planetary scale. During the spread of an epidemic disease, there are phenomena, like the sudden extinction of the epidemic, that can not be captured by deterministic models. As a consequence, stochastic models have been proposed during the last decades. A typical forward problem in the stochastic setting could be the approximation of the expected number of infected individuals found in one month from now. On the other hand, a typical inverse problem could be, given a discretely observed set of epidemiological data, infer the transmission rate of the epidemic or its basic reproduction number. Markovian epidemic models are stochastic models belonging to a wide class of pure jump processes known as Stochastic Reaction Networks (SRNs), that are intended to describe the time evolution of interacting particle systems where one particle interacts with the others through a finite set of reaction channels. SRNs have been mainly developed to model biochemical reactions but they also have applications in neural networks, virus kinetics, and dynamics of social networks, among others. 4 This PhD thesis is focused on novel fast simulation algorithms and statistical inference methods for SRNs. Our novel Multi-level Monte Carlo (MLMC) hybrid simulation algorithms provide accurate estimates of expected values of a given observable of SRNs at a prescribed final time. They are designed to control the global approximation error up to a user-selected accuracy and up to a certain confidence level, and with near optimal computational work. We also present novel dual-weighted residual expansions for fast estimation of weak and strong errors arising from the MLMC methodology. Regarding the statistical inference

  2. Effects of network dissolution changes on pore-to-core upscaled reaction rates for kaolinite and anorthite reactions under acidic conditions

    KAUST Repository

    Kim, Daesang

    2013-11-01

    We have extended reactive flow simulation in pore-network models to include geometric changes in the medium from dissolution effects. These effects include changes in pore volume and reactive surface area, as well as topological changes that open new connections. The computed changes were based upon a mineral map from an X-ray computed tomography image of a sandstone core. We studied the effect of these changes on upscaled (pore-scale to core-scale) reaction rates and compared against the predictions of a continuum model. Specifically, we modeled anorthite and kaolinite reactions under acidic flow conditions during which the anorthite reactions remain far from equilibrium (dissolution only), while the kaolinite reactions can be near-equilibrium. Under dissolution changes, core-scale reaction rates continuously and nonlinearly evolved in time. At higher injection rates, agreement with predictions of the continuum model degraded significantly. For the far-from-equilibrium reaction, our results indicate that the ability to correctly capture the heterogeneity in dissolution changes in the reactive mineral surface area is critical to accurately predict upscaled reaction rates. For the near-equilibrium reaction, the ability to correctly capture the heterogeneity in the saturation state remains critical. Inclusion of a Nernst-Planck term to ensure neutral ionic currents under differential diffusion resulted in at most a 9% correction in upscaled rates.

  3. Propensity approach to nonequilibrium thermodynamics of a chemical reaction network: Controlling single E-coli β-galactosidase enzyme catalysis through the elementary reaction steps

    Energy Technology Data Exchange (ETDEWEB)

    Das, Biswajit; Gangopadhyay, Gautam, E-mail: gautam@bose.res.in [S. N. Bose National Centre For Basic Sciences, Block-JD, Sector-III, Salt Lake, Kolkata 700 098 (India); Banerjee, Kinshuk [Department of Chemistry, University of Calcutta, 92 A.P.C. Road, Kolkata 700 009 (India)

    2013-12-28

    In this work, we develop an approach to nonequilibrium thermodynamics of an open chemical reaction network in terms of the elementary reaction propensities. The method is akin to the microscopic formulation of the dissipation function in terms of the Kullback-Leibler distance of phase space trajectories in Hamiltonian system. The formalism is applied to a single oligomeric enzyme kinetics at chemiostatic condition that leads the reaction system to a nonequilibrium steady state, characterized by a positive total entropy production rate. Analytical expressions are derived, relating the individual reaction contributions towards the total entropy production rate with experimentally measurable reaction velocity. Taking a real case of Escherichia coli β-galactosidase enzyme obeying Michaelis-Menten kinetics, we thoroughly analyze the temporal as well as the steady state behavior of various thermodynamic quantities for each elementary reaction. This gives a useful insight in the relative magnitudes of various energy terms and the dissipated heat to sustain a steady state of the reaction system operating far-from-equilibrium. It is also observed that, the reaction is entropy-driven at low substrate concentration and becomes energy-driven as the substrate concentration rises.

  4. Biomolecular Modification of Inorganic Crystal Growth

    Energy Technology Data Exchange (ETDEWEB)

    De Yoreo, J J

    2007-04-27

    The fascinating shapes and hierarchical designs of biomineralized structures are an inspiration to materials scientists because of the potential they suggest for biomolecular control over materials synthesis. Conversely, the failure to prevent or limit tissue mineralization in the vascular, skeletal, and urinary systems is a common source of disease. Understanding the mechanisms by which organisms direct or limit crystallization has long been a central challenge to the biomineralization community. One prevailing view is that mineral-associated macromolecules are responsible for either inhibiting crystallization or initiating and stabilizing non-equilibrium crystal polymorphs and morphologies through interactions between anionic moieties and cations in solution or at mineralizing surfaces. In particular, biomolecules that present carboxyl groups to the growing crystal have been implicated as primary modulators of growth. Here we review the results from a combination of in situ atomic force microscopy (AFM) and molecular modeling (MM) studies to investigate the effect of specific interactions between carboxylate-rich biomolecules and atomic steps on crystal surfaces during the growth of carbonates, oxalates and phosphates of calcium. Specifically, we how the growth kinetics and morphology depend on the concentration of additives that include citrate, simple amino acids, synthetic Asp-rich polypeptides, and naturally occurring Asp-rich proteins found in both functional and pathological mineral tissues. The results reveal a consistent picture of shape modification in which stereochemical matching of modifiers to specific atomic steps drives shape modification. Inhibition and other changes in growth kinetics are shown to be due to a range of mechanisms that depend on chemistry and molecular size. Some effects are well described by classic crystal growth theories, but others, such as step acceleration due to peptide charge and hydrophylicity, were previously unrealized

  5. Bridging Nano- and Microtribology in Mechanical and Biomolecular Layers

    Science.gov (United States)

    Tomala, Agnieszka; Göçerler, Hakan; Gebeshuber, Ille C.

    The physical and chemical composition of surfaces determine various important properties of solids such as corrosion rates, adhesive properties, frictional properties, catalytic activity, wettability, contact potential and - finally and most importantly - failure mechanisms. Very thin, weak layers (of man-made and biological origin) on much harder substrates that reduce friction are the focus of the micro- and nanotribological investigations presented in this chapter.Biomolecular layers fulfil various functions in organs of the human body. Examples comprise the skin that provides a protective physical barrier between the body and the environment, preventing unwanted inward and outward passage of water and electrolytes, reducing penetration by destructive chemicals, arresting the penetration of microorganisms and external antigens and absorbing radiation from the sun, or the epithelium of the cornea that blocks the passage of foreign material, such as dust, water and bacteria, into the eye and that contributes to the lubrication layer that ensures smooth movement of the eyelids over the eyeballs.Monomolecular thin films, additive-derived reaction layers and hard coatings are widely used to tailor tribological properties of surfaces. Nanotribological investigations on these substrates can reveal novel properties regarding the orientation of chemisorbed additive layers, development of rubbing films with time and the relation of frictional properties to surface characteristics in diamond coatings.Depending on the questions to be answered with the tribological research, various micro- and nanotribological measurement methods are applied, including scanning probe microscopy (AFM, FFM), scanning electron microscopy, microtribometer investigations, angle-resolved photoelectron spectroscopy and optical microscopy. Thoughts on the feasibility of a unified approach to energy-dissipating systems and how it might be reached (touching upon new ways of scientific publishing

  6. Trade-off between responsiveness and noise suppression in biomolecular system responses to environmental cues.

    Directory of Open Access Journals (Sweden)

    Alexander V Ratushny

    2011-06-01

    Full Text Available When living systems detect changes in their external environment their response must be measured to balance the need to react appropriately with the need to remain stable, ignoring insignificant signals. Because this is a fundamental challenge of all biological systems that execute programs in response to stimuli, we developed a generalized time-frequency analysis (TFA framework to systematically explore the dynamical properties of biomolecular networks. Using TFA, we focused on two well-characterized yeast gene regulatory networks responsive to carbon-source shifts and a mammalian innate immune regulatory network responsive to lipopolysaccharides (LPS. The networks are comprised of two different basic architectures. Dual positive and negative feedback loops make up the yeast galactose network; whereas overlapping positive and negative feed-forward loops are common to the yeast fatty-acid response network and the LPS-induced network of macrophages. TFA revealed remarkably distinct network behaviors in terms of trade-offs in responsiveness and noise suppression that are appropriately tuned to each biological response. The wild type galactose network was found to be highly responsive while the oleate network has greater noise suppression ability. The LPS network appeared more balanced, exhibiting less bias toward noise suppression or responsiveness. Exploration of the network parameter space exposed dramatic differences in system behaviors for each network. These studies highlight fundamental structural and dynamical principles that underlie each network, reveal constrained parameters of positive and negative feedback and feed-forward strengths that tune the networks appropriately for their respective biological roles, and demonstrate the general utility of the TFA approach for systems and synthetic biology.

  7. A mechanical Turing machine: blueprint for a biomolecular computer.

    Science.gov (United States)

    Shapiro, Ehud

    2012-08-01

    We describe a working mechanical device that embodies the theoretical computing machine of Alan Turing, and as such is a universal programmable computer. The device operates on three-dimensional building blocks by applying mechanical analogues of polymer elongation, cleavage and ligation, movement along a polymer, and control by molecular recognition unleashing allosteric conformational changes. Logically, the device is not more complicated than biomolecular machines of the living cell, and all its operations are part of the standard repertoire of these machines; hence, a biomolecular embodiment of the device is not infeasible. If implemented, such a biomolecular device may operate in vivo, interacting with its biochemical environment in a program-controlled manner. In particular, it may 'compute' synthetic biopolymers and release them into its environment in response to input from the environment, a capability that may have broad pharmaceutical and biological applications. PMID:22649583

  8. Biomolecular crystals for material applications and a mechanistic study of an iron oxide nanoparticle synthesis

    Science.gov (United States)

    Falkner, Joshua Charles

    The three projects within this work address the difficulties of controlling biomolecular crystal formats (i.e. size and shape), producing 3-D ordered composite materials from biomolecular crystal templates, and understanding the mechanism of a practical iron oxide synthesis. The unifying thread consistent throughout these three topics is the development of methods to manipulate nanomaterials using a bottom-up approach. Biomolecular crystals are nanometer to millimeter sized crystals that have well ordered mesoporous solvent channels. The overall physical dimensions of these crystals are highly dependent on crystallization conditions. The controlled growth of micro- and nanoprotein crystals was studied to provide new pathways for creating smaller crystalline protein materials. This method produced tetragonal hen egg-white lysozyme crystals (250--100,000 nm) with near monodisperse size distributions (membranes or templates. In this work, the porous structure of larger cowpea mosaic virus crystals was used to template metal nanoparticle growth within the body centered cubic crystalline network. The final composite material was found to have long range ordering of palladium and platinum nonocrystal aggregates (10nm) with symmetry consistent to the virus template. Nanoparticle synthesis itself is an immense field of study with an array of diverse applications. The final piece of this work investigates the mechanism behind a previously developed iron oxide synthesis to gain more understanding and direction to future synthesis strategies. The particle growth mechanism was found to proceed by the formation of a solvated iron(III)oleate complex followed by a reduction of iron (III) to iron (II). This unstable iron(II) nucleates to form a wustite (FeO) core which serves as an epitaxial surface for the magnetite (Fe3O4) shell growth. This method produces spherical particles (6-60nm) with relative size distributions of less than 15%.

  9. Evolution of Autocatalytic Sets in Computational Models of Chemical Reaction Networks

    Science.gov (United States)

    Hordijk, Wim

    2016-06-01

    Several computational models of chemical reaction networks have been presented in the literature in the past, showing the appearance and (potential) evolution of autocatalytic sets. However, the notion of autocatalytic sets has been defined differently in different modeling contexts, each one having some shortcoming or limitation. Here, we review four such models and definitions, and then formally describe and analyze them in the context of a mathematical framework for studying autocatalytic sets known as RAF theory. The main results are that: (1) RAF theory can capture the various previous definitions of autocatalytic sets and is therefore more complete and general, (2) the formal framework can be used to efficiently detect and analyze autocatalytic sets in all of these different computational models, (3) autocatalytic (RAF) sets are indeed likely to appear and evolve in such models, and (4) this could have important implications for a possible metabolism-first scenario for the origin of life.

  10. Evolution of Autocatalytic Sets in Computational Models of Chemical Reaction Networks.

    Science.gov (United States)

    Hordijk, Wim

    2016-06-01

    Several computational models of chemical reaction networks have been presented in the literature in the past, showing the appearance and (potential) evolution of autocatalytic sets. However, the notion of autocatalytic sets has been defined differently in different modeling contexts, each one having some shortcoming or limitation. Here, we review four such models and definitions, and then formally describe and analyze them in the context of a mathematical framework for studying autocatalytic sets known as RAF theory. The main results are that: (1) RAF theory can capture the various previous definitions of autocatalytic sets and is therefore more complete and general, (2) the formal framework can be used to efficiently detect and analyze autocatalytic sets in all of these different computational models, (3) autocatalytic (RAF) sets are indeed likely to appear and evolve in such models, and (4) this could have important implications for a possible metabolism-first scenario for the origin of life. PMID:26499126

  11. A model for lignin alteration - Part I: A kinetic reaction-network model

    Science.gov (United States)

    Payne, D.F.; Ortoleva, P.J.

    2001-01-01

    A new quantitative model is presented which simulates the maturation of lignin-derived sedimentary organic matter under geologic conditions. In this model, compositionally specific reactants evolve to specific intermediate and mobile products through balanced, nth order processes, by way of a network of sequential and parallel reactions. The chemical kinetic approach is based primarily on published observed structural transformations of naturally matured, lignin-derived, sedimentary organic matter. Assuming that Upper Cretaceous Williams Fork coal in the Piceance Basin is primarily lignin-derived, the model is calibrated for the Multi-Well Experiment(MWX) Site in this basin. This kind of approach may be applied to other selectively preserved chemical components of sedimentary organic matter. ?? 2001 Elsevier Science Ltd. All rights reserved.

  12. Spatially orthogonal chemical functionalization of a hierarchical pore network for catalytic cascade reactions

    Science.gov (United States)

    Parlett, Christopher M. A.; Isaacs, Mark A.; Beaumont, Simon K.; Bingham, Laura M.; Hondow, Nicole S.; Wilson, Karen; Lee, Adam F.

    2016-02-01

    The chemical functionality within porous architectures dictates their performance as heterogeneous catalysts; however, synthetic routes to control the spatial distribution of individual functions within porous solids are limited. Here we report the fabrication of spatially orthogonal bifunctional porous catalysts, through the stepwise template removal and chemical functionalization of an interconnected silica framework. Selective removal of polystyrene nanosphere templates from a lyotropic liquid crystal-templated silica sol-gel matrix, followed by extraction of the liquid crystal template, affords a hierarchical macroporous-mesoporous architecture. Decoupling of the individual template extractions allows independent functionalization of macropore and mesopore networks on the basis of chemical and/or size specificity. Spatial compartmentalization of, and directed molecular transport between, chemical functionalities affords control over the reaction sequence in catalytic cascades; herein illustrated by the Pd/Pt-catalysed oxidation of cinnamyl alcohol to cinnamic acid. We anticipate that our methodology will prompt further design of multifunctional materials comprising spatially compartmentalized functions.

  13. A moment-convergence method for stochastic analysis of biochemical reaction networks

    Science.gov (United States)

    Zhang, Jiajun; Nie, Qing; Zhou, Tianshou

    2016-05-01

    Traditional moment-closure methods need to assume that high-order cumulants of a probability distribution approximate to zero. However, this strong assumption is not satisfied for many biochemical reaction networks. Here, we introduce convergent moments (defined in mathematics as the coefficients in the Taylor expansion of the probability-generating function at some point) to overcome this drawback of the moment-closure methods. As such, we develop a new analysis method for stochastic chemical kinetics. This method provides an accurate approximation for the master probability equation (MPE). In particular, the connection between low-order convergent moments and rate constants can be more easily derived in terms of explicit and analytical forms, allowing insights that would be difficult to obtain through direct simulation or manipulation of the MPE. In addition, it provides an accurate and efficient way to compute steady-state or transient probability distribution, avoiding the algorithmic difficulty associated with stiffness of the MPE due to large differences in sizes of rate constants. Applications of the method to several systems reveal nontrivial stochastic mechanisms of gene expression dynamics, e.g., intrinsic fluctuations can induce transient bimodality and amplify transient signals, and slow switching between promoter states can increase fluctuations in spatially heterogeneous signals. The overall approach has broad applications in modeling, analysis, and computation of complex biochemical networks with intrinsic noise.

  14. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

    OpenAIRE

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2012-01-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking ...

  15. Engineering intracellular active transport systems as in vivo biomolecular tools.

    Energy Technology Data Exchange (ETDEWEB)

    Bachand, George David; Carroll-Portillo, Amanda

    2006-11-01

    Active transport systems provide essential functions in terms of cell physiology and metastasis. These systems, however, are also co-opted by invading viruses, enabling directed transport of the virus to and from the cell's nucleus (i.e., the site of virus replication). Based on this concept, fundamentally new approaches for interrogating and manipulating the inner workings of living cells may be achievable by co-opting Nature's active transport systems as an in vivo biomolecular tool. The overall goal of this project was to investigate the ability to engineer kinesin-based transport systems for in vivo applications, specifically the collection of effector proteins (e.g., transcriptional regulators) within single cells. In the first part of this project, a chimeric fusion protein consisting of kinesin and a single chain variable fragment (scFv) of an antibody was successfully produced through a recombinant expression system. The kinesin-scFv retained both catalytic and antigenic functionality, enabling selective capture and transport of target antigens. The incorporation of a rabbit IgG-specific scFv into the kinesin established a generalized system for functionalizing kinesin with a wide range of target-selective antibodies raised in rabbits. The second objective was to develop methods of isolating the intact microtubule network from live cells as a platform for evaluating kinesin-based transport within the cytoskeletal architecture of a cell. Successful isolation of intact microtubule networks from two distinct cell types was demonstrated using glutaraldehyde and methanol fixation methods. This work provides a platform for inferring the ability of kinesin-scFv to function in vivo, and may also serve as a three-dimensional scaffold for evaluating and exploiting kinesin-based transport for nanotechnological applications. Overall, the technology developed in this project represents a first-step in engineering active transport system for in vivo

  16. From dynamics to structure and function of model biomolecular systems

    NARCIS (Netherlands)

    Fontaine-Vive-Curtaz, F.

    2007-01-01

    The purpose of this thesis was to extend recent works on structure and dynamics of hydrogen bonded crystals to model biomolecular systems and biological processes. The tools that we have used are neutron scattering (NS) and density functional theory (DFT) and force field (FF) based simulation method

  17. Neutral-particle emission in collisions of electrons with biomolecular ions in an electrostatic storage ring

    International Nuclear Information System (INIS)

    Electron-biomolecular ion collisions were studied using an electrostatic storage ring with a merging electron beam device. Biomolecular ions produced by an electrospray ion source and accelerated to 20 keV/charge were injected into the ring after being mass-analyzed. The circulating ion beam was then merged with an electron beam. Neutral reaction products in collisions of electrons with ions were detected by a micro-channel plate outside of the ring. Electron-ion collisions were studied for multiply-deprotonated oligonucleotide and peptide anions as well as singly protonated oligonucleotide and peptide cations. For peptide cations, neutrals were resonantly emitted at an electron energy of around 6.5 eV, which was almost independent of the ion masses. This is deduced to come from electron-ion recombination, resulting in the cleavage of a peptide bond. For DNA oligonucleotide cations, resonant neutral particle emission was also observed. In electron and DNA anion collisions, neutrals started to increase from definite threshold energies, where the threshold energies increased in proportion to the ion charge. The same was found for peptide anions. The origin of this phenomenon is discussed

  18. Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks.

    Science.gov (United States)

    Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay

    2013-05-01

    Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three subnetworks. It turns out that our reaction classifier, which is blind to the biochemical role of pathways, leads to three functionally relevant subnetworks that correspond to input, output, and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality. PMID:23767567

  19. Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement

    Science.gov (United States)

    Srinivas, Niranjan

    Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for

  20. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space

    Science.gov (United States)

    Ruess, Jakob

    2015-12-01

    Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space.

  1. MONITORING POTENTIAL DRUG INTERACTIONS AND REACTIONS VIA NETWORK ANALYSIS OF INSTAGRAM USER TIMELINES.

    Science.gov (United States)

    Correia, Rion Brattig; Li, Lang; Rocha, Luis M

    2016-01-01

    Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this "Bibliome", the universe of social media provides a very promising source of large-scale data that can help identify DDI and ADR in ways that have not been hitherto possible. Given the large number of users, analysis of social media data may be useful to identify under-reported, population-level pathology associated with DDI, thus further contributing to improvements in population health. Moreover, tapping into this data allows us to infer drug interactions with natural products-including cannabis-which constitute an array of DDI very poorly explored by biomedical research thus far. Our goal is to determine the potential of Instagram for public health monitoring and surveillance for DDI, ADR, and behavioral pathology at large. Most social media analysis focuses on Twitter and Facebook, but Instagram is an increasingly important platform, especially among teens, with unrestricted access of public posts, high availability of posts with geolocation coordinates, and images to supplement textual analysis. Using drug, symptom, and natural product dictionaries for identification of the various types of DDI and ADR evidence, we have collected close to 7000 user timelines spanning from October 2010 to June 2015.We report on 1) the development of a monitoring tool to easily observe user-level timelines associated with drug and symptom terms of interest, and 2) population-level behavior via the analysis of co-occurrence networks computed from user timelines at three different scales: monthly, weekly, and daily occurrences. Analysis of these networks further reveals 3) drug and symptom direct and indirect associations with greater support in user timelines, as well as 4) clusters of symptoms and drugs revealed by the collective behavior of the observed population. This demonstrates that Instagram

  2. Biomolecular self-defense and futility of high-specificity therapeutic targeting.

    Science.gov (United States)

    Rosenfeld, Simon

    2011-01-01

    Robustness has been long recognized to be a distinctive property of living entities. While a reasonably wide consensus has been achieved regarding the conceptual meaning of robustness, the biomolecular mechanisms underlying this systemic property are still open to many unresolved questions. The goal of this paper is to provide an overview of existing approaches to characterization of robustness in mathematically sound terms. The concept of robustness is discussed in various contexts including network vulnerability, nonlinear dynamic stability, and self-organization. The second goal is to discuss the implications of biological robustness for individual-target therapeutics and possible strategies for outsmarting drug resistance arising from it. Special attention is paid to the concept of swarm intelligence, a well studied mechanism of self-organization in natural, societal and artificial systems. It is hypothesized that swarm intelligence is the key to understanding the emergent property of chemoresistance. PMID:22272063

  3. Advances in modeling of biomolecular interactions

    Institute of Scientific and Technical Information of China (English)

    Cong-zhongCAI; Ze-rongLI; Wan-luWANG; Yu-zongCHEN

    2004-01-01

    Modeling of molecular interactions is increasingly used in life science research and biotechnology development.Examples are computer aided drug design, prediction of protein interactions with other molecules, and simulation of networks of biomolecules in a particular process in human body. This article reviews recent progress in the related fields and provides a brief overview on the methods used in molecular modeling of biological systems.

  4. Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks

    KAUST Repository

    Ben Hammouda, Chiheb

    2015-05-12

    In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for

  5. LiHe{sup +} IN THE EARLY UNIVERSE: A FULL ASSESSMENT OF ITS REACTION NETWORK AND FINAL ABUNDANCES

    Energy Technology Data Exchange (ETDEWEB)

    Bovino, Stefano; Tacconi, Mario; Gianturco, Francesco A. [Department of Chemistry, Universita degli Studi di Roma ' La Sapienza' , Piazzale A. Moro 5, 00185 Roma (Italy); Curik, Roman [J. Heyrovsky Institute of Physical Chemistry, Dolejskova 3, Prague (Czech Republic); Galli, Daniele, E-mail: fa.gianturco@caspur.it [INAF-Osservatorio Astrofisico di Arcetri, Largo E. Fermi 5, 50125 Firenze (Italy)

    2012-06-10

    We present the results of quantum calculations based on entirely ab initio methods for a variety of molecular processes and chemical reactions involving the LiHe{sup +} ionic polar molecule. With the aid of these calculations, we derive accurate reaction rates and fitting expressions valid over a range of gas temperatures representative of the typical conditions of the pregalactic gas. With the help of a full chemical network, we then compute the evolution of the abundance of LiHe{sup +} as function of redshift in the early universe. Finally, we compare the relative abundance of LiHe{sup +} with that of other polar cations formed in the same redshift interval.

  6. Thermodynamic Integration Networks and Their Application to Charge Transfer Reactions within the AauDyPI Fungal Peroxidase.

    Science.gov (United States)

    Bauß, Anna; Langenmaier, Michael; Strittmatter, Eric; Plattner, Dietmar A; Koslowski, Thorsten

    2016-06-01

    We present a computer simulation study of the thermodynamics and kinetics of charge transfer reactions within the fungal peroxidase AauDyPI from Auricularia auriculae-judae. Driving forces and reorganization energies are obtained from a thermodynamic integration scheme based upon molecular dynamics simulations. To enhance the numerical accuracy, the free energies are analyzed within a least-squares scheme of a closely knit thermodynamic network. We identify Tyr147, Tyr229, and Trp105 as oxidative agents, and find Trp377 to be a long-lived reaction intermediate. The results are compared to recent experimental findings. PMID:27182684

  7. Physics at the biomolecular interface fundamentals for molecular targeted therapy

    CERN Document Server

    Fernández, Ariel

    2016-01-01

    This book focuses primarily on the role of interfacial forces in understanding biological phenomena at the molecular scale. By providing a suitable statistical mechanical apparatus to handle the biomolecular interface, the book becomes uniquely positioned to address core problems in molecular biophysics. It highlights the importance of interfacial tension in delineating a solution to the protein folding problem, in unravelling the physico-chemical basis of enzyme catalysis and protein associations, and in rationally designing molecular targeted therapies. Thus grounded in fundamental science, the book develops a powerful technological platform for drug discovery, while it is set to inspire scientists at any level in their careers determined to address the major challenges in molecular biophysics. The acknowledgment of how exquisitely the structure and dynamics of proteins and their aqueous environment are related attests to the overdue recognition that biomolecular phenomena cannot be effectively understood w...

  8. Biomolecular structure refinement using the GROMOS simulation software

    Energy Technology Data Exchange (ETDEWEB)

    Schmid, Nathan; Allison, Jane R.; Dolenc, Jozica; Eichenberger, Andreas P.; Kunz, Anna-Pitschna E.; Gunsteren, Wilfred F. van, E-mail: wfvgn@igc.phys.chem.ethz.ch [Swiss Federal Institute of Technology ETH, Laboratory of Physical Chemistry (Switzerland)

    2011-11-15

    For the understanding of cellular processes the molecular structure of biomolecules has to be accurately determined. Initial models can be significantly improved by structure refinement techniques. Here, we present the refinement methods and analysis techniques implemented in the GROMOS software for biomolecular simulation. The methodology and some implementation details of the computation of NMR NOE data, {sup 3}J-couplings and residual dipolar couplings, X-ray scattering intensities from crystals and solutions and neutron scattering intensities used in GROMOS is described and refinement strategies and concepts are discussed using example applications. The GROMOS software allows structure refinement combining different types of experimental data with different types of restraining functions, while using a variety of methods to enhance conformational searching and sampling and the thermodynamically calibrated GROMOS force field for biomolecular simulation.

  9. Graph-theoretical identification of dissociation pathways on free energy landscapes of biomolecular interaction.

    Science.gov (United States)

    Wang, Ling; Stumm, Boris; Helms, Volkhard

    2010-03-01

    Biomolecular association and dissociation reactions take place on complicated interaction free energy landscapes that are still very hard to characterize computationally. For large enough distances, though, it often suffices to consider the six relative translational and rotational degrees of freedom of the two particles treated as rigid bodies. Here, we computed the six-dimensional free energy surface of a dimer of water-soluble alpha-helices by scanning these six degrees of freedom in about one million grid points. In each point, the relative free energy difference was computed as the sum of the polar and nonpolar solvation free energies of the helix dimer and of the intermolecular coulombic interaction energy. The Dijkstra graph algorithm was then applied to search for the lowest cost dissociation pathways based on a weighted, directed graph, where the vertices represent the grid points, the edges connect the grid points and their neighbors, and the weights are the reaction costs between adjacent pairs of grid points. As an example, the configuration of the bound state was chosen as the source node, and the eight corners of the translational cube were chosen as the destination nodes. With the strong electrostatic interaction of the two helices giving rise to a clearly funnel-shaped energy landscape, the eight lowest-energy cost pathways coming from different orientations converge into a well-defined pathway for association. We believe that the methodology presented here will prove useful for identifying low-energy association and dissociation pathways in future studies of complicated free energy landscapes for biomolecular interaction. PMID:19603501

  10. Quantifying Modularity in the Evolution of Biomolecular Systems

    OpenAIRE

    2004-01-01

    Functional modules are considered the primary building blocks of biomolecular systems. Here we study to what extent functional modules behave cohesively across genomes:That is, are functional modules also evolutionary modules? We probe this question by analyzing for a large collection of functional modules the phyletic patterns of their genes across 110 genomes. The majority of functional modules display limited evolutionary modularity. This result confirms certain comparative genome analyses...

  11. The biomolecular and ultrastructural basis of epidermolysis bullosa:

    OpenAIRE

    Ciolan, Maria; Olariu, Liviu; Solovan, Caius

    2005-01-01

    Transmission electron microscopy, immunoelectron microscopy, immunofluorescence and antigenic mapping have improved our understanding of the dermo-epidermal junction. We have reviewed some ultrastructural and biomolecular aspects related to the dermo-epidermal junction. In part, they are implicated in the pathogenesis of a group of hereditary disorders characterized by skin fragility, collectively known as epidermolysis bullosa (EB). These disorders could benefit in the near future from a gen...

  12. Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor (IRIS)

    OpenAIRE

    Carlos A Lopez; George G Daaboul; Ahn, Sunmin; Reddington, Alexander P.; Monroe, Margo R.; Zhang, Xirui; Irani, Rostem J.; Yu, Chunxiao; Genco, Caroline A.; Cretich, Marina; Chiari, Marcella; Goldberg, Bennett B.; Connor, John H.; Ünlü, M. Selim

    2011-01-01

    The sensitive measurement of biomolecular interactions has use in many fields and industries such as basic biology and microbiology, environmental/agricultural/biodefense monitoring, nanobiotechnology, and more. For diagnostic applications, monitoring (detecting) the presence, absence, or abnormal expression of targeted proteomic or genomic biomarkers found in patient samples can be used to determine treatment approaches or therapy efficacy. In the research arena, information on molecular aff...

  13. A mechanical Turing machine: blueprint for a biomolecular computer

    OpenAIRE

    Shapiro, Ehud

    2012-01-01

    We describe a working mechanical device that embodies the theoretical computing machine of Alan Turing, and as such is a universal programmable computer. The device operates on three-dimensional building blocks by applying mechanical analogues of polymer elongation, cleavage and ligation, movement along a polymer, and control by molecular recognition unleashing allosteric conformational changes. Logically, the device is not more complicated than biomolecular machines of the living cell, and a...

  14. Dynamic Presentation of Immobilized Ligands Regulated through Biomolecular Recognition

    OpenAIRE

    Liu, Bo; Liu, Yang; Riesberg, Jeremiah J.; Shen, Wei

    2010-01-01

    To mimic the dynamic regulation of signaling ligands immobilized on extracellular matrices or on the surfaces of neighboring cells for guidance of cell behavior and fate selection, we have harnessed biomolecular recognition in combination with polymer engineering to create dynamic surfaces on which the accessibility of immobilized ligands to cell surface receptors can be reversibly interconverted under physiological conditions. The cell-adhesive RGD peptide is chosen as a model ligand. RGD is...

  15. Descriptions of surface chemical reactions using a neural network representation of the potential-energy surface

    Science.gov (United States)

    Lorenz, Sönke; Scheffler, Matthias; Gross, Axel

    2006-03-01

    A neural network (NN) approach is proposed for the representation of six-dimensional ab initio potential-energy surfaces (PES) for the dissociation of a diatomic molecule at surfaces. We report tests of NN representations that are fitted to six-dimensional analytical PESs for H2 dissociation on the clean and the sulfur covered Pd(100) surfaces. For the present study we use high-dimensional analytical PESs as the basis for the NN training, as this enables us to investigate the influence of phase space sampling on adsorption rates in great detail. We note, however, that these analytical PESs were obtained from detailed density functional theory calculations. When information about the PES is collected only from a few high-symmetric adsorption sites, we find that the obtained adsorption probabilities are not reliable. Thus, intermediate configurations need to be considered as well. However, it is not necessary to map out complete elbow plots above nonsymmetric sites. Our study suggests that only a few additional energies need to be considered in the region of activated systems where the molecular bond breaks. With this understanding, the required number of NN training energies for obtaining a high-quality PES that provides a reliable description of the dissociation and adsorption dynamics is orders of magnitude smaller than the number of total-energy calculations needed in traditional ab initio on the fly molecular dynamics. Our analysis also demonstrates the importance of a reliable, high-dimensional PES to describe reaction rates for dissociative adsorption of molecules at surfaces.

  16. Interfacial reaction of silver ultra-thin film deposited on interpenetrating polymer network substrate by liquor-phase reduction

    International Nuclear Information System (INIS)

    The interfacial reaction, metal transformations, and nonmetal bond types of silver ultra-thin film deposited on polyurethane (PU) based interpenetrating polymer networks (IPN) substrate by the liquor-phase reduction at room temperatures were studied by atomic force microscope (AFM), X-ray photoelectron spectroscopy (XPS) and attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR). The IPN substrate was prepared by dip-pulling precursors onto a silicon wafer or a glass plate, followed by solidification at room temperature. The interpenetrate structures of IPN with two crosslinked networks restricted the aggregation of silver during the reduction and deposition. The devised -OH terminal group in PU simplified the determination of reactive site in IPN and reinforced the adhesion between IPN and silver through interfacial reaction. The XPS results, which matched well with the ATR-FTIR results, verified the chemical reactive site of PU in IPN with silver in the oxide state.

  17. Interfacial reaction of silver ultra-thin film deposited on interpenetrating polymer network substrate by liquor-phase reduction

    Energy Technology Data Exchange (ETDEWEB)

    Tang Dongyan, E-mail: dytang@hit.edu.cn [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China); Guo Yudi [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China); Zhang Xiaohong [College of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150001 (China); Yin Yuelong [Department of Chemistry, School of Science, Harbin Institute of Technology, Harbin 150001 (China)

    2010-08-01

    The interfacial reaction, metal transformations, and nonmetal bond types of silver ultra-thin film deposited on polyurethane (PU) based interpenetrating polymer networks (IPN) substrate by the liquor-phase reduction at room temperatures were studied by atomic force microscope (AFM), X-ray photoelectron spectroscopy (XPS) and attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR). The IPN substrate was prepared by dip-pulling precursors onto a silicon wafer or a glass plate, followed by solidification at room temperature. The interpenetrate structures of IPN with two crosslinked networks restricted the aggregation of silver during the reduction and deposition. The devised -OH terminal group in PU simplified the determination of reactive site in IPN and reinforced the adhesion between IPN and silver through interfacial reaction. The XPS results, which matched well with the ATR-FTIR results, verified the chemical reactive site of PU in IPN with silver in the oxide state.

  18. States with identical steady dissipation rate in reaction networks: A non-equilibrium thermodynamic insight in enzyme efficiency

    International Nuclear Information System (INIS)

    Highlights: • States with identical steady dissipation rate are distinguished. • Variation of the entropy production rate with the reaction rate is studied. • Enzyme catalysis under chemiostatic condition is taken as an exactly-solvable test case. • A connection between the total entropy production with the enzyme efficiency is established. • The treatment is generalized to a more complex kinetic network. - Abstract: A non-equilibrium steady state is characterized by a non-zero steady dissipation rate. Chemical reaction systems under suitable conditions may generate such states. We propose here a method that is able to distinguish states with identical values of the steady dissipation rate. This necessitates a study of the variation of the entropy production rate with the experimentally observable reaction rate in regions close to the steady states. As an exactly-solvable test case, we choose the problem of enzyme catalysis. Link of the total entropy production with the enzyme efficiency is also established, offering a desirable connection with the inherent irreversibility of the process. The chief outcomes are finally noted in a more general reaction network with numerical demonstrations

  19. Theoretical models for the emergence of biomolecular homochirality

    Science.gov (United States)

    Walker, Sara Imari

    Little is known about the emergence of life from nonliving precursors. A key missing-piece is the origin of homochirality: nearly all life is characterized by exclusively dextrorotary sugars and levorotary amino acids. The research presented in this thesis addresses the challenge of uncovering mechanisms for chiral symmetry breaking in a prebiotic environment and implications for the origin of life on Earth. Expanding on a well-known model for chiral selection through polymerization, and modeling the spatiotemporal dynamics starting from near-racemic initial conditions, it is demonstrated that the net chirality of molecular building blocks grows with the longest polymer in the reaction network (of length N) with critical behavior for the onset of chiral asymmetry determined by the value of N. This surprising result indicates that significant chiral asymmetry occurs only for systems which permit growth of long polymers. Expanding on this work, the effects of environmental disturbances on the evolution of chirality in prebiotic reaction-diffusion networks are studied via the implementation of a stochastic spatiotemporal Langevin equation. The results show that environmental interactions can have significant impact on the evolution of prebiotic chirality: the history of prebiotic chirality is therefore interwoven with the Earths early environmental history in a mechanism we call punctuated chirality. This result establishes that the onset of homochirality is not an isolated phenomenon: chiral selection must occur in tandem with the transition from chemistry to biology, otherwise the prebiotic soup is unstable to environmental events. Addressing the challenge of understanding the role of chirality in the transition from non-life to life, the diffusive slowdown of reaction networks induced, for example, through tidal cycles or evaporating pools, is modeled. The results of this study demonstrate that such diffusive slowdown leads to the stabilization of homochiral

  20. Resonance Reaction in Diffusion-Influenced Bimolecular Reactions

    CERN Document Server

    Kolb, Jakob J; Dzubiella, Joachim

    2016-01-01

    We investigate the influence of a stochastically fluctuating step-barrier potential on bimolecular reaction rates by exact analytical theory and stochastic simulations. We demonstrate that the system exhibits a new resonant reaction behavior with rate enhancement if an appropriately defined fluctuation decay length is of the order of the system size. Importantly, we find that in the proximity of resonance the standard reciprocal additivity law for diffusion and surface reaction rates is violated due to the dynamical coupling of multiple kinetic processes. Together, these findings may have important repercussions on the correct interpretation of various kinetic reaction problems in complex systems, as, e.g., in biomolecular association or catalysis.

  1. Communication: Resonance reaction in diffusion-influenced bimolecular reactions

    Science.gov (United States)

    Kolb, Jakob J.; Angioletti-Uberti, Stefano; Dzubiella, Joachim

    2016-02-01

    We investigate the influence of a stochastically fluctuating step-barrier potential on bimolecular reaction rates by exact analytical theory and stochastic simulations. We demonstrate that the system exhibits a new "resonant reaction" behavior with rate enhancement if an appropriately defined fluctuation decay length is of the order of the system size. Importantly, we find that in the proximity of resonance, the standard reciprocal additivity law for diffusion and surface reaction rates is violated due to the dynamical coupling of multiple kinetic processes. Together, these findings may have important repercussions on the correct interpretation of various kinetic reaction problems in complex systems, as, e.g., in biomolecular association or catalysis.

  2. Scanning probe and optical tweezer investigations of biomolecular interactions

    Energy Technology Data Exchange (ETDEWEB)

    Rigby-Singleton, Shellie

    2002-07-01

    A complex array of intermolecular forces controls the interactions between and within biological molecules. The desire to empirically explore the fundamental forces has led to the development of several biophysical techniques. Of these, the atomic force microscope (AFM) and the optical tweezers have been employed throughout this thesis to monitor the intermolecular forces involved in biomolecular interactions. The AFM is a well-established force sensing technique capable of measuring biomolecular interactions at a single molecule level. However, its versatility has not been extrapolated to the investigation of a drug-enzyme complex. The energy landscape for the force induced dissociation of the DHFR-methotrexate complex was studied. Revealing an energy barrier to dissociation located {approx}0.3 nm from the bound state. Unfortunately, the AFM has a limited range of accessible loading rates and in order to profile the complete energy landscape alternative force sensing instrumentation should be considered, for example the BFP and optical tweezers. Thus, this thesis outlines the development and construction an optical trap capable of measuring intermolecular forces between biomolecules at the single molecule level. To demonstrate the force sensing abilities of the optical set up, proof of principle measurements were performed which investigate the interactions between proteins and polymer surfaces subjected to varying degrees of argon plasma treatment. Complementary data was gained from measurements performed independently by the AFM. Changes in polymer resistance to proteins as a response to changes in polymer surface chemistry were detected utilising both AFM and optical tweezers measurements. Finally, the AFM and optical tweezers were employed as ultrasensitive biosensors. Single molecule investigations of the antibody-antigen interaction between the cardiac troponin I marker and its complementary antibody, reveals the impact therapeutic concentrations of heparin

  3. Averaging methods for stochastic dynamics of complex reaction networks: description of multi-scale couplings

    CERN Document Server

    Plyasunov, S

    2005-01-01

    This paper is concerned with classes of models of stochastic reaction dynamics with time-scales separation. We demonstrate that the existence of the time-scale separation naturally leads to the application of the averaging principle and elimination of degrees of freedom via the renormalization of transition rates of slow reactions. The method suggested in this work is more general than other approaches presented previously: it is not limited to a particular type of stochastic processes and can be applied to different types of processes describing fast dynamics, and also provides crossover to the case when separation of time scales is not well pronounced. We derive a family of exact fluctuation-dissipation relations which establish the connection between effective rates and the statistics of the reaction events in fast reaction channels. An illustration of the technique is provided. Examples show that renormalized transition rates exhibit in general non-exponential relaxation behavior with a broad range of pos...

  4. Delay-induced Turing-like waves for one-species reaction-diffusion model on a network

    Science.gov (United States)

    Petit, Julien; Carletti, Timoteo; Asllani, Malbor; Fanelli, Duccio

    2015-09-01

    A one-species time-delay reaction-diffusion system defined on a complex network is studied. Traveling waves are predicted to occur following a symmetry-breaking instability of a homogeneous stationary stable solution, subject to an external nonhomogeneous perturbation. These are generalized Turing-like waves that materialize in a single-species populations dynamics model, as the unexpected byproduct of the imposed delay in the diffusion part. Sufficient conditions for the onset of the instability are mathematically provided by performing a linear stability analysis adapted to time-delayed differential equations. The method here developed exploits the properties of the Lambert W-function. The prediction of the theory are confirmed by direct numerical simulation carried out for a modified version of the classical Fisher model, defined on a Watts-Strogatz network and with the inclusion of the delay.

  5. Report on the IAEA technical meeting on co-ordination of the network of nuclear reaction data centres

    International Nuclear Information System (INIS)

    Results of the IAEA Technical Meeting on the Co-ordination of the Network of Nuclear Reaction Data Centres held at the IAEA Headquarters, Vienna, Austria, 17 to 19 June 2003, are summarised in this report. The meeting was attended by 14 participants from 9 cooperating data centres of five member states and two International Organizations. A meeting summary, the conclusions and actions, progress and status reports of the participating data centres, and working papers considered at the meeting, are given in the relevant sections. (author)

  6. Sign conditions for injectivity of generalized polynomial maps with applications to chemical reaction networks and real algebraic geometry

    DEFF Research Database (Denmark)

    Müller, Stefan; Feliu, Elisenda; Regensburger, Georg;

    2016-01-01

    We give necessary and sufficient conditions in terms of sign vectors for the injectivity of families of polynomials maps with arbitrary real exponents defined on the positive orthant. Our work relates and extends existing injectivity conditions expressed in terms of Jacobian matrices and determin...... determinants. In the context of chemical reaction networks with power-law kinetics, our results can be used to preclude as well as to guarantee multiple positive steady states. In the context of real algebraic geometry, our results reveal the first ...

  7. MPBEC, a Matlab Program for Biomolecular Electrostatic Calculations

    Science.gov (United States)

    Vergara-Perez, Sandra; Marucho, Marcelo

    2016-01-01

    One of the most used and efficient approaches to compute electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation. There are several software packages available that solve the PB equation for molecules in aqueous electrolyte solutions. Most of these software packages are useful for scientists with specialized training and expertise in computational biophysics. However, the user is usually required to manually take several important choices, depending on the complexity of the biological system, to successfully obtain the numerical solution of the PB equation. This may become an obstacle for researchers, experimentalists, even students with no special training in computational methodologies. Aiming to overcome this limitation, in this article we present MPBEC, a free, cross-platform, open-source software that provides non-experts in the field an easy and efficient way to perform biomolecular electrostatic calculations on single processor computers. MPBEC is a Matlab script based on the Adaptative Poisson-Boltzmann Solver, one of the most popular approaches used to solve the PB equation. MPBEC does not require any user programming, text editing or extensive statistical skills, and comes with detailed user-guide documentation. As a unique feature, MPBEC includes a useful graphical user interface (GUI) application which helps and guides users to configure and setup the optimal parameters and approximations to successfully perform the required biomolecular electrostatic calculations. The GUI also incorporates visualization tools to facilitate users pre- and post-analysis of structural and electrical properties of biomolecules.

  8. Biomolecular interaction analysis for carbon nanotubes and for biocompatibility prediction.

    Science.gov (United States)

    Chen, Xiaoping; Fang, Jinzhang; Cheng, Yun; Zheng, Jianhui; Zhang, Jingjing; Chen, Tao; Ruan, Benfang Helen

    2016-07-15

    The interactions between carbon nanotubes (CNTs) and biologics have been commonly studied by various microscopy and spectroscopy methods. We tried biomolecular interaction analysis to measure the kinetic interactions between proteins and CNTs. The analysis demonstrated that wheat germ agglutinin (WGA) and other proteins have high affinity toward carboxylated CNT (f-MWCNT) but essentially no binding to normal CNT (p-MWCNT). The binding of f-MWCNT-protein showed dose dependence, and the observed kinetic constants were in the range of 10(-9) to 10(-11) M with very small off-rates (10(-3) to 10(-7) s(-1)), indicating a relatively tight and stable f-MWCNT-protein complex formation. Interestingly in hemolysis assay, p-MWCNT showed good biocompatibility, f-MWCNT caused 30% hemolysis, but WGA-coated f-MWCNT did not show hemolysis. Furthermore, the f-MWCNT-WGA complex demonstrated enhanced cytotoxicity toward cancer cells, perhaps through the glycoproteins expressed on the cells' surface. Taken together, biomolecular interaction analysis is a precise method that might be useful in evaluating the binding affinity of biologics to CNTs and in predicting biological actions. PMID:27108187

  9. Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks

    Czech Academy of Sciences Publication Activity Database

    Liao, S.; Vejchodský, Tomáš; Erban, R.

    2015-01-01

    Roč. 12, č. 108 (2015), s. 20150233. ISSN 1742-5689 EU Projects: European Commission(XE) 328008 - STOCHDETBIOMODEL Institutional support : RVO:67985840 Keywords : gene regulatory networks * stochastic modelling * parametric analysis Subject RIV: BA - General Mathematics Impact factor: 3.917, year: 2014 http://rsif.royalsocietypublishing.org/ content /12/108/20150233

  10. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    International Nuclear Information System (INIS)

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules

  11. Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks

    Czech Academy of Sciences Publication Activity Database

    Liao, S.; Vejchodský, Tomáš; Erban, R.

    2015-01-01

    Roč. 12, č. 108 (2015), s. 20150233. ISSN 1742-5689 EU Projects: European Commission(XE) 328008 - STOCHDETBIOMODEL Institutional support: RVO:67985840 Keywords : gene regulatory networks * stochastic modelling * parametric analysis Subject RIV: BA - General Mathematics Impact factor: 3.917, year: 2014 http://rsif.royalsocietypublishing.org/content/12/108/20150233

  12. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    Science.gov (United States)

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M.

    2016-01-01

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.

  13. Confinement and diffusion modulate bistability and stochastic switching in a reaction network with positive feedback

    Energy Technology Data Exchange (ETDEWEB)

    Mlynarczyk, Paul J.; Pullen, Robert H.; Abel, Steven M., E-mail: abel@utk.edu [Department of Chemical and Biomolecular Engineering, University of Tennessee, Knoxville, Tennessee 37996 (United States)

    2016-01-07

    Positive feedback is a common feature in signal transduction networks and can lead to phenomena such as bistability and signal propagation by domain growth. Physical features of the cellular environment, such as spatial confinement and the mobility of proteins, play important but inadequately understood roles in shaping the behavior of signaling networks. Here, we use stochastic, spatially resolved kinetic Monte Carlo simulations to explore a positive feedback network as a function of system size, system shape, and mobility of molecules. We show that these physical properties can markedly alter characteristics of bistability and stochastic switching when compared with well-mixed simulations. Notably, systems of equal volume but different shapes can exhibit qualitatively different behaviors under otherwise identical conditions. We show that stochastic switching to a state maintained by positive feedback occurs by cluster formation and growth. Additionally, the frequency at which switching occurs depends nontrivially on the diffusion coefficient, which can promote or suppress switching relative to the well-mixed limit. Taken together, the results provide a framework for understanding how confinement and protein mobility influence emergent features of the positive feedback network by modulating molecular concentrations, diffusion-influenced rate parameters, and spatiotemporal correlations between molecules.

  14. Pushing back the frontiers of mercury speciation using a combination of biomolecular and isotopic signatures: challenge and perspectives.

    Science.gov (United States)

    Pedrero, Zoyne; Donard, Olivier F X; Amouroux, David

    2016-04-01

    Mercury (Hg) pollution is considered a major environmental problem due to the extreme toxicity of Hg. However, Hg metabolic pathways in biota remain elusive. An understanding of these pathways is crucial to elucidating the (eco)toxic effects of Hg and its biogeochemical cycle. The development of a new analytical methodology based on both speciation and natural isotopic fractionation represents a promising approach for metabolic studies of Hg and other metal(loid)s. Speciation provides valuable information about the reactivity and potential toxicity of metabolites, while the use of natural isotopic signature analysis adds a complementary dynamic dimension that allows the life history of the target element to be probed, the source of the target element (i.e., the source of pollution) to be identified, and reactions to be tracked. The resulting combined (bio)molecular and isotopic signature affords precious insight into the behavior of Hg in biota and Hg detoxification mechanisms. In the long term, this highly innovative methodology could be used in life and environmental science studies of metal(loid)s to push back the frontiers of our knowledge in this field. This paper summarizes the current status of the application of Hg speciation and the isotopic signature of Hg at the biomolecular level in living organisms, and discusses potential future uses of this combination of techniques. Graphical Abstract Application of Hg speciation and the isotopic signature of Hg to enhance our understanding of the roles of Hg in metabolic, toxicological, and environmental processes. PMID:26753975

  15. Automatic reaction to a chemical event detected by a low-cost wireless chemical sensing network

    OpenAIRE

    Beirne, Stephen; Lau, King-Tong; Corcoran, Brian; Diamond, Dermot

    2009-01-01

    A test-scale wireless chemical sensor network (WCSN) has been deployed within a controlled Environmental Chamber (EC). The combined signals from the WCSN were used to initiate a controllable response to the detected chemical event. When a particular sensor response pattern was obtained, a purging cycle was initiated. Sensor data were continuously checked against user-defined action limits, to determine if a chemical event had occurred. An acidic contaminant was used to demonstrate the respons...

  16. Gait Phases Recognition from Accelerations and Ground Reaction Forces: Application of Neural Networks

    Directory of Open Access Journals (Sweden)

    S. Rafajlović

    2009-06-01

    Full Text Available The goal of this study was to test the applicability of accelerometer as the sensor for assessment of the walking. We present here the comparison of gait phases detected from the data recorded by force sensing resistors mounted in the shoe insoles, non-processed acceleration and processed acceleration perpendicular to the direction of the foot. The gait phases in all three cases were detected by means of a neural network. The output from the neural network was the gait phase, while the inputs were data from the sensors. The results show that the errors were in the ranges: 30 ms (2.7% – force sensors; 150 ms (13.6% – nonprocessed acceleration, and 120 ms (11% – processed acceleration data. This result suggests that it is possible to use the accelerometer as the gait phase detector, however, with the knowledge that the gait phases are time shifted for about 100 ms with respect the neural network predicted times.

  17. Stochastic innovation as a mechanism by which catalysts might self-assemble into chemical reaction networks

    OpenAIRE

    Bradford, Justin A; Dill, Ken A.

    2007-01-01

    We develop a computer model for how two different chemical catalysts in solution, A and B, could be driven to form AB complexes, based on the concentration gradients of a substrate or product that they share in common. If A's product is B's substrate, B will be attracted to A, mediated by a common resource that is not otherwise plentiful in the environment. By this simple physicochemical mechanism, chemical reactions could spontaneously associate to become chained together in solution. Accord...

  18. Stochastic focusing coupled with negative feedback enables robust regulation in biochemical reaction networks.

    Science.gov (United States)

    Milias-Argeitis, Andreas; Engblom, Stefan; Bauer, Pavol; Khammash, Mustafa

    2015-12-01

    Nature presents multiple intriguing examples of processes that proceed with high precision and regularity. This remarkable stability is frequently counter to modellers' experience with the inherent stochasticity of chemical reactions in the regime of low-copy numbers. Moreover, the effects of noise and nonlinearities can lead to 'counterintuitive' behaviour, as demonstrated for a basic enzymatic reaction scheme that can display stochastic focusing (SF). Under the assumption of rapid signal fluctuations, SF has been shown to convert a graded response into a threshold mechanism, thus attenuating the detrimental effects of signal noise. However, when the rapid fluctuation assumption is violated, this gain in sensitivity is generally obtained at the cost of very large product variance, and this unpredictable behaviour may be one possible explanation of why, more than a decade after its introduction, SF has still not been observed in real biochemical systems. In this work, we explore the noise properties of a simple enzymatic reaction mechanism with a small and fluctuating number of active enzymes that behaves as a high-gain, noisy amplifier due to SF caused by slow enzyme fluctuations. We then show that the inclusion of a plausible negative feedback mechanism turns the system from a noisy signal detector to a strong homeostatic mechanism by exchanging high gain with strong attenuation in output noise and robustness to parameter variations. Moreover, we observe that the discrepancy between deterministic and stochastic descriptions of stochastically focused systems in the evolution of the means almost completely disappears, despite very low molecule counts and the additional nonlinearity due to feedback. The reaction mechanism considered here can provide a possible resolution to the apparent conflict between intrinsic noise and high precision in critical intracellular processes. PMID:26609065

  19. Reproduction of a Protocell by Replication of Minority Molecule in Catalytic Reaction Network

    OpenAIRE

    Kamimura, Atsushi; Kaneko, Kunihiko

    2010-01-01

    For understanding the origin of life, it is essential to explain the development of a compartmentalized structure, which undergoes growth and division, from a set of chemical reactions. In this study, a hypercycle with two chemicals that mutually catalyze each other is considered in order to show that the reproduction of a protocell with a growth-division process naturally occurs when the replication speed of one chemical is considerably slower than that of the other chemical. It is observed ...

  20. Compartmentalization and Cell Division through Molecular Discreteness and Crowding in a Catalytic Reaction Network

    OpenAIRE

    Atsushi Kamimura; Kunihiko Kaneko

    2014-01-01

    Explanation of the emergence of primitive cellular structures from a set of chemical reactions is necessary to unveil the origin of life and to experimentally synthesize protocells. By simulating a cellular automaton model with a two-species hypercycle, we demonstrate the reproduction of a localized cluster; that is, a protocell with a growth-division process emerges when the replication and degradation speeds of one species are respectively slower than those of the other species, because of ...

  1. Effect of gel network on pattern formation in the ferrocyanide-iodate-sulfite reaction.

    Science.gov (United States)

    Ueno, Tomonaga; Yoshida, Ryo

    2011-06-01

    Stationary patterns have been researched experimentally since the discovery of the Turing pattern in the chlorite-iodide-malonic acid (CIMA) reaction and the self-replicating spot pattern in the ferrocyanide-iodate-sulfite (FIS) reaction. In this study, we reproduced the pattern formation in the FIS reaction by using poly(acrylamide) gels. Gels with different swelling ratios were prepared to use as a medium. The effect of the swelling ratio was compared with the effect of thickness. It was found that the swelling ratio greatly influenced pattern formation. Oscillating spot patterns appeared at high swelling ratios, and lamellar patterns appeared at a low swelling ratio. Self-replicating spot patterns appeared in between the two areas. The front velocities, which were observed in the initial stage of pattern formation, depended on the swelling ratio. Furthermore, this dependence obeys the free volume theory of diffusion. These results provide evidence that the change in front velocities is caused by a change in diffusion. Pattern formation can be controlled not only by thickness but also by swelling ratio, which may be useful for creating novel pattern templates. PMID:21557556

  2. Simulation of Parallel Logical Operations with Biomolecular Computing

    Directory of Open Access Journals (Sweden)

    Mahnaz Kadkhoda

    2008-01-01

    Full Text Available Biomolecular computing is the computational method that uses the potential of DNA as a parallel computing device. DNA computing can be used to solve NP-complete problems. An appropriate application of DNA computation is large-scale evaluation of parallel computation models such as Boolean Circuits. In this study, we present a molecular-based algorithm for evaluation of Nand-based Boolean Circuits. The contribution of this paper is that the proposed algorithm has been implemented using only three molecular operations and the number of passes in each level is decreased to less than half of previously addressed in the literature. Thus, the proposed algorithm is much easier to implement in the laboratory.

  3. Perspective: Markov models for long-timescale biomolecular dynamics

    International Nuclear Information System (INIS)

    Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics

  4. Computational and theoretical aspects of biomolecular structure and dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Garcia, A.E.; Berendzen, J.; Catasti, P., Chen, X. [and others

    1996-09-01

    This is the final report for a project that sought to evaluate and develop theoretical, and computational bases for designing, performing, and analyzing experimental studies in structural biology. Simulations of large biomolecular systems in solution, hydrophobic interactions, and quantum chemical calculations for large systems have been performed. We have developed a code that implements the Fast Multipole Algorithm (FMA) that scales linearly in the number of particles simulated in a large system. New methods have been developed for the analysis of multidimensional NMR data in order to obtain high resolution atomic structures. These methods have been applied to the study of DNA sequences in the human centromere, sequences linked to genetic diseases, and the dynamics and structure of myoglobin.

  5. Nanopatterned structures for biomolecular analysis toward genomic and proteomic applications

    Science.gov (United States)

    Chou, Chia-Fu; Gu, Jian; Wei, Qihuo; Liu, Yingjie; Gupta, Ravi; Nishio, Takeyoshi; Zenhausern, Frederic

    2005-01-01

    We report our fabrication of nanoscale devices using electron beam and nanoimprint lithography (NIL). We focus our study in the emerging fields of NIL, nanophotonics and nanobiotechnology and give a few examples as to how these nanodevices may be applied toward genomic and proteomic applications for molecular analysis. The examples include reverse NIL-fabricated nanofluidic channels for DNA stretching, nanoscale molecular traps constructed from dielectric constrictions for DNA or protein focusing by dielectrophoresis, multi-layer nanoburger and nanoburger multiplets for optimized surface-plasma enhanced Raman scattering for protein detection, and biomolecular motor-based nanosystems. The development of advanced nanopatterning techniques promises reliable and high-throughput manufacturing of nanodevices which could impact significantly on the areas of genomics, proteomics, drug discovery and molecular clinical diagnostics.

  6. Perspective: Markov Models for Long-Timescale Biomolecular Dynamics

    CERN Document Server

    Schwantes, Christian R; Pande, Vijay S

    2014-01-01

    Molecular dynamics simulations have the potential to provide atomic-level detail and insight to important questions in chemical physics that cannot be observed in typical experiments. However, simply generating a long trajectory is insufficient, as researchers must be able to transform the data in a simulation trajectory into specific scientific insights. Although this analysis step has often been taken for granted, it deserves further attention as large-scale simulations become increasingly routine. In this perspective, we discuss the application of Markov models to the analysis of large-scale biomolecular simulations. We draw attention to recent improvements in the construction of these models as well as several important open issues. In addition, we highlight recent theoretical advances that pave the way for a new generation of models of molecular kinetics.

  7. The biomolecular corona of nanoparticles in circulating biological media

    Science.gov (United States)

    Pozzi, D.; Caracciolo, G.; Digiacomo, L.; Colapicchioni, V.; Palchetti, S.; Capriotti, A. L.; Cavaliere, C.; Zenezini Chiozzi, R.; Puglisi, A.; Laganà, A.

    2015-08-01

    When nanoparticles come into contact with biological media, they are covered by a biomolecular `corona', which confers a new identity to the particles. In all the studies reported so far nanoparticles are incubated with isolated plasma or serum that are used as a model for protein adsorption. Anyway, bodily fluids are dynamic in nature so the question arises on whether the incubation protocol, i.e. dynamic vs. static incubation, could affect the composition and structure of the biomolecular corona. Here we let multicomponent liposomes interact with fetal bovine serum (FBS) both statically and dynamically, i.e. in contact with circulating FBS (~40 cm s-1). The structure and composition of the liposome-protein corona, as determined by dynamic light scattering, electrophoretic light scattering and liquid chromatography tandem mass spectrometry, were found to be dependent on the incubation protocol. Specifically, following dynamic exposure to FBS, multicomponent liposomes were less enriched in complement proteins and appreciably more enriched in apolipoproteins and acute phase proteins (e.g. alpha-1-antitrypsin and inter-alpha-trypsin inhibitor heavy chain H3) that are involved in relevant interactions between nanoparticles and living systems. Supported by our results, we speculate that efficient predictive modeling of nanoparticle behavior in vivo will require accurate knowledge of nanoparticle-specific protein fingerprints in circulating biological media.When nanoparticles come into contact with biological media, they are covered by a biomolecular `corona', which confers a new identity to the particles. In all the studies reported so far nanoparticles are incubated with isolated plasma or serum that are used as a model for protein adsorption. Anyway, bodily fluids are dynamic in nature so the question arises on whether the incubation protocol, i.e. dynamic vs. static incubation, could affect the composition and structure of the biomolecular corona. Here we let

  8. A ladder network modelling the electrochemical impedance of the diffusion and reaction processes in semi-infinite space.

    Science.gov (United States)

    Moya, A A

    2016-02-01

    The Gerischer impedance, i.e., the diffusion-reaction impedance of an ionic species in semi-infinite space, has been modelled by means of a novel simple equivalent ladder electric circuit constituted by a finite number of resistors and capacitors, which corresponds to the Cauer structure obtained from development into continued fractions. The Nyquist plots of the impedance of the ladder network or Cauer circuit and the deviation with respect to the Gerischer impedance have been originally analysed as a function of the number of circuit elements. From the Cauer equivalent circuit, a new and simple expression modelling the Gerischer impedance at the limit of the lowest frequencies has been derived. PMID:26763107

  9. PARENT: A Parallel Software Suite for the Calculation of Configurational Entropy in Biomolecular Systems.

    Science.gov (United States)

    Fleck, Markus; Polyansky, Anton A; Zagrovic, Bojan

    2016-04-12

    Accurate estimation of configurational entropy from the in silico-generated biomolecular ensembles, e.g., from molecular dynamics (MD) trajectories, is dependent strongly on exhaustive sampling for physical reasons. This, however, creates a major computational problem for the subsequent estimation of configurational entropy using the Maximum Information Spanning Tree (MIST) or Mutual Information Expansion (MIE) approaches for internal molecular coordinates. In particular, the available software for such estimation exhibits serious limitations when it comes to molecules with hundreds or thousands of atoms, because of its reliance on a serial program architecture. To overcome this problem, we have developed a parallel, hybrid MPI/openMP C++ implementation of MIST and MIE, called PARENT, which is particularly optimized for high-performance computing and provides efficient estimation of configurational entropy in different biological processes (e.g., protein-protein interactions). In addition, PARENT also allows for a detailed mapping of intramolecular allosteric networks. Here, we benchmark the program on a set of 1-μs-long MD trajectories of 10 different protein complexes and their components, demonstrating robustness and good scalability. A direct comparison between MIST and MIE on the same dataset demonstrates a superior convergence behavior for the former approach, when it comes to total simulation length and configurational-space binning. PMID:26989950

  10. Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations.

    Science.gov (United States)

    Takada, Shoji; Kanada, Ryo; Tan, Cheng; Terakawa, Tsuyoshi; Li, Wenfei; Kenzaki, Hiroo

    2015-12-15

    Due to hierarchic nature of biomolecular systems, their computational modeling calls for multiscale approaches, in which coarse-grained (CG) simulations are used to address long-time dynamics of large systems. Here, we review recent developments and applications of CG modeling methods, focusing on our methods primarily for proteins, DNA, and their complexes. These methods have been implemented in the CG biomolecular simulator, CafeMol. Our CG model has resolution such that ∼10 non-hydrogen atoms are grouped into one CG particle on average. For proteins, each amino acid is represented by one CG particle. For DNA, one nucleotide is simplified by three CG particles, representing sugar, phosphate, and base. The protein modeling is based on the idea that proteins have a globally funnel-like energy landscape, which is encoded in the structure-based potential energy function. We first describe two representative minimal models of proteins, called the elastic network model and the classic Go̅ model. We then present a more elaborate protein model, which extends the minimal model to incorporate sequence and context dependent local flexibility and nonlocal contacts. For DNA, we describe a model developed by de Pablo's group that was tuned to well reproduce sequence-dependent structural and thermodynamic experimental data for single- and double-stranded DNAs. Protein-DNA interactions are modeled either by the structure-based term for specific cases or by electrostatic and excluded volume terms for nonspecific cases. We also discuss the time scale mapping in CG molecular dynamics simulations. While the apparent single time step of our CGMD is about 10 times larger than that in the fully atomistic molecular dynamics for small-scale dynamics, large-scale motions can be further accelerated by two-orders of magnitude with the use of CG model and a low friction constant in Langevin dynamics. Next, we present four examples of applications. First, the classic Go̅ model was used to

  11. Artificial Hormone Reaction Networks: Towards Higher Evolvability in Evolutionary Multi-Modular Robotics

    CERN Document Server

    Hamann, Heiko; Schmickl, Thomas; Crailsheim, Karl

    2010-01-01

    The semi-automatic or automatic synthesis of robot controller software is both desirable and challenging. Synthesis of rather simple behaviors such as collision avoidance by applying artificial evolution has been shown multiple times. However, the difficulty of this synthesis increases heavily with increasing complexity of the task that should be performed by the robot. We try to tackle this problem of complexity with Artificial Homeostatic Hormone Systems (AHHS), which provide both intrinsic, homeostatic processes and (transient) intrinsic, variant behavior. By using AHHS the need for pre-defined controller topologies or information about the field of application is minimized. We investigate how the principle design of the controller and the hormone network size affects the overall performance of the artificial evolution (i.e., evolvability). This is done by comparing two variants of AHHS that show different effects when mutated. We evolve a controller for a robot built from five autonomous, cooperating modu...

  12. Photochemical Production of Interpenetrating Polymer Networks; Simultaneous Initiation of Radical and Cationic Polymerization Reactions

    Directory of Open Access Journals (Sweden)

    Jean Pierre Fouassier

    2014-10-01

    Full Text Available In this paper, we propose to review the ways to produce, through photopolymerization, interpenetrating polymer networks (IPN based, e.g., on acrylate/epoxide or acrylate/vinylether blends and to outline the recent developments that allows a one-step procedure (concomitant radical/cationic polymerization, under air or in laminate, under various irradiation conditions (UV/visible/near IR; high/low intensity sources; monochromatic/polychromatic sources; household lamps/laser diodes/Light Emitting Diodes (LEDs. The paper illustrates the encountered mechanisms and the polymerization profiles. A short survey on the available monomer systems and some brief examples of the attained final properties of the IPNs is also provided.

  13. Permutation invariant potential energy surfaces for polyatomic reactions using atomistic neural networks.

    Science.gov (United States)

    Kolb, Brian; Zhao, Bin; Li, Jun; Jiang, Bin; Guo, Hua

    2016-06-14

    The applicability and accuracy of the Behler-Parrinello atomistic neural network method for fitting reactive potential energy surfaces is critically examined in three systems, H + H2 → H2 + H, H + H2O → H2 + OH, and H + CH4 → H2 + CH3. A pragmatic Monte Carlo method is proposed to make efficient choice of the atom-centered mapping functions. The accuracy of the potential energy surfaces is not only tested by fitting errors but also validated by direct comparison in dynamically important regions and by quantum scattering calculations. Our results suggest this method is both accurate and efficient in representing multidimensional potential energy surfaces even when dissociation continua are involved. PMID:27305992

  14. Calculating free-energy profiles in biomolecular systems from fast nonequilibrium processes

    Science.gov (United States)

    Forney, Michael W.; Janosi, Lorant; Kosztin, Ioan

    2008-11-01

    Often gaining insight into the functioning of biomolecular systems requires to follow their dynamics along a microscopic reaction coordinate (RC) on a macroscopic time scale, which is beyond the reach of current all atom molecular dynamics (MD) simulations. A practical approach to this inherently multiscale problem is to model the system as a fictitious overdamped Brownian particle that diffuses along the RC in the presence of an effective potential of mean force (PMF) due to the rest of the system. By employing the recently proposed FR method [I. Kosztin , J. Chem. Phys. 124, 064106 (2006)], which requires only a small number of fast nonequilibrium MD simulations of the system in both forward and time reversed directions along the RC, we reconstruct the PMF: (1) of deca-alanine as a function of its end-to-end distance, and (2) that guides the motion of potassium ions through the gramicidin A channel. In both cases the computed PMFs are found to be in good agreement with previous results obtained by different methods. Our approach appears to be about one order of magnitude faster than the other PMF calculation methods and, in addition, it also provides the position-dependent diffusion coefficient along the RC. Thus, the obtained PMF and diffusion coefficient can be used in an overdamped Brownian model to estimate important characteristics of the studied systems, e.g., the mean folding time of the stretched deca-alanine and the mean diffusion time of the potassium ion through gramicidin A.

  15. Calculating free energy profiles in biomolecular systems from fast non-equilibrium processes

    CERN Document Server

    Forney, Michael; Kosztin, Ioan

    2008-01-01

    Often gaining insight into the functioning of biomolecular systems requires to follow their dynamics along a microscopic reaction coordinate (RC) on a macroscopic time scale, which is beyond the reach of current all atom molecular dynamics (MD) simulations. A practical approach to this inherently multiscale problem is to model the system as a fictitious overdamped Brownian particle that diffuses along the RC in the presence of an effective potential of mean force (PMF) due to the rest of the system. By employing the recently proposed FR method [I. Kosztin et al., J. of Chem. Phys. 124, 064106 (2006)], which requires only a small number of fast nonequilibrium MD simulations of the system in both forward and time reversed directions along the RC, we reconstruct the PMF: (1) of deca-alanine as a function of its end-to-end distance, and (2) that guides the motion of potassium ions through the gramicidin A channel. In both cases the computed PMFs are found to be in good agreement with previous results obtained by ...

  16. Symmetry breaking in a bulk-surface reaction-diffusion model for signalling networks

    Science.gov (United States)

    Rätz, Andreas; Röger, Matthias

    2014-08-01

    Signalling molecules play an important role for many cellular functions. We investigate here a general system of two membrane reaction-diffusion equations coupled to a diffusion equation inside the cell by a Robin-type boundary condition and a flux term in the membrane equations. A specific model of this form was recently proposed by the authors for the GTPase cycle in cells. We investigate here a putative role of diffusive instabilities in cell polarization. By a linearized stability analysis, we identify two different mechanisms. The first resembles a classical Turing instability for the membrane subsystem and requires (unrealistically) large differences in the lateral diffusion of activator and substrate. On the other hand, the second possibility is induced by the difference in cytosolic and lateral diffusion and appears much more realistic. We complement our theoretical analysis by numerical simulations that confirm the new stability mechanism and allow us to investigate the evolution beyond the regime where the linearization applies.

  17. Compartmentalization and Cell Division through Molecular Discreteness and Crowding in a Catalytic Reaction Network

    Directory of Open Access Journals (Sweden)

    Atsushi Kamimura

    2014-10-01

    Full Text Available Explanation of the emergence of primitive cellular structures from a set of chemical reactions is necessary to unveil the origin of life and to experimentally synthesize protocells. By simulating a cellular automaton model with a two-species hypercycle, we demonstrate the reproduction of a localized cluster; that is, a protocell with a growth-division process emerges when the replication and degradation speeds of one species are respectively slower than those of the other species, because of overcrowding of molecules as a natural outcome of the replication. The protocell exhibits synchrony between its division process and replication of the minority molecule. We discuss the effects of the crowding molecule on the formation of primitive structures. The generality of this result is demonstrated through the extension of our model to a hypercycle with three molecular species, where a localized layered structure of molecules continues to divide, triggered by the replication of a minority molecule at the center.

  18. Reproduction of a Protocell by Replication of a Minority Molecule in a Catalytic Reaction Network

    Science.gov (United States)

    Kamimura, Atsushi; Kaneko, Kunihiko

    2010-12-01

    For understanding the origin of life, it is essential to explain the development of a compartmentalized structure, which undergoes growth and division, from a set of chemical reactions. In this study, a hypercycle with two chemicals that mutually catalyze each other is considered in order to show that the reproduction of a protocell with a growth-division process naturally occurs when the replication speed of one chemical is considerably slower than that of the other chemical, and molecules are crowded as a result of replication. It is observed that the protocell divides after a minority molecule is replicated at a slow synthesis rate, and thus, a synchrony between the reproduction of a cell and molecule replication is achieved. The robustness of such protocells against the invasion of parasitic molecules is also demonstrated.

  19. On global exponential stability and existence of periodic solutions for BAM neural networks with distributed delays and reaction-diffusion terms

    Energy Technology Data Exchange (ETDEWEB)

    Lou Xuyang [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: louxuyang28945@163.com; Cui Baotong [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)], E-mail: btcui@sohu.com; Wu Wei [Research Center of Control Science and Engineering, Southern Yangtze University, 1800 Lihu Road, Wuxi, Jiangsu 214122 (China)

    2008-05-15

    Both exponential stability and existence of periodic solutions are considered for a class of bi-directional associative memory (BAM) neural networks with distributed delays and reaction-diffusion terms by constructing suitable Lyapunov functional and Young inequality technique. The general sufficient conditions are given ensuring the global exponential stability and existence of periodic solutions of BAM neural networks with distributed delays and reaction-diffusion terms. The earlier results are extended and improved, and an illustrative example is given to demonstrate the effectiveness of the results in this paper.

  20. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  1. Computational methods to study the structure and dynamics of biomolecules and biomolecular processes from bioinformatics to molecular quantum mechanics

    CERN Document Server

    2014-01-01

    Since the second half of the 20th century machine computations have played a critical role in science and engineering. Computer-based techniques have become especially important in molecular biology, since they often represent the only viable way to gain insights into the behavior of a biological system as a whole. The complexity of biological systems, which usually needs to be analyzed on different time- and size-scales and with different levels of accuracy, requires the application of different approaches, ranging from comparative analysis of sequences and structural databases, to the analysis of networks of interdependence between cell components and processes, through coarse-grained modeling to atomically detailed simulations, and finally to molecular quantum mechanics. This book provides a comprehensive overview of modern computer-based techniques for computing the structure, properties and dynamics of biomolecules and biomolecular processes. The twenty-two chapters, written by scientists from all over t...

  2. Electron spin and the origin of Bio-homochirality II. Prebiotic inorganic-organic reaction model

    CERN Document Server

    Wang, Wei

    2014-01-01

    The emergence of biomolecular homochirality is a critically important question about life phenomenon and the origins of life. In a previous paper (arXiv:1309.1229), I tentatively put forward a new hypothesis that the emergence of a single chiral form of biomolecules in living organisms is specifically determined by the electron spin state during their enzyme-catalyzed synthesis processes. However, how a homochirality world of biomolecules could have formed in the absence of enzymatic networks before the origins of life remains unanswered. Here I discussed the electron spin properties in Fe3S4, ZnS, and transition metal doped dilute magnetic ZnS, and their possible roles in the prebiotic synthesis of chiral molecules. Since the existence of these minerals in hydrothermal vent systems is matter of fact, the suggested prebiotic inorganic-organic reaction model, if can be experimentally demonstrated, may help explain where and how life originated on early Earth.

  3. Bioelectronic Interface Connecting Reversible Logic Gates Based on Enzyme and DNA Reactions.

    Science.gov (United States)

    Guz, Nataliia; Fedotova, Tatiana A; Fratto, Brian E; Schlesinger, Orr; Alfonta, Lital; Kolpashchikov, Dmitry M; Katz, Evgeny

    2016-07-18

    It is believed that connecting biomolecular computation elements in complex networks of communicating molecules may eventually lead to a biocomputer that can be used for diagnostics and/or the cure of physiological and genetic disorders. Here, a bioelectronic interface based on biomolecule-modified electrodes has been designed to bridge reversible enzymatic logic gates with reversible DNA-based logic gates. The enzyme-based Fredkin gate with three input and three output signals was connected to the DNA-based Feynman gate with two input and two output signals-both representing logically reversible computing elements. In the reversible Fredkin gate, the routing of two data signals between two output channels was controlled by the control signal (third channel). The two data output signals generated by the Fredkin gate were directed toward two electrochemical flow cells, responding to the output signals by releasing DNA molecules that serve as the input signals for the next Feynman logic gate based on the DNA reacting cascade, producing, in turn, two final output signals. The Feynman gate operated as the controlled NOT gate (CNOT), where one of the input channels controlled a NOT operation on another channel. Both logic gates represented a highly sophisticated combination of input-controlled signal-routing logic operations, resulting in redirecting chemical signals in different channels and performing orchestrated computing processes. The biomolecular reaction cascade responsible for the signal processing was realized by moving the solution from one reacting cell to another, including the reacting flow cells and electrochemical flow cells, which were organized in a specific network mimicking electronic computing circuitries. The designed system represents the first example of high complexity biocomputing processes integrating enzyme and DNA reactions and performing logically reversible signal processing. PMID:27145731

  4. Self-assembling biomolecular catalysts for hydrogen production

    Science.gov (United States)

    Jordan, Paul C.; Patterson, Dustin P.; Saboda, Kendall N.; Edwards, Ethan J.; Miettinen, Heini M.; Basu, Gautam; Thielges, Megan C.; Douglas, Trevor

    2016-02-01

    The chemistry of highly evolved protein-based compartments has inspired the design of new catalytically active materials that self-assemble from biological components. A frontier of this biodesign is the potential to contribute new catalytic systems for the production of sustainable fuels, such as hydrogen. Here, we show the encapsulation and protection of an active hydrogen-producing and oxygen-tolerant [NiFe]-hydrogenase, sequestered within the capsid of the bacteriophage P22 through directed self-assembly. We co-opted Escherichia coli for biomolecular synthesis and assembly of this nanomaterial by expressing and maturing the EcHyd-1 hydrogenase prior to expression of the P22 coat protein, which subsequently self assembles. By probing the infrared spectroscopic signatures and catalytic activity of the engineered material, we demonstrate that the capsid provides stability and protection to the hydrogenase cargo. These results illustrate how combining biological function with directed supramolecular self-assembly can be used to create new materials for sustainable catalysis.

  5. Function of Amphiphilic Biomolecular Machines: Elastic Protein-based Polymers

    Science.gov (United States)

    Urry, Dan W.

    2000-03-01

    Elastic protein-based polymers function as biomolecular machines due to inverse temperature transitions of hydrophobic folding and assembly. The transitions occur either on raising the temperature from below to above the transition temperature, Tt, or on isothermally lowering Tt from above to below an operating temperature. The inverse temperature transition involves a decrease in entropy of the polymer component of the system on raising the temperature and a larger increase in solvent entropy on hydrophobic association. Tt depends on the quantity of hydrophobic hydration that undergoes transition to bulk water. Designed amphiphilic polymers perform free energy transductions involving the intensive variables of mechanical force, pressure, temperature, chemical potential, electrochemical potential and electromagnetic radiation and define a set of five axioms for their function as machines. The physical basis for these diverse energy conversions is competition for hydration between apolar (hydrophobic) and polar (e.g., charged) moieties. The effectiveness of these Tt-type entropic elastic protein-based machines is due to repeating peptide sequences that form regular, dynamic repeating structures and exhibit damping of backbone torsional oscillations on extension.

  6. A programmable biomolecular computing machine with bacterial phenotype output.

    Science.gov (United States)

    Kossoy, Elizaveta; Lavid, Noa; Soreni-Harari, Michal; Shoham, Yuval; Keinan, Ehud

    2007-07-23

    The main advantage of autonomous biomolecular computing devices over electronic computers is their ability to interact directly with biological systems. No interface is required since all components of molecular computers, including hardware, software, input, and output are molecules that interact in solution along a cascade of programmable chemical events. Here, we demonstrate for the first time that the output of a computation preduced by a molecular finite automaton can be a visible bacterial phenotype. Our 2-symbol-2-state finite automaton utilized linear double-stranded DNA inputs that were prepared by inserting a string of six base pair symbols into the lacZ gene on the pUC18 plasmid. The computation resulted in a circular plasmid that differed from the original pUC18 by either a 9 base pair (accepting state) or 11 base pair insert (unaccepting state) within the lacZ alpha region gene. Upon transformation and expression of the resultant plasmids in E. coli, the accepting state was represented by production of functional beta-galactosidase and formation of blue colonies on X-gal medium. In contrast, the unaccepting state was represented by white colonies due to a shift in the open reading frame of lacZ. PMID:17562552

  7. SWISS-PROT: connecting biomolecular knowledge via a protein database.

    Science.gov (United States)

    Gasteiger, E; Jung, E; Bairoch, A

    2001-07-01

    With the explosive growth of biological data, the development of new means of data storage was needed. More and more often biological information is no longer published in the conventional way via a publication in a scientific journal, but only deposited into a database. In the last two decades these databases have become essential tools for researchers in biological sciences. Biological databases can be classified according to the type of information they contain. There are basically three types of sequence-related databases (nucleic acid sequences, protein sequences and protein tertiary structures) as well as various specialized data collections. It is important to provide the users of biomolecular databases with a degree of integration between these databases as by nature all of these databases are connected in a scientific sense and each one of them is an important piece to biological complexity. In this review we will highlight our effort in connecting biological information as demonstrated in the SWISS-PROT protein database. PMID:11488411

  8. Moving Objects Trajectoty Prediction Based on Artificial Neural Network Approximator by Considering Instantaneous Reaction Time, Case Study: CAR Following

    Science.gov (United States)

    Poor Arab Moghadam, M.; Pahlavani, P.

    2015-12-01

    Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network approximator was used to introduce a trajectory model for vehicle movements. In this regard, the Levenberg-Marquardt back propagation function and the hyperbolic tangent sigmoid function were employed as the training and the transfer functions, respectively. One of the important aspects in identifying driver behavior is the reaction time. This parameter shows the period between the time the driver recognizes a stimulus and the time a suitable response is shown to that stimulus. In this paper, the actual data on car following from the NGSIM project was used to determine the performance of the proposed model. This dataset was used for the purpose of expanding behavioral algorithm in micro simulation. Sixty percent of the data was entered into the designed artificial neural network approximator as the training data, twenty percent as the testing data, and twenty percent as the evaluation data. A statistical and a micro simulation method were employed to show the accuracy of the proposed model. Moreover, the two popular Gipps and Helly models were implemented. Finally, it was shown that the accuracy of the proposed model was much higher - and its computational costs were lower - than those of other models when calibration operations were not performed on these models. Therefore, the proposed model can be used for displaying and predicting trajectories of moving objects being

  9. MOVING OBJECTS TRAJECTOTY PREDICTION BASED ON ARTIFICIAL NEURAL NETWORK APPROXIMATOR BY CONSIDERING INSTANTANEOUS REACTION TIME, CASE STUDY: CAR FOLLOWING

    Directory of Open Access Journals (Sweden)

    M. Poor Arab Moghadam

    2015-12-01

    Full Text Available Car following models as well-known moving objects trajectory problems have been used for more than half a century in all traffic simulation software for describing driving behaviour in traffic flows. However, previous empirical studies and modeling about car following behavior had some important limitations. One of the main and clear defects of the introduced models was the very large number of parameters that made their calibration very time-consuming and costly. Also, any change in these parameters, even slight ones, severely disrupted the output. In this study, an artificial neural network approximator was used to introduce a trajectory model for vehicle movements. In this regard, the Levenberg-Marquardt back propagation function and the hyperbolic tangent sigmoid function were employed as the training and the transfer functions, respectively. One of the important aspects in identifying driver behavior is the reaction time. This parameter shows the period between the time the driver recognizes a stimulus and the time a suitable response is shown to that stimulus. In this paper, the actual data on car following from the NGSIM project was used to determine the performance of the proposed model. This dataset was used for the purpose of expanding behavioral algorithm in micro simulation. Sixty percent of the data was entered into the designed artificial neural network approximator as the training data, twenty percent as the testing data, and twenty percent as the evaluation data. A statistical and a micro simulation method were employed to show the accuracy of the proposed model. Moreover, the two popular Gipps and Helly models were implemented. Finally, it was shown that the accuracy of the proposed model was much higher - and its computational costs were lower - than those of other models when calibration operations were not performed on these models. Therefore, the proposed model can be used for displaying and predicting trajectories of moving

  10. Development of an informatics infrastructure for data exchange of biomolecular simulations: Architecture, data models and ontology.

    Science.gov (United States)

    Thibault, J C; Roe, D R; Eilbeck, K; Cheatham Iii, T E; Facelli, J C

    2015-01-01

    Biomolecular simulations aim to simulate structure, dynamics, interactions, and energetics of complex biomolecular systems. With the recent advances in hardware, it is now possible to use more complex and accurate models, but also reach time scales that are biologically significant. Molecular simulations have become a standard tool for toxicology and pharmacology research, but organizing and sharing data - both within the same organization and among different ones - remains a substantial challenge. In this paper we review our recent work leading to the development of a comprehensive informatics infrastructure to facilitate the organization and exchange of biomolecular simulations data. Our efforts include the design of data models and dictionary tools that allow the standardization of the metadata used to describe the biomedical simulations, the development of a thesaurus and ontology for computational reasoning when searching for biomolecular simulations in distributed environments, and the development of systems based on these models to manage and share the data at a large scale (iBIOMES), and within smaller groups of researchers at laboratory scale (iBIOMES Lite), that take advantage of the standardization of the meta data used to describe biomolecular simulations. PMID:26387907

  11. Prediction of firing time of Magnesio Thermic Reduction (MTR) reaction and study of relative importance of the dependent parameters using artificial neural network

    International Nuclear Information System (INIS)

    In uranium metal production process, uranium ingot is generally produced by Magnesio Thermic Reduction (MTR) of uranium tetra fluoride. This highly exothermic reaction is carried out in a closed vessel, called 'bomb reactor', lined with MgF2. Initiation of this instantaneous reaction is indicated by sudden temperature shoot up of the reaction mixture and it is called firing. It is observed that time required to initiate the reaction (firing time) depends on various parameters of the reactants and lining material along with operating parameters. But no correlation is available to correlate the firing time as a function of these parameters together. Artificial neural network is used here to predict firing time based on these parameters using BIKAS software and exclusive studies have been carried out here to study the relative importance of the parameters on firing time. (author)

  12. Soft Supercharging of Biomolecular Ions in Electrospray Ionization Mass Spectrometry

    Science.gov (United States)

    Chingin, Konstantin; Xu, Ning; Chen, Huanwen

    2014-06-01

    The charge states of biomolecular ions in ESI-MS can be significantly increased by the addition of low-vapor supercharging (SC) reagents into the spraying solution. Despite the considerable interest from the community, the mechanistic aspects of SC are not well understood and are hotly debated. Arguments that denaturation accounts for the increased charging observed in proteins sprayed from aqueous solutions containing SC reagent have been published widely, but often with incomplete or ambiguous supporting data. In this work, we explored ESI MS charging and SC behavior of several biopolymers including proteins and DNA oligonucleotides. Analytes were ionized from 100 mM ammonium acetate (NH4Ac) aqueous buffer in both positive (ESI+) and negative (ESI-) ion modes. SC was induced either with m-NBA or by the elevated temperature of ESI capillary. For all the analytes studied we, found striking differences in the ESI MS response to these two modes of activation. The data suggest that activation with m-NBA results in more extensive analyte charging with lower degree of denaturation. When working solution with m-NBA was analyzed at elevated temperatures, the SC effect from m-NBA was neutralized. Instead, the net SC effect was similar to the SC effect achieved by thermal activation only. Overall, our observations indicate that SC reagents enhance ESI charging of biomolecules via distinctly different mechanism compared with the traditional approaches based on analyte denaturation. Instead, the data support the hypothesis that the SC phenomenon involves a direct interaction between a biopolymer and SC reagent occurring in evaporating ESI droplets.

  13. An Analytical Framework for Studying Small-Number Effects in Catalytic Reaction Networks: A Probability Generating Function Approach to Chemical Master Equations.

    Science.gov (United States)

    Nakagawa, Masaki; Togashi, Yuichi

    2016-01-01

    Cell activities primarily depend on chemical reactions, especially those mediated by enzymes, and this has led to these activities being modeled as catalytic reaction networks. Although deterministic ordinary differential equations of concentrations (rate equations) have been widely used for modeling purposes in the field of systems biology, it has been pointed out that these catalytic reaction networks may behave in a way that is qualitatively different from such deterministic representation when the number of molecules for certain chemical species in the system is small. Apart from this, representing these phenomena by simple binary (on/off) systems that omit the quantities would also not be feasible. As recent experiments have revealed the existence of rare chemical species in cells, the importance of being able to model potential small-number phenomena is being recognized. However, most preceding studies were based on numerical simulations, and theoretical frameworks to analyze these phenomena have not been sufficiently developed. Motivated by the small-number issue, this work aimed to develop an analytical framework for the chemical master equation describing the distributional behavior of catalytic reaction networks. For simplicity, we considered networks consisting of two-body catalytic reactions. We used the probability generating function method to obtain the steady-state solutions of the chemical master equation without specifying the parameters. We obtained the time evolution equations of the first- and second-order moments of concentrations, and the steady-state analytical solution of the chemical master equation under certain conditions. These results led to the rank conservation law, the connecting state to the winner-takes-all state, and analysis of 2-molecules M-species systems. A possible interpretation of the theoretical conclusion for actual biochemical pathways is also discussed. PMID:27047384

  14. Development of a biomolecular assay for postmortem diagnosis of Taenia saginata Cysticercosis.

    Science.gov (United States)

    Chiesa, Francesco; Dalmasso, Alessandra; Bellio, Alberto; Martinetti, Manuela; Gili, Stefano; Civera, Tiziana

    2010-10-01

    Bovine cysticercosis is caused by the larval stage of the human tapeworm Taenia saginata. According to European data on meat inspection, the prevalence ranges from 0.007% to 6.8%, but the real prevalence is considered to be at least 10 times higher. Laboratory confirmation of the etiological agent is based on gross, stereomicroscopic, and histological examination of submitted specimens. False identifications may occur, possibly because of death and degeneration of cysts, or because taeniid larvae and other tissue parasites, such as Sarcocystis spp., may cause similar macroscopic morphological lesions. Therefore, tests that can warrant sure identification of taeniid lesions and calcified cysts in the muscle are needed. The focus of our study was to develop a suitable postmortem test that could be applied on putative lesions by T. saginata cysticerci, as ambiguously diagnosed after routine meat inspection. In particular, we proposed a biomolecular assay targeting the mitochondrial cytochrome c oxidase subunit I gene (COI). For developing the polymerase chain reaction assay, viable cysts of Cysticercus bovis (n = 10) were used as positive reference samples, and those of Echinococcus granulosus (n = 3), Cysticercus tenuicollis (n = 3), and Sarcocystis spp. (n = 4) as reference negative controls. Further, to evaluate the applicability of the proposed assay, 171 samples of bovine muscular tissue, obtained from local slaughterhouses and containing lesions recognized as T. saginata cysticerci by macroscopic examination, were tested. The proposed test confirmed the diagnosis at postmortem inspection in 94.7% (162/171) of samples. In conclusion, the assay developed in this study, amplifying a short fragment from the mitochondrial gene COI, showed to be suitable for samples containing both viable and degenerating T. saginata cysticerci, yielding an unequivocal diagnosis. PMID:20618079

  15. Multiple Features Based Approach to Extract Bio-molecular Event Triggers Using Conditional Random Field

    Directory of Open Access Journals (Sweden)

    Amit Majumder

    2012-11-01

    Full Text Available The purpose of Biomedical Natural Language Processing (BioNLP is to capture biomedical phenomena from textual data by extracting relevant entities, information and relations between biomedical entities (i.e. proteins and genes. In general, in most of the published papers, only binary relations were extracted. In a recent past, the focus is shifted towards extracting more complex relations in the form of bio-molecular events that may include several entities or other relations. In this paper we propose an approach that enables event trigger extraction of relatively complex bio-molecular events. We approach this problem as a detection of bio-molecular event trigger using the well-known algorithm, namely Conditional Random Field (CRF. We apply our experiments on development set. It shows the overall average recall, precision and F-measure values of 64.27504%, 69.97559% and 67.00429%, respectively for the event detection.

  16. Output-input coupling in thermally fluctuating biomolecular machines

    CERN Document Server

    Kurzynski, Michal; Chelminiak, Przemyslaw

    2011-01-01

    Biological molecular machines are proteins that operate under isothermal conditions hence are referred to as free energy transducers. They can be formally considered as enzymes that simultaneously catalyze two chemical reactions: the free energy-donating reaction and the free energy-accepting one. Most if not all biologically active proteins display a slow stochastic dynamics of transitions between a variety of conformational substates composing their native state. In the steady state, this dynamics is characterized by mean first-passage times between transition substates of the catalyzed reactions. On taking advantage of the assumption that each reaction proceeds through a single pair (the gate) of conformational transition substates of the enzyme-substrates complex, analytical formulas were derived for the flux-force dependence of the both reactions, the respective stalling forces and the degree of coupling between the free energy-accepting (output) reaction flux and the free energy-donating (input) one. Th...

  17. The Chemical Master Equation Approach to Nonequilibrium Steady-State of Open Biochemical Systems: Linear Single-Molecule Enzyme Kinetics and Nonlinear Biochemical Reaction Networks

    Directory of Open Access Journals (Sweden)

    Lisa M. Bishop

    2010-09-01

    Full Text Available We develop the stochastic, chemical master equation as a unifying approach to the dynamics of biochemical reaction systems in a mesoscopic volume under a living environment. A living environment provides a continuous chemical energy input that sustains the reaction system in a nonequilibrium steady state with concentration fluctuations. We discuss the linear, unimolecular single-molecule enzyme kinetics, phosphorylation-dephosphorylation cycle (PdPC with bistability, and network exhibiting oscillations. Emphasis is paid to the comparison between the stochastic dynamics and the prediction based on the traditional approach based on the Law of Mass Action. We introduce the difference between nonlinear bistability and stochastic bistability, the latter has no deterministic counterpart. For systems with nonlinear bistability, there are three different time scales: (a individual biochemical reactions, (b nonlinear network dynamics approaching to attractors, and (c cellular evolution. For mesoscopic systems with size of a living cell, dynamics in (a and (c are stochastic while that with (b is dominantly deterministic. Both (b and (c are emergent properties of a dynamic biochemical network; We suggest that the (c is most relevant to major cellular biochemical processes such as epi-genetic regulation, apoptosis, and cancer immunoediting. The cellular evolution proceeds with transitions among the attractors of (b in a “punctuated equilibrium” manner.

  18. The chemical master equation approach to nonequilibrium steady-state of open biochemical systems: linear single-molecule enzyme kinetics and nonlinear biochemical reaction networks.

    Science.gov (United States)

    Qian, Hong; Bishop, Lisa M

    2010-01-01

    We develop the stochastic, chemical master equation as a unifying approach to the dynamics of biochemical reaction systems in a mesoscopic volume under a living environment. A living environment provides a continuous chemical energy input that sustains the reaction system in a nonequilibrium steady state with concentration fluctuations. We discuss the linear, unimolecular single-molecule enzyme kinetics, phosphorylation-dephosphorylation cycle (PdPC) with bistability, and network exhibiting oscillations. Emphasis is paid to the comparison between the stochastic dynamics and the prediction based on the traditional approach based on the Law of Mass Action. We introduce the difference between nonlinear bistability and stochastic bistability, the latter has no deterministic counterpart. For systems with nonlinear bistability, there are three different time scales: (a) individual biochemical reactions, (b) nonlinear network dynamics approaching to attractors, and (c) cellular evolution. For mesoscopic systems with size of a living cell, dynamics in (a) and (c) are stochastic while that with (b) is dominantly deterministic. Both (b) and (c) are emergent properties of a dynamic biochemical network; We suggest that the (c) is most relevant to major cellular biochemical processes such as epi-genetic regulation, apoptosis, and cancer immunoediting. The cellular evolution proceeds with transitions among the attractors of (b) in a "punctuated equilibrium" manner. PMID:20957107

  19. Optical Coherence Tomography and Biomolecular Imaging with Coherent Raman Scattering Microscopy

    DEFF Research Database (Denmark)

    Andersson-Engels, Stefan; Andersen, Peter E.

    2014-01-01

    The Special Section on Selected Topics in Biophotonics: Optical Coherence Tomography and Biomolecular Imaging with Coherent Raman Scattering Microscopy comprises two invited review papers and several contributed papers from the summer school Biophotonics ’13, as well as contributed papers within...

  20. Transition metal bioconjugates with an organometallic link between the metal and the biomolecular scaffold

    OpenAIRE

    Monney, Angèle; Albrecht, Martin

    2013-01-01

    This overview compiles recent advances in the synthesis and application of organometallic bioconjugates that comprise a metal–carbon linkage between the metal and the biomolecular scaffold. This specific area of bioorganometallic chemistry has been spurred by the discovery of naturally occurring bioorganometallic compounds and afforded organometallic bioconjugates from transition metals binding to amino acids, nucleic acids and other biomolecules. These artificial bioorganometallic compounds ...

  1. Computer Programming and Biomolecular Structure Studies: A Step beyond Internet Bioinformatics

    Science.gov (United States)

    Likic, Vladimir A.

    2006-01-01

    This article describes the experience of teaching structural bioinformatics to third year undergraduate students in a subject titled "Biomolecular Structure and Bioinformatics." Students were introduced to computer programming and used this knowledge in a practical application as an alternative to the well established Internet bioinformatics…

  2. In situ construction of three anion-dependent cu(i) coordination networks as promising heterogeneous catalysts for azide-alkyne "click" reactions.

    Science.gov (United States)

    Xu, Zhenghu; Han, Lu Lu; Zhuang, Gui Lin; Bai, Jing; Sun, Di

    2015-05-18

    Three Cu(I) coordination networks, namely, {[Cu2(bpz)2(CN)X]·CH3CN}n, (X = Cl, 1; I, 3), {[Cu6(bpz)6(CH3CN)3(CN)3Br]·2OH·14CH3CN}n, (2, bpz = 3,3',5,5'-tetramethyl-4,4'-bipyrazole), were prepared by using solvothermal method. The cyanide ligands in these networks were generated in situ by cleavage of C-C bond of MeCN under solvothermal condition. The structures of these networks are dependent on halogen anions. Complex 1 is a ladderlike structure with μ2-CN(-) as rung and μ2-bpz as armrest. The Cl(-) in 1 is at terminal position but does not extend the one-dimensional (1D) ladder to higher dimensionalities. Complex 2 is a three-dimensional (3D) framework comprised of novel planar [Cu3Br] triangle and single Cu nodes, which are extended by μ2-bpz and μ2-CN(-) to form a novel (3,9)-connected gfy network. Density functional theory calculations showed that single-electron delocalization of Br atom induces the plane structure of [Cu3Br]. Complex 3 also possesses a similar ladderlike subunit as in 1, but the I(-) acts as bidentate bridge to extend the ladder to 3D framework with a four-connected sra topology. The three networks show notable catalytic activity on the click reaction. The compared catalytic results demonstrate that complex 2 possesses the best catalysis performance among three complexes, which is ascribed to the largest solvent-accessible void (porosity: 2 (29.4%) > 1 (25.7%) > 3 (17.6%)) and the more Cu(I) active sites in 2. The present combined structure-property studies provide not only a new synthetic route to obtain a new kind of catalyst for click reaction but also the new insights on catalyst structure-function relationships. PMID:25941881

  3. A random walk solution for modeling solute transport with network reactions and multi-rate mass transfer in heterogeneous systems: Impact of biofilms

    Science.gov (United States)

    Henri, Christopher V.; Fernàndez-Garcia, Daniel

    2015-12-01

    The interplay between the spatial variability of the aquifer hydraulic properties, mass transfer due to sub-grid heterogeneity and chemical reactions often complicates reactive transport simulations. It is well documented that hydro-biochemical properties are ubiquitously heterogeneous and that diffusion and slow advection at the sub-grid scale typically leads to the conceptualization of an aquifer as a multi-porosity system. Within this context, chemical reactions taking place in mobile/immobile water regions can be substantially different between each other. This paper presents a particle-based method that can efficiently simulate heterogeneity, network reactions and multi-rate mass transfer. The approach is based on the development of transition probabilities that describe the likelihood that particles belonging to a given species and mobile/immobile domain at a given time will be transformed into another species and mobile/immobile domain afterwards. The joint effect of mass transfer and sequential degradation is shown to be non-trivial. A characteristic rebound of degradation products can be observed. This late rebound of concentrations is not driven by any change in the flow regime (e.g., pumping ceases in the pump-and-treat remediation strategy) but due to the natural interplay between mass transfer and chemical reactions. To illustrate that the method can simultaneously represent mass transfer, spatially varying properties and network reactions without numerical problems, we have simulated the degradation of tetrachloroethylene (PCE) in a three-dimensional fully heterogeneous aquifer subjected to rate-limited mass transfer. Two types of degradation modes were considered to compare the effect of an active biofilm with that of clay pods present in the aquifer. Results of the two scenarios display significantly differences. Biofilms that promote the degradation of compounds in an immobile region are shown to significantly enhance degradation, rapidly producing

  4. ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining

    OpenAIRE

    Sivachenko Andrey Y; Huan Tianxiao; Harrison Scott H; Chen Jake Y

    2008-01-01

    Abstract Background New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of c...

  5. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; de Fries, Louise Skovlund

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social...

  6. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  7. Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurodegenerative diseases

    OpenAIRE

    Maia, Pedro D; Kutz, J Nathan

    2016-01-01

    The presence of diffuse Focal Axonal Swellings (FAS) is a hallmark cellular feature in many neurodegenerative diseases and traumatic brain injury. Among other things, the FAS have a significant impact on spike-train encodings that propagate through the affected neurons, leading to compromised signal processing on a neuronal network level. This work merges, for the first time, three fields of study: (i) signal processing in excitatory-inhibitory (EI) networks of neurons via population codes, (...

  8. Chemical networks*

    OpenAIRE

    Thi Wing-Fai

    2015-01-01

    This chapter discusses the fundamental ideas of how chemical networks are build, their strengths and limitations. The chemical reactions that occur in disks combine the cold phase reactions used to model cold molecular clouds with the hot chemistry applied to planetary atmosphere models. With a general understanding of the different types of reactions that can occur, one can proceed in building a network of chemical reactions and use it to explain the abundance of species seen in disks. One o...

  9. New product development with the innovative biomolecular sublingual immunotherapy formulations for the management of allergic rhinitis

    Directory of Open Access Journals (Sweden)

    Frati F

    2014-09-01

    Full Text Available Franco Frati,1 Lorenzo Cecchi,2,3 Enrico Scala,4 Erminia Ridolo,5 Ilaria Dell'Albani,1 Eleni Makrì,6 Giovanni Pajno,7 Cristoforo Incorvaia6 1Medical and Scientific Department, Stallergenes, Milan, Italy; 2Interdepartmental Centre of Bioclimatology, University of Florence, Florence, Italy; 3Allergy and Clinical Immunology Section, Azienda Sanitaria di Prato, Prato, Italy; 4Experimental Allergy Unit, IDI-IRCCS, Rome, Italy; 5Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy; 6Allergy/Pulmonary Rehabilitation, ICP Hospital, Milan, Italy; 7Department of Pediatrics, Allergy Unit, University of Messina, Messina, Italy Abstract: The molecular allergy technique, currently defined as component-resolved diagnosis, significantly improved the diagnosis of allergy, allowing for differentiation between molecules actually responsible for clinical symptoms (genuine sensitizers and those simply cross-reacting or shared by several sources (panallergens, thus influencing the appropriate management of a patient's allergy. This also concerns allergen immunotherapy (AIT, which may be prescribed more precisely based on the component-resolved diagnosis results. However, the advance in diagnosis needs to be mirrored in AIT. According to consensus documents and to expectations of specialists, therapy should be based on standardized extracts containing measured amounts of the clinically relevant molecules, ie, the major allergens. The new generation of extracts for sublingual immunotherapy fulfills these requirements and are thus defined as biomolecular (BM. BM refers to natural extracts with a defined content of major allergens in micrograms. All Staloral BM products are indicated for the treatment of allergic rhinitis with or without asthma. The effectiveness of AIT is related to its ability to modify the immunological response of allergic subjects. The 5-grass and house dust mite extracts were evaluated addressing the T helper 1, T

  10. Reactive monolayers for surface gradients and biomolecular patterned interfaces

    NARCIS (Netherlands)

    Nicosia, C.

    2013-01-01

    Self-assembled monolayers (SAMs) are an excellent platform to implement and develop interfacial reactions for the preparation of versatile materials of pivotal importance for the fabrication of, among others, biochips, sensors, catalysts, smart surfaces and electronic devices. The development of met

  11. Pyrolysis reaction networks for lignin model compounds: unraveling thermal deconstruction of β-O-4 and α-O-4 compounds

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Yong S.; Singh, Rahul; Zhang, Jing; Balasubramanian, Ganesh; Sturgeon, Matthew R.; Katahira, Rui; Chupka, Gina; Beckham, Gregg T.; Shanks, Brent H.

    2016-01-01

    Although lignin is one of the main components of biomass, its pyrolysis chemistry is not well understood due to complex heterogeneity. To gain insights into this chemistry, the pyrolysis of seven lignin model compounds (five ..beta..-O-4 and two ..alpha..-O-4 linked molecules) was investigated in a micropyrolyzer connected to GC-MS/FID. According to quantitative product mole balance for the reaction networks, concerted retro-ene fragmentation and homolytic dissociation were strongly suggested as the initial reaction step for ..beta..-O-4 compounds and ..alpha..-O-4 compounds, respectively. The difference in reaction pathway between compounds with different linkages was believed to result from thermodynamics of the radical initiation. The rate constants for the different reaction pathways were predicted from ab initio density functional theory calculations and pre-exponential literature values. The computational findings were consistent with the experiment results, further supporting the different pyrolysis mechanisms for the ..beta..-ether linked and ..alpha..-ether linked compounds. A combination of the two pathways from the dimeric model compounds was able to describe qualitatively the pyrolysis of a trimeric lignin model compound containing both ..beta..-O-4 and ..alpha..-O-4 linkages.

  12. Minimal metabolic pathway structure is consistent with associated biomolecular interactions

    OpenAIRE

    Bordbar, Aarash; Nagarajan, Harish; Lewis, Nathan E.; Latif, Haythem; Ebrahim, Ali; Federowicz, Stephen; Schellenberger, Jan; Palsson, Bernhard

    2014-01-01

    Pathways are a universal paradigm for functionally describing cellular processes. Even though advances in high-throughput data generation have transformed biology, the core of our biological understanding, and hence data interpretation, is still predicated on human-defined pathways. Here, we introduce an unbiased, pathway structure for genome-scale metabolic networks defined based on principles of parsimony that do not mimic canonical human-defined textbook pathways. Instead, these minimal pa...

  13. Constructing Bio-molecular Databases on a DNA-based Computer

    CERN Document Server

    Chang, Weng-Long; Ho,; Guo, Minyi

    2007-01-01

    Codd [Codd 1970] wrote the first paper in which the model of a relational database was proposed. Adleman [Adleman 1994] wrote the first paper in which DNA strands in a test tube were used to solve an instance of the Hamiltonian path problem. From [Adleman 1994], it is obviously indicated that for storing information in molecules of DNA allows for an information density of approximately 1 bit per cubic nm (nanometer) and a dramatic improvement over existing storage media such as video tape which store information at a density of approximately 1 bit per 1012 cubic nanometers. This paper demonstrates that biological operations can be applied to construct bio-molecular databases where data records in relational tables are encoded as DNA strands. In order to achieve the goal, DNA algorithms are proposed to perform eight operations of relational algebra (calculus) on bio-molecular relational databases, which include Cartesian product, union, set difference, selection, projection, intersection, join and division. Fu...

  14. Micromachining microcarrier-based biomolecular encoding for miniaturized and multiplexed immunoassay.

    Science.gov (United States)

    Zhi, Zheng-liang; Morita, Yasutaka; Hasan, Quamrul; Tamiya, Eiichi

    2003-08-15

    Micromachining techniques, which originated in the microelectronics industry, have been employed to manufacture microparticles bearing an engraved dot-type signature for biomolecular encoding. These metallic microstructures are photolithographically defined and manufactured in a highly reproducible manner. In addition, the code introduced on the particle face is a straightforward visible feature that is easily recognizable with the use of optical microscopy. The number of distinct codes theoretically could be many thousands, depending on the coding element numbers. Such microparticles are, thus, with appropriate surface organic functionalizations, ideal for encoding biomolecular libraries and serving as a platform for developing high-throughput multiplexed bioassay schemes based on suspension array technology. As proof of this statement, we demonstrated that encoded microparticles tagged with antibodies to human immunoglobulin classes are capable, using imaging detection as the interrogating approach, of high sensitivity and high specificity, as well as multiplexed detection of the respective antigens in a microliter-sample volume. PMID:14651038

  15. PREFACE: India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation

    Science.gov (United States)

    Onoda, Mitsuyoshi; Malhotra, Bansi D.

    2012-04-01

    The 'India-Japan Workshop on Biomolecular Electronics & Organic Nanotechnology for Environment Preservation' (IJWBME 2011) will be held on 7-10 December 2011 at EGRET Himeji, Himeji, Hyogo, Japan. This workshop was held for the first time on 17-19 December 2009 at NPL, New Delhi. Keeping in mind the importance of organic nanotechnology and biomolecular electronics for environmental preservation and their anticipated impact on the economics of both the developing and the developed world, IJWBME 2009 was jointly organized by the Department of Biological Functions, Graduate School of Life Sciences and Systems Engineering, the Kyushu Institute of Technology (KIT), Kitakyushu, Japan, and the Department of Science & Technology Centre on Biomolecular Electronics (DSTCBE), National Physical Laboratory (NPL). Much progress in the field of biomolecular electronics and organic nanotechnology for environmental preservation is expected for the 21st Century. Organic optoelectronic devices, such as organic electroluminescent devices, organic thin-film transistors, organic sensors, biological systems and so on have especially attracted much attention. The main purpose of this workshop is to provide an opportunity for researchers interested in biomolecular electronics and organic nanotechnology for environmental preservation, to come together in an informal and friendly atmosphere and exchange technical knowledge and experience. We are sure that this workshop will be very useful and fruitful for all participants in summarizing the recent progress in biomolecular electronics and organic nanotechnology for environmental preservation and preparing new ground for the next generation. Many papers have been submitted from India and Japan and more than 30 papers have been accepted for presentation. The main topics of interest are as follows: Bioelectronics Biomolecular Electronics Fabrication Techniques Self-assembled Monolayers Nano-sensors Environmental Monitoring Organic Devices

  16. Effect of antibody modifications on its biomolecular binding as determined by surface plasmon resonance.

    Science.gov (United States)

    Vashist, Sandeep Kumar

    2012-02-01

    A surface plasmon resonance (SPR)-based procedure was developed to determine the effect of antibody modifications on its biomolecular binding behavior. Mouse immunoglobulin G (IgG) was immobilized on a protein A-functionalized gold-coated SPR chip. Goat anti-mouse IgG and its various commercially available modifications (i.e., conjugated with atto 550, atto 647, tetramethylrhodamine isothiocyanate [TRITC], horseradish peroxidase [HRP], or biotin) were employed in exactly the same concentration for the detection of mouse IgG. The various modifications of goat anti-mouse IgG decreased its biomolecular binding to mouse IgG in the order of unmodified>HRP-labeled>atto 550-labeled>biotinylated>TRITC-labeled>atto 647-labeled. PMID:22093612

  17. Use of pruned computational neural networks for processing the response of oscillating chemical reactions with a view to analyzing nonlinear multicomponent mixtures.

    Science.gov (United States)

    Hervás, C; Toledo, R; Silva, M

    2001-01-01

    The suitability of pruned computational neural networks (CNNs) for resolving nonlinear multicomponent systems involving synergistic effects by use of oscillating chemical reaction-based methods implemented using the analyte pulse perturbation technique is demonstrated. The CNN input data used for this purpose are estimates provided by the Levenberg-Marquardt method in the form of a three-parameter Gaussian curve associated with the singular profile obtained when the oscillating system is perturbed by an analyte mixture. The performance of the proposed method was assessed by applying it to the resolution of mixtures of pyrogallol and gallic acid based on their perturbating effect on a classical oscillating chemical system, viz. the Belousov-Zhabotinskyi reaction. A straightforward network topology (3:3:2, with 18 connections after pruning) allowed the resolution of mixtures of the two analytes in concentration ratios from 1:7 to 6:2 with a standard error of prediction for the testing set of 4.01 and 8.98% for pyrogallol and gallic acid, respectively. The reduced dimensions of the selected CNN architecture allowed a mathematical transformation of the input vector into the output one that can be easily implemented via software. Finally, the suitability of response surface analysis as an alternative to CNNs was also tested. The results were poor (relative errors were high), which confirms that properly selected pruned CNNs are effective tools for solving the analytical problem addressed in this work. PMID:11500128

  18. Classification of Modern and Old Río Tinto Sedimentary Deposits Through the Biomolecular Record Using a Life Marker Biochip: Implications for Detecting Life on Mars

    Science.gov (United States)

    Parro, Victor; Fernández-Remolar, David; Rodríguez-Manfredi, José A.; Cruz-Gil, Patricia; Rivas, Luis A.; Ruiz-Bermejo, Marta; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Gómez-Ortiz, David; Blanco-López, Yolanda; Menor-Salván, César; Prieto-Ballesteros, Olga; Gómez-Elvira, Javier

    2011-01-01

    The particular mineralogy formed in the acidic conditions of the Río Tinto has proven to be a first-order analogue for the acid-sulfate aqueous environments of Mars. Therefore, studies about the formation and preservation of biosignatures in the Río Tinto will provide insights into equivalent processes on Mars. We characterized the biomolecular patterns recorded in samples of modern and old fluvial sediments along a segment of the river by means of an antibody microarray containing more than 200 antibodies (LDCHIP200, for Life Detector Chip) against whole microorganisms, universal biomolecules, or environmental extracts. Samples containing 0.3-0.5g of solid material were automatically analyzed in situ by the Signs Of LIfe Detector instrument (SOLID2), and the results were corroborated by extensive analysis in the laboratory. Positive antigen-antibody reactions indicated the presence of microbial strains or high-molecular-weight biopolymers that originated from them. The LDCHIP200 results were quantified and subjected to a multivariate analysis for immunoprofiling. We associated similar immunopatterns, and biomolecular markers, to samples with similar sedimentary age. Phyllosilicate-rich samples from modern fluvial sediments gave strong positive reactions with antibodies against bacteria of the genus Acidithiobacillus and against biochemical extracts from Río Tinto sediments and biofilms. These samples contained high amounts of sugars (mostly polysaccharides) with monosaccharides like glucose, rhamnose, fucose, and so on. By contrast, the older deposits, which are a mix of clastic sands and evaporites, showed only a few positives with LDCHIP200, consistent with lower protein and sugar content. We conclude that LDCHIP200 results can establish a correlation between microenvironments, diagenetic stages, and age with the biomarker profile associated with a sample. Our results would help in the search for putative martian biomarkers in acidic deposits with similar

  19. Bridge- and Solvent-Mediated Intramolecular Electronic Communications in Ubiquinone-Based Biomolecular Wires

    OpenAIRE

    Liu, Xiao-Yuan; Ma, Wei; Zhou, Hao; Cao, Xiao-Ming; Long, Yi-Tao

    2015-01-01

    Intramolecular electronic communications of molecular wires play a crucial role for developing molecular devices. In the present work, we describe different degrees of intramolecular electronic communications in the redox processes of three ubiquinone-based biomolecular wires (Bis-CoQ0s) evaluated by electrochemistry and Density Functional Theory (DFT) methods in different solvents. We found that the bridges linkers have a significant effect on the electronic communications between the two pe...

  20. Extension of the GLYCAM06 Biomolecular Force Field to Lipids, Lipid Bilayers and Glycolipids

    OpenAIRE

    Tessier, Matthew B; DeMarco, Mari L.; Yongye, Austin B.; Woods, Robert J.

    2008-01-01

    GLYCAM06 is a generalisable biomolecular force field that is extendible to diverse molecular classes in the spirit of a small-molecule force field. Here we report parameters for lipids, lipid bilayers and glycolipids for use with GLYCAM06. Only three lipid-specific atom types have been introduced, in keeping with the general philosophy of transferable parameter development. Bond stretching, angle bending, and torsional force constants were derived by fitting to quantum mechanical data for a c...

  1. Atomic force microscopy of self-assembled biomolecular structures and their interaction with metallic nanoparticles.

    OpenAIRE

    Gysemans, Maarten

    2009-01-01

    We applied AFM to study biomolecular wires, both out of interest in thei r biological functions and in the framework of nanotechnology based fabr ication. We have focused on two different kinds of protein wires: Insuli n fibrils and microtubules. Microtubules are an important constituent of the cytoskeleton and fulfill multiple vital functions in the cell. Insu lin fibrils on the other hand are amyloid fibrils without a clear biolog ical role, but with intriguing polymerization properties tha...

  2. The Shadow Map: A General Contact Definition for Capturing the Dynamics of Biomolecular Folding and Function

    OpenAIRE

    Jeffrey K Noel; Whitford, Paul C.; Onuchic, José N.

    2012-01-01

    Structure-based models (SBMs) are simplified models of the biomolecular dynamics that arise from funneled energy landscapes. We recently introduced an all-atom SBM that explicitly represents the atomic geometry of a biomolecule. While this initial study showed the robustness of the all-atom SBM Hamiltonian to changes in many of the energetic parameters, an important aspect, which has not been explored previously, is the definition of native interactions. In this study, we propose a general de...

  3. A Review of Salam Phase Transition in Protein Amino Acids: Implication for Biomolecular Homochirality

    OpenAIRE

    Bai, Fan; Wang, Wenqing

    2002-01-01

    The origin of chirality, closely related to the evolution of life on the earth, has long been debated. In 1991, Abdus Salam suggested a novel approach to achieve biomolecular homochirality by a phase transition. In his subsequent publication, he predicted that this phase transition could eventually change D-amino acids to L-amino acids as C -H bond would break and H atom became a superconductive atom. Since many experiments denied the configuration change in amino acids, Salam hypothesis arou...

  4. Affinity capillary electrophoresis and density functional theory employed for characterization of (bio)molecular interactions

    Czech Academy of Sciences Publication Activity Database

    Kašička, Václav; Ehala, Sille; Růžička, Martin; Dybal, Jiří; Toman, Petr

    Salzburg: Society of Analytical Chemistry, 2014. OR28. [ISC 2014. International Symposium on Chromatography /30./. 14.09.2014-18.09.2014, Salzburg] R&D Projects: GA ČR(CZ) GAP206/12/0453; GA ČR(CZ) GA13-17224S Institutional support: RVO:61388963 ; RVO:61389013 Keywords : affinity capillary electrophoresis * density functional theory * biomolecular complexes Subject RIV: CB - Analytical Chemistry, Separation

  5. Interacting with the biomolecular solvent accessible surface via a haptic feedback device

    OpenAIRE

    Hayward Steven; Stocks Matthew B; Laycock Stephen D

    2009-01-01

    Abstract Background From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with mo...

  6. Biomolecular Self-Defense and Futility of High-Specificity Therapeutic Targeting

    OpenAIRE

    Simon Rosenfeld

    2011-01-01

    Robustness has been long recognized to be a distinctive property of living entities. While a reasonably wide consensus has been achieved regarding the conceptual meaning of robustness, the biomolecular mechanisms underlying this systemic property are still open to many unresolved questions. The goal of this paper is to provide an overview of existing approaches to characterization of robustness in mathematically sound terms. The concept of robustness is discussed in various contexts including...

  7. Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

    Science.gov (United States)

    Cole, Daniel J; Vilseck, Jonah Z; Tirado-Rives, Julian; Payne, Mike C; Jorgensen, William L

    2016-05-10

    Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme. PMID:27057643

  8. ssDNA-Functionalized Nanoceria: A Redox-Active Aptaswitch for Biomolecular Recognition.

    Science.gov (United States)

    Bülbül, Gonca; Hayat, Akhtar; Andreescu, Silvana

    2016-04-01

    Quantification of biomolecular binding events is a critical step for the development of biorecognition assays for diagnostics and therapeutic applications. This paper reports the design of redox-active switches based on aptamer conjugated nanoceria for detection and quantification of biomolecular recognition. It is shown that the conformational transition state of the aptamer on nanoceria, combined with the redox properties of these particles can be used to create surface based structure switchable aptasensing platforms. Changes in the redox properties at the nanoceria surface upon binding of the ssDNA and its target analyte enables rapid and highly sensitive measurement of biomolecular interactions. This concept is demonstrated as a general applicable method to the colorimetric detection of DNA binding events. An example of a nanoceria aptaswitch for the colorimetric sensing of Ochratoxin A (OTA) and applicability to other targets is provided. The system can sensitively and selectivity detect as low as 0.15 × 10(-9) m OTA. This novel assay is simple in design and does not involve oligonucleotide labeling or elaborate nanoparticle modification steps. The proposed mechanism discovered here opens up a new way of designing optical sensing methods based on aptamer recognition. This approach can be broadly applicable to many bimolecular recognition processes and related applications. PMID:26844813

  9. Multiresolution persistent homology for excessively large biomolecular datasets

    Science.gov (United States)

    Xia, Kelin; Zhao, Zhixiong; Wei, Guo-Wei

    2015-10-01

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

  10. Multiresolution persistent homology for excessively large biomolecular datasets

    International Nuclear Information System (INIS)

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs

  11. Multiresolution persistent homology for excessively large biomolecular datasets

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Kelin; Zhao, Zhixiong [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Wei, Guo-Wei, E-mail: wei@math.msu.edu [Department of Mathematics, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Electrical and Computer Engineering, Michigan State University, East Lansing, Michigan 48824 (United States); Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824 (United States)

    2015-10-07

    Although persistent homology has emerged as a promising tool for the topological simplification of complex data, it is computationally intractable for large datasets. We introduce multiresolution persistent homology to handle excessively large datasets. We match the resolution with the scale of interest so as to represent large scale datasets with appropriate resolution. We utilize flexibility-rigidity index to access the topological connectivity of the data set and define a rigidity density for the filtration analysis. By appropriately tuning the resolution of the rigidity density, we are able to focus the topological lens on the scale of interest. The proposed multiresolution topological analysis is validated by a hexagonal fractal image which has three distinct scales. We further demonstrate the proposed method for extracting topological fingerprints from DNA molecules. In particular, the topological persistence of a virus capsid with 273 780 atoms is successfully analyzed which would otherwise be inaccessible to the normal point cloud method and unreliable by using coarse-grained multiscale persistent homology. The proposed method has also been successfully applied to the protein domain classification, which is the first time that persistent homology is used for practical protein domain analysis, to our knowledge. The proposed multiresolution topological method has potential applications in arbitrary data sets, such as social networks, biological networks, and graphs.

  12. Formulation of a Network and the Study of Reaction Paths for the Sustainable Reduction of CO2 Emissions

    DEFF Research Database (Denmark)

    Frauzem, Rebecca; Kongpanna, Pichayapan; Roh, Kosan;

    , primarily greenhouse gas emissions. Of these, carbon dioxide (CO2) is the largest source and, hence, the reduction of the amount emitted is primary focus of developments [1]. A new and promising process that reduces the emissions is the conversion of CO2 into useful products, such as methanol and dimethyl......Various organizations, especially the Intergovernmental Panel on Climate Change, have stated that global warming is an ever-increasing threat to the environment and poses a problem if not addressed. Therefore, efforts are being made to find methods of reducing contributors to global warming...... carbonate (DMC) [2]. In this work, through a computer-aided framework for process network synthesis-design, a network of conversion processes that all use emitted CO2 is investigated. CO2 is emitted into the environment from various sources: power generation, industrial processes, transportation and...

  13. N,P-Codoped Carbon Networks as Efficient Metal-free Bifunctional Catalysts for Oxygen Reduction and Hydrogen Evolution Reactions.

    Science.gov (United States)

    Zhang, Jintao; Qu, Liangti; Shi, Gaoquan; Liu, Jiangyong; Chen, Jianfeng; Dai, Liming

    2016-02-01

    The high cost and scarcity of noble metal catalysts, such as Pt, have hindered the hydrogen production from electrochemical water splitting, the oxygen reduction in fuel cells and batteries. Herein, we developed a simple template-free approach to three-dimensional porous carbon networks codoped with nitrogen and phosphorus by pyrolysis of a supermolecular aggregate of self-assembled melamine, phytic acid, and graphene oxide (MPSA/GO). The pyrolyzed MPSA/GO acted as the first metal-free bifunctional catalyst with high activities for both oxygen reduction and hydrogen evolution. Zn-air batteries with the pyrolyzed MPSA/GO air electrode showed a high peak power density (310 W g(-1) ) and an excellent durability. Thus, the pyrolyzed MPSA/GO is a promising bifunctional catalyst for renewable energy technologies, particularly regenerative fuel cells. PMID:26709954

  14. Research on the Reaction Mechanism of Network Public Opinion Related to Procuratorate%涉检网络舆情反应机制研究

    Institute of Scientific and Technical Information of China (English)

    张亚力; 余芳

    2011-01-01

    新形势下的舆论环境要求检察机关提高处置网络舆情危机的能力。只有建立涉检网络舆情反应机制,敏锐地把握、驾驭应对舆论的能力,及时、坦诚地公开检务信息,才能培养人民群众对司法权威的认同感,提高检察工作的执法公信力,化解社会矛盾、维护社会和谐稳定。%Procuratorial organs are required to improve their abilities to deal with the crisis of network public opinion under the new situation. Only by establishing the reaction mechanism of network public opinion, mastering how to handle the public opinion keenly, opening the procuratorial information timely and frankly, people's sense of identity to judicial authority can be educated, the law enforcement credibility of procuratorial work can be improved, social contradictions can be defused, social harmony and stability can be maintained.

  15. Raman spectroscopy detects biomolecular changes associated with nanoencapsulated hesperetin treatment in experimental oral carcinogenesis

    Science.gov (United States)

    Gurushankar, K.; Gohulkumar, M.; Kumar, Piyush; Krishna, C. Murali; Krishnakumar, N.

    2016-03-01

    Recently it has been shown that Raman spectroscopy possesses great potential in the investigation of biomolecular changes of tumor tissues with therapeutic drug response in a non-invasive and label-free manner. The present study is designed to investigate the antitumor effect of hespertin-loaded nanoparticles (HETNPs) relative to the efficacy of native hesperetin (HET) in modifying the biomolecular changes during 7,12-dimethyl benz(a)anthracene (DMBA)-induced oral carcinogenesis using a Raman spectroscopic technique. Significant differences in the intensity and shape of the Raman spectra between the control and the experimental tissues at 1800-500 cm-1 were observed. Tumor tissues are characterized by an increase in the relative amount of proteins, nucleic acids, tryptophan and phenylalanine and a decrease in the percentage of lipids when compared to the control tissues. Further, oral administration of HET and its nanoparticulates restored the status of the lipids and significantly decreased the levels of protein and nucleic acid content. Treatment with HETNPs showed a more potent antitumor effect than treatment with native HET, which resulted in an overall reduction in the intensity of several biochemical Raman bands in DMBA-induced oral carcinogenesis being observed. Principal component and linear discriminant analysis (PC-LDA), together with leave-one-out cross validation (LOOCV) on Raman spectra yielded diagnostic sensitivities of 100%, 80%, 91.6% and 65% and specificities of 100%, 65%, 60% and 55% for classification of control versus DMBA, DMBA versus DMBA  +  HET, DMBA versus DMBA  +  HETNPs and DMBA  +  HET versus DMBA  +  HETNPs treated tissue groups, respectively. These results further demonstrate that Raman spectroscopy associated with multivariate statistical algorithms could be a valuable tool for developing a comprehensive understanding of the process of biomolecular changes, and could reveal the signatures of the

  16. Interacting with the biomolecular solvent accessible surface via a haptic feedback device

    Directory of Open Access Journals (Sweden)

    Hayward Steven

    2009-10-01

    Full Text Available Abstract Background From the 1950s computer based renderings of molecules have been produced to aid researchers in their understanding of biomolecular structure and function. A major consideration for any molecular graphics software is the ability to visualise the three dimensional structure of the molecule. Traditionally, this was accomplished via stereoscopic pairs of images and later realised with three dimensional display technologies. Using a haptic feedback device in combination with molecular graphics has the potential to enhance three dimensional visualisation. Although haptic feedback devices have been used to feel the interaction forces during molecular docking they have not been used explicitly as an aid to visualisation. Results A haptic rendering application for biomolecular visualisation has been developed that allows the user to gain three-dimensional awareness of the shape of a biomolecule. By using a water molecule as the probe, modelled as an oxygen atom having hard-sphere interactions with the biomolecule, the process of exploration has the further benefit of being able to determine regions on the molecular surface that are accessible to the solvent. This gives insight into how awkward it is for a water molecule to gain access to or escape from channels and cavities, indicating possible entropic bottlenecks. In the case of liver alcohol dehydrogenase bound to the inhibitor SAD, it was found that there is a channel just wide enough for a single water molecule to pass through. Placing the probe coincident with crystallographic water molecules suggests that they are sometimes located within small pockets that provide a sterically stable environment irrespective of hydrogen bonding considerations. Conclusion By using the software, named HaptiMol ISAS (available from http://www.haptimol.co.uk, one can explore the accessible surface of biomolecules using a three-dimensional input device to gain insights into the shape and water

  17. Dynamics of biomoleculars studied by Rayleigh scattering of Moessbauer radiation and Moessbauer spectroscopy

    International Nuclear Information System (INIS)

    This paper reports on dynamics of biomoleculars, proteins and DNA that plays a role in the supply and the regulation their functional activity, for example, like transducers of oxygen, like enzymes, in photosynthesis and so on. The Mossbauer spectroscopy (MS) and especially Rayleigh Scattering of Mossbauer Radiation (RSMR) permit to obtain the quantitative data on dimensions and times of complex hierarchy of motion in biopolymers and to create correspondent functional models. The scheme of RSMR includes Mossbauer source 57Co, the scatterer---biopolymer, the detector and Mossbauer analyzer (Black absorber---or one-line absorber), that situated before and after the scatterer on definite angle -2θ

  18. Surface-plasmon-enhanced fluorescence from periodic quantum dot arrays through distance control using biomolecular linkers

    International Nuclear Information System (INIS)

    We have developed a protein-enabled strategy to fabricate quantum dot (QD) nanoarrays where up to a 15-fold increase in surface-plasmon-enhanced fluorescence has been achieved. This approach permits a comprehensive control both laterally (via lithographically defined gold nanoarrays) and vertically (via the QD-metal distance) of the collectively behaving assemblies of QDs and gold nanoarrays by way of biomolecular recognition. Specifically, we demonstrated the spectral tuning of plasmon resonant metal nanoarrays and self-assembly of protein-functionalized QDs in a stepwise fashion with a concomitant incremental increase in separation from the metal surface through biotin-streptavidin spacer units.

  19. The use of gold nanoparticle aggregation for DNA computing and logic-based biomolecular detection

    Energy Technology Data Exchange (ETDEWEB)

    Lee, In-Hee; Yang, Kyung-Ae; Zhang, Byoung-Tak [School of Computer Science and Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Lee, Ji-Hoon [Center for Bioinformation Technology, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742 (Korea, Republic of); Park, Ji-Yoon; Chai, Young Gyu [Division of Molecular and Life Sciences, Hanyang University, 1271 Sa-dong, Sangnok-gu, Ansan, Gyeonggi-do 426-791 (Korea, Republic of); Lee, Jae-Hoon [Fachgebiet Mikrobiologie und Genetik, Institut fuer Biotechnologie, Technische Universitaet Berlin, Gustav-Meyer Allee 25, D-13355 Berlin (Germany)], E-mail: btzhang@bi.snu.ac.kr

    2008-10-01

    The use of DNA molecules as a physical computational material has attracted much interest, especially in the area of DNA computing. DNAs are also useful for logical control and analysis of biological systems if efficient visualization methods are available. Here we present a quick and simple visualization technique that displays the results of the DNA computing process based on a colorimetric change induced by gold nanoparticle aggregation, and we apply it to the logic-based detection of biomolecules. Our results demonstrate its effectiveness in both DNA-based logical computation and logic-based biomolecular detection.

  20. Effects of Clear Kefir on Biomolecular Aspects of Glycemic Status of Type 2 Diabetes Mellitus (T2DM Patients in Bandung, West Java [Study on Human Blood Glucose, c Peptide and Insulin

    Directory of Open Access Journals (Sweden)

    Judiono J

    2014-08-01

    Full Text Available Background: Diabetes Mellitus (DM triggers an excessive reaction of free-radicals. It increases reactive oxygen species and reduces antioxidants status as well as the β cell damage. Clear kefir was used for DM therapies, however it limited biomolecular exploration of its bioactive roles. Research aimed to investigate the effects of clear kefir on the biomolecular nature of the glycemic status of T2DM in Bandung. Methods: The randomized pretest-posttest control group was conducted by 106 T2DM patients. Research was done in several hospitals in Bandung and Cimahi, West Java from 2012–2013. Samples were divided randomly into three groups: (1 T2DM with HbA1c 7 fed standard diet and supplemented 200 ml/day by clear kefir, (3 T2DM with HbA1c was fed a standard diet as a control group. Dose response was obtained from a preeliminary vivo study, and then converted to human dosage by year 2011. Intervention was effectively done for 30 days. HbA1c was measured by HPLC. Fasting blood glucose (FBG and Postprandial blood glucose levels (PBG were measured by enzymes levels. C Peptide and insulin were measured by Elisa. Data was analyzed by a statictics programme by significance p<0,05. Study was approved by ethic committee. Results : HbA1c was significantly reduced in delta level (p<0.01 and FBG (p<0.015 among kefir groups. PBG was not significantly reduced among groups. C-Peptide was significantly increased in delta level, except in control group (p<0.014. Insulin was reduced significantly, except in control group (p<0.003. Conclusions : Supplementation of clear kefir reduced blood glucose levels (HbA1c, FBG, PBG and increased c-peptide. Clear kefir’s biomolecular mechanisms and chemistry characterization is a challenge for future studies.

  1. Dynamics of simple gene-network motifs subject to extrinsic fluctuations

    Science.gov (United States)

    Roberts, Elijah; Be'er, Shay; Bohrer, Chris; Sharma, Rati; Assaf, Michael

    2015-12-01

    Cellular processes do not follow deterministic rules; even in identical environments genetically identical cells can make random choices leading to different phenotypes. This randomness originates from fluctuations present in the biomolecular interaction networks. Most previous work has been focused on the intrinsic noise (IN) of these networks. Yet, especially for high-copy-number biomolecules, extrinsic or environmental noise (EN) has been experimentally shown to dominate the variation. Here, we develop an analytical formalism that allows for calculation of the effect of EN on gene-expression motifs. We introduce a method for modeling bounded EN as an auxiliary species in the master equation. The method is fully generic and is not limited to systems with small EN magnitudes. We focus our study on motifs that can be viewed as the building blocks of genetic switches: a nonregulated gene, a self-inhibiting gene, and a self-promoting gene. The role of the EN properties (magnitude, correlation time, and distribution) on the statistics of interest are systematically investigated, and the effect of fluctuations in different reaction rates is compared. Due to its analytical nature, our formalism can be used to quantify the effect of EN on the dynamics of biochemical networks and can also be used to improve the interpretation of data from single-cell gene-expression experiments.

  2. Spatially encoded strategies in the execution of biomolecular-oriented 3D NMR experiments

    International Nuclear Information System (INIS)

    Three-dimensional nuclear magnetic resonance (3D NMR) provides one of the foremost analytical tools available for the elucidation of biomolecular structure, function and dynamics. Executing a 3D NMR experiment generally involves scanning a series of time-domain signals S(t3), as a function of two time variables (t1, t2) which need to undergo parametric incrementations throughout independent experiments. Recent years have witnessed extensive efforts towards the acceleration of this kind of experiments. Among the different approaches that have been proposed counts an 'ultrafast' scheme, which distinguishes itself from other propositions by enabling-at least in principle-the acquisition of the complete multidimensional NMR data set within a single transient. 2D protein NMR implementations of this single-scan method have been demonstrated, yet its potential for 3D acquisitions has only been exemplified on model organic compounds. This publication discusses a number of strategies that could make these spatial encoding protocols compatible with 3D biomolecular NMR applications. These include a merging of 2D ultrafast NMR principles with temporal 2D encoding schemes, which can yield 3D HNCO spectra from peptides and proteins within ∼100 s timescales. New processing issues that facilitate the collection of 3D NMR spectra by relying fully on spatial encoding principles are also assessed, and shown capable of delivering HNCO spectra within 1 s timescales. Limitations and prospects of these various schemes are briefly addressed

  3. DockScreen: A Database of In Silico Biomolecular Interactions to Support Computational Toxicology

    Directory of Open Access Journals (Sweden)

    Michael-Rock Goldsmith

    2014-01-01

    Full Text Available We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme binding scores calculated by molecular docking of more than 1000 chemicals into 150 protein targets and contains nearly 135 thousand unique ligand/target binding scores. Obtaining this dataset was achieved using eHiTS (Simbiosys Inc., a fragment-based molecular docking approach with an exhaustive search algorithm, on a heterogeneous distributed high-performance computing framework. The chemical landscape covered in DockScreen comprises selected environmental and therapeutic chemicals. The target landscape covered in DockScreen was selected based on the availability of high-quality crystal structures that covered the assay space of phase I ToxCast in vitro assays. This in silico data provides continuous information that establishes a means for quantitatively comparing, on a structural biophysical basis, a chemical’s profile of biomolecular interactions. The combined minimum-score chemical/target matrix is provided.

  4. X3DBio2: A visual analysis tool for biomolecular structure comparison

    Science.gov (United States)

    Yi, Hong; Thakur, Sidharth; Sethaphong, Latsavongsakda; Yingling, Yaroslava G.

    2013-01-01

    A major problem in structural biology is the recognition of differences and similarities between related three dimensional (3D) biomolecular structures. Investigating these structure relationships is important not only for understanding of functional properties of biologically significant molecules, but also for development of new and improved materials based on naturally-occurring molecules. We developed a new visual analysis tool, X3DBio2, for 3D biomolecular structure comparison and analysis. The tool is designed for elucidation of structural effects of mutations in proteins and nucleic acids and for assessment of time dependent trajectories from molecular dynamics simulations. X3DBio2 is a freely downloadable open source software and provides tightly integrated features to perform many standard analysis and visual exploration tasks. We expect this tool can be applied to solve a variety of biological problems and illustrate the use of the tool on the example study of the differences and similarities between two proteins of the glycosyltransferase family 2 that synthesize polysaccharides oligomers. The size and conformational distances and retained core structural similarity of proteins SpsA to K4CP represent significant epochs in the evolution of inverting glycosyltransferases.

  5. The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

    Science.gov (United States)

    van Zundert, G C P; Rodrigues, J P G L M; Trellet, M; Schmitz, C; Kastritis, P L; Karaca, E; Melquiond, A S J; van Dijk, M; de Vries, S J; Bonvin, A M J J

    2016-02-22

    The prediction of the quaternary structure of biomolecular macromolecules is of paramount importance for fundamental understanding of cellular processes and drug design. In the era of integrative structural biology, one way of increasing the accuracy of modeling methods used to predict the structure of biomolecular complexes is to include as much experimental or predictive information as possible in the process. This has been at the core of our information-driven docking approach HADDOCK. We present here the updated version 2.2 of the HADDOCK portal, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface. With well over 6000 registered users and 108,000 jobs served, an increasing fraction of which on grid resources, we hope that this timely upgrade will help the community to solve important biological questions and further advance the field. The HADDOCK2.2 Web server is freely accessible to non-profit users at http://haddock.science.uu.nl/services/HADDOCK2.2. PMID:26410586

  6. Optimizing water hyperpolarization and dissolution for sensitivity-enhanced 2D biomolecular NMR

    Science.gov (United States)

    Olsen, Greg; Markhasin, Evgeny; Szekely, Or; Bretschneider, Christian; Frydman, Lucio

    2016-03-01

    A recent study explored the use of hyperpolarized water, to enhance the sensitivity of nuclei in biomolecules thanks to rapid proton exchanges with labile amide backbone and sidechain groups. Further optimizations of this approach have now allowed us to achieve proton polarizations approaching 25% in the water transferred into the NMR spectrometer, effective water T1 times approaching 40 s, and a reduction in the dilution demanded for the cryogenic dissolution process. Further hardware developments have allowed us to perform these experiments, repeatedly and reliably, in 5 mm NMR tubes. All these ingredients - particularly the ⩾3000× 1H polarization enhancements over 11.7 T thermal counterparts, long T1 times and a compatibility with high-resolution biomolecular NMR setups - augur well for hyperpolarized 2D NMR studies of peptides, unfolded proteins and intrinsically disordered systems undergoing fast exchanges of their protons with the solvent. This hypothesis is here explored by detailing the provisions that lead to these significant improvements over previous reports, and demonstrating 1D coherence transfer experiments and 2D biomolecular HMQC acquisitions delivering NMR spectral enhancements of 100-500× over their optimized, thermally-polarized, counterparts.

  7. Group transfer theory of single molecule imaging experiments in the F-ATPase biomolecular motor

    Science.gov (United States)

    Volkan-Kacso, Sandor; Marcus, Rudolph

    I describe a chemo-mechanical theory to treat single molecule imaging and ``stalling'' experiments on the F-ATPase enzyme. This enzyme is an effective stepping biomolecular rotary motor with a rotor shaft and a stator ring. Using group transfer theoretical approach the proposed structure-based theory couples the binding transition of nucleotides in the stator subunits and the physics of torsional elasticity in the rotor. The twisting of the elastic rotor domain acts as a perturbation upon the driving potential, the Gibbs free energy. In the theory, without the use of adjustastable parameters, we predict the rate and equilibrium constant dependence of steps such as ATP binding and phosphate release as a function of manipulated rotor angle. Then we compare these predictions to available data from stalling experiments. Besides treating experiments, the theory can provide guides for atomistic simulations, which could calculate the reorganization parameter and the torsional spring constant. The framework is generic and I discuss its application to other single molecule experiments, such as controlled rotation and other biomolecular motors, including motor-DNA complexes and linear motors.[PNAS, Early Edition, Oct. 19, 2015, doi: 10.1073/pnas.1518489112

  8. Assessment of nitric oxide (NO) redox reactions contribution to nitrous oxide (N2 O) formation during nitrification using a multispecies metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Chandran, Kartik; Villas-Boas, Silas G; Singhal, Naresh

    2016-05-01

    Over the coming decades nitrous oxide (N2O) is expected to become a dominant greenhouse gas and atmospheric ozone depleting substance. In wastewater treatment systems, N2O is majorly produced by nitrifying microbes through biochemical reduction of nitrite (NO2(-)) and nitric oxide (NO). However it is unknown if the amount of N2O formed is affected by alternative NO redox reactions catalyzed by oxidative nitrite oxidoreductase (NirK), cytochromes (i.e., P460 [CytP460] and 554 [Cyt554 ]) and flavohemoglobins (Hmp) in ammonia- and nitrite-oxidizing bacteria (AOB and NOB, respectively). In this study, a mathematical model is developed to assess how N2O formation is affected by such alternative nitrogen redox transformations. The developed multispecies metabolic network model captures the nitrogen respiratory pathways inferred from genomes of eight AOB and NOB species. The performance of model variants, obtained as different combinations of active NO redox reactions, was assessed against nine experimental datasets for nitrifying cultures producing N2O at different concentration of electron donor and acceptor. Model predicted metabolic fluxes show that only variants that included NO oxidation to NO2(-) by CytP460 and Hmp in AOB gave statistically similar estimates to observed production rates of N2O, NO, NO2(-) and nitrate (NO3(-)), together with fractions of AOB and NOB species in biomass. Simulations showed that NO oxidation to NO2(-) decreased N2O formation by 60% without changing culture's NO2(-) production rate. Model variants including NO reduction to N2O by Cyt554 and cNor in NOB did not improve the accuracy of experimental datasets estimates, suggesting null N2O production by NOB during nitrification. Finally, the analysis shows that in nitrifying cultures transitioning from dissolved oxygen levels above 3.8 ± 0.38 to <1.5 ± 0.8 mg/L, NOB cells can oxidize the NO produced by AOB through reactions catalyzed by oxidative NirK. PMID:26551878

  9. Biomolecular motors

    Directory of Open Access Journals (Sweden)

    Henry Hess

    2005-12-01

    Here, we give a brief introduction to molecular motors, with an emphasis on motor proteins, describe the challenges in interfacing these bionanomachines with an artificial environment, and provide examples of emerging applications.

  10. Electrochemical sensor for multiplex screening of genetically modified DNA: identification of biotech crops by logic-based biomolecular analysis.

    Science.gov (United States)

    Liao, Wei-Ching; Chuang, Min-Chieh; Ho, Ja-An Annie

    2013-12-15

    Genetically modified (GM) technique, one of the modern biomolecular engineering technologies, has been deemed as profitable strategy to fight against global starvation. Yet rapid and reliable analytical method is deficient to evaluate the quality and potential risk of such resulting GM products. We herein present a biomolecular analytical system constructed with distinct biochemical activities to expedite the computational detection of genetically modified organisms (GMOs). The computational mechanism provides an alternative to the complex procedures commonly involved in the screening of GMOs. Given that the bioanalytical system is capable of processing promoter, coding and species genes, affirmative interpretations succeed to identify specified GM event in terms of both electrochemical and optical fashions. The biomolecular computational assay exhibits detection capability of genetically modified DNA below sub-nanomolar level and is found interference-free by abundant coexistence of non-GM DNA. This bioanalytical system, furthermore, sophisticates in array fashion operating multiplex screening against variable GM events. Such a biomolecular computational assay and biosensor holds great promise for rapid, cost-effective, and high-fidelity screening of GMO. PMID:23893064

  11. Small-angle X-ray scattering investigations of biomolecular confinement, loading, and release from liquid-crystalline nanochannel assemblies

    Czech Academy of Sciences Publication Activity Database

    Angelova, A.; Angelov, Borislav; Garamus, V. M.; Couvreur, P.; Lesieur, S.

    2012-01-01

    Roč. 3, č. 3 (2012), s. 445-457. ISSN 1948-7185 Institutional research plan: CEZ:AV0Z40500505 Keywords : nanochannels * biomolecular nanostructures * SAXS Subject RIV: CD - Macromolecular Chemistry Impact factor: 6.585, year: 2012

  12. Investigation of the Human Disease Osteogenesis Imperfecta: A Research-Based Introduction to Concepts and Skills in Biomolecular Analysis

    Science.gov (United States)

    Mate, Karen; Sim, Alistair; Weidenhofer, Judith; Milward, Liz; Scott, Judith

    2013-01-01

    A blended approach encompassing problem-based learning (PBL) and structured inquiry was used in this laboratory exercise based on the congenital disease Osteogenesis imperfecta (OI), to introduce commonly used techniques in biomolecular analysis within a clinical context. During a series of PBL sessions students were presented with several…

  13. Biosensors with Built-In Biomolecular Logic Gates for Practical Applications

    Directory of Open Access Journals (Sweden)

    Yu-Hsuan Lai

    2014-08-01

    Full Text Available Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems.

  14. Biomolecular papain thin films grown by matrix assisted and conventional pulsed laser deposition: A comparative study

    Science.gov (United States)

    György, E.; Pérez del Pino, A.; Sauthier, G.; Figueras, A.

    2009-12-01

    Biomolecular papain thin films were grown both by matrix assisted pulsed laser evaporation (MAPLE) and conventional pulsed laser deposition (PLD) techniques with the aid of an UV KrF∗ (λ =248 nm, τFWHM≅20 ns) excimer laser source. For the MAPLE experiments the targets submitted to laser radiation consisted on frozen composites obtained by dissolving the biomaterial powder in distilled water at 10 wt % concentration. Conventional pressed biomaterial powder targets were used in the PLD experiments. The surface morphology of the obtained thin films was studied by atomic force microscopy and their structure and composition were investigated by Fourier transform infrared spectroscopy. The possible physical mechanisms implied in the ablation processes of the two techniques, under comparable experimental conditions were identified. The results showed that the growth mode, surface morphology as well as structure of the deposited biomaterial thin films are determined both by the incident laser fluence value as well as target preparation procedure.

  15. Biomolecular Electrostatics Simulation by an FMM-based BEM on 512 GPUs

    CERN Document Server

    Yokota, Rio; Bardhan, Jaydeep P; Knepley, Matthew G; Barba, L A

    2010-01-01

    We present simulations of biomolecular electrostatics at a scale not reached before, thanks to both algorithmic and hardware acceleration. The algorithmic acceleration is achieved with the fast multipole method (FMM) in conjunction with a boundary element method (BEM) formulation of the continuum electrostatic model. The hardware acceleration is achieved through graphics processors, GPUs. We demonstrate the power of our algorithms and software for the calculation of the electrostatic interactions between biological molecules in solution. Computational experiments are presented simulating the electrostatics of protein--drug binding and several multi-million atom systems consisting of hundreds to thousands of copies of the problems, which models over 20 million atoms and has more than six billion unknowns, one iteration step requires only a few minutes on 512 GPU nodes. We achieved a sustained performance of 34.6TFlops for the entire BEM calculation. We are currently adapting our solver to model the linearized ...

  16. Conformation of bovine submaxillary mucin layers on hydrophobic surface as studied by biomolecular probes

    DEFF Research Database (Denmark)

    Pakkanen, Kirsi I.; Madsen, Jan Busk; Lee, Seunghwan

    2015-01-01

    In the present study, the conformational changes of bovine submaxillary mucin (BSM) adsorbed on a hydrophobic surface (polystyrene (PS)) as a function of concentration in bulk solution (up to 2mg/mL) have been investigated with biomolecular probe-based approaches, including bicinchoninic acid (BCA...... solution. Adsorbed masses of BSM onto hydrophobic surface, as probe by BCA, showed a continuously increasing trend up to 2mg/mL. But, the signals from EIA and ELLA, which probe the concentration of available unglycosylatedC-terminals and the central glycosylated regions, respectively, showed complicated......),enzyme-linkedimmunosorbentassay(EIA),andenzyme linkedlectinassay(ELLA).Theconformationand hydrodynamic diameter of highly purified BSM molecules, as characterized by circular dichroism (CD) spectroscopy and dynamic light scattering (DLS), respectively, showed a slight, yet gradual coiling and compaction in response to the increase in BSM concentration in bulk...

  17. Biomolecular ion detection using high-temperature superconducting MgB2 strips

    Science.gov (United States)

    Zen, N.; Shibata, H.; Mawatari, Y.; Koike, M.; Ohkubo, M.

    2015-06-01

    Superconducting strip ion detectors (SSIDs) are promising for realization of ideal ion detection with 100% efficiency and nanosecond-scale time response in time-of-flight mass spectrometry. We have detected single biomolecular ions in the keV range using a 10-nm-thick and 250-nm-wide strip of a high temperature superconductor, magnesium diboride (MgB2), at temperatures of up to 13 K. The output pulse shape is explained remarkably well using circuit simulations and time-dependent Ginzburg-Landau simulations coupled with a heat diffusion equation. The simulations show that the hot spot model is applicable to the proposed MgB2-SSIDs and the normal region expansion is completed within 16 ps, which corresponds to a maximum length of 1010 nm.

  18. Overcoming the solubility limit with solubility-enhancement tags: successful applications in biomolecular NMR studies

    International Nuclear Information System (INIS)

    Although the rapid progress of NMR technology has significantly expanded the range of NMR-trackable systems, preparation of NMR-suitable samples that are highly soluble and stable remains a bottleneck for studies of many biological systems. The application of solubility-enhancement tags (SETs) has been highly effective in overcoming solubility and sample stability issues and has enabled structural studies of important biological systems previously deemed unapproachable by solution NMR techniques. In this review, we provide a brief survey of the development and successful applications of the SET strategy in biomolecular NMR. We also comment on the criteria for choosing optimal SETs, such as for differently charged target proteins, and recent new developments on NMR-invisible SETs.

  19. Advances in biomolecular surface meshing and its applications to mathematical modeling

    Institute of Scientific and Technical Information of China (English)

    CHEN MinXin; LU BenZhuo

    2013-01-01

    In the field of molecular modeling and simulation,molecular surface meshes are necessary for many problems,such as molecular structure visualization and analysis,docking problem and implicit solvent modeling and simulation.Recently,with the developments of advanced mathematical modeling in the field of implicit solvent modeling and simulation,providing surface meshes with good qualities efficiently for large real biomolecular systems becomes an urgent issue beyond its traditional purposes for visualization and geometry analyses for molecular structure.In this review,we summarize recent works on this issue.First,various definitions of molecular surfaces and corresponding meshing methods are introduced.Second,our recent meshing tool,TMSmesh,and its performances are presented.Finally,we show the applications of the molecular surface mesh in implicit solvent modeling and simulations using boundary element method (BEM) and finite element method (FEM).

  20. Piezoelectric tuning fork biosensors for the quantitative measurement of biomolecular interactions

    Science.gov (United States)

    Gonzalez, Laura; Rodrigues, Mafalda; Benito, Angel Maria; Pérez-García, Lluïsa; Puig-Vidal, Manel; Otero, Jorge

    2015-12-01

    The quantitative measurement of biomolecular interactions is of great interest in molecular biology. Atomic force microscopy (AFM) has proved its capacity to act as a biosensor and determine the affinity between biomolecules of interest. Nevertheless, the detection scheme presents certain limitations when it comes to developing a compact biosensor. Recently, piezoelectric quartz tuning forks (QTFs) have been used as laser-free detection sensors for AFM. However, only a few studies along these lines have considered soft biological samples, and even fewer constitute quantified molecular recognition experiments. Here, we demonstrate the capacity of QTF probes to perform specific interaction measurements between biotin-streptavidin complexes in buffer solution. We propose in this paper a variant of dynamic force spectroscopy based on representing adhesion energies E (aJ) against pulling rates v (nm s-1). Our results are compared with conventional AFM measurements and show the great potential of these sensors in molecular interaction studies.

  1. Amplified vibrational circular dichroism as a probe of local biomolecular structure.

    Science.gov (United States)

    Domingos, Sérgio R; Huerta-Viga, Adriana; Baij, Lambert; Amirjalayer, Saeed; Dunnebier, Dorien A E; Walters, Annemarie J C; Finger, Markus; Nafie, Laurence A; de Bruin, Bas; Buma, Wybren Jan; Woutersen, Sander

    2014-03-01

    We show that the VCD signal intensities of amino acids and oligopeptides can be enhanced by up to 2 orders of magnitude by coupling them to a paramagnetic metal ion. If the redox state of the metal ion is changed from paramagnetic to diamagnetic the VCD amplification vanishes completely. From this observation and from complementary quantum-chemical calculations we conclude that the observed VCD amplification finds its origin in vibronic coupling with low-lying electronic states. We find that the enhancement factor is strongly mode dependent and that it is determined by the distance between the oscillator and the paramagnetic metal ion. This localized character of the VCD amplification provides a unique tool to specifically probe the local structure surrounding a paramagnetic ion and to zoom in on such local structure within larger biomolecular systems. PMID:24506134

  2. Overcoming the solubility limit with solubility-enhancement tags: successful applications in biomolecular NMR studies.

    Science.gov (United States)

    Zhou, Pei; Wagner, Gerhard

    2010-01-01

    Although the rapid progress of NMR technology has significantly expanded the range of NMR-trackable systems, preparation of NMR-suitable samples that are highly soluble and stable remains a bottleneck for studies of many biological systems. The application of solubility-enhancement tags (SETs) has been highly effective in overcoming solubility and sample stability issues and has enabled structural studies of important biological systems previously deemed unapproachable by solution NMR techniques. In this review, we provide a brief survey of the development and successful applications of the SET strategy in biomolecular NMR.We also comment on the criteria for choosing optimal SETs, such as for differently charged target proteins, and recent new developments on NMR-invisible SETs. PMID:19731047

  3. A program to calculate non-bonded interaction energy in biomolecular aggregates.

    Science.gov (United States)

    Sundaram, K; Prasad, C V

    1982-02-01

    This paper describes a program to calculate intermolecular as well as intramolecular electronic potential energy resulting from non-bonded interactions. The underlying theory is obtained by the application of Rayleigh-Schroedinger perturbation theory to non-overlap regions of a molecular system. The rigorous theoretical expressions for the energy terms are simplified by approximations consistent with those commonly employed in semi-empirical molecular orbital theories. The program is particularly suited for the study of biomolecular assemblies, and in situations where insight into contributions to total energy from various component interaction types is desired. The inclusion of the non-additive dispersion effects in this approach makes it especially interesting for the study of cooperative phenomena in the light of a recent finding [1]. PMID:7067416

  4. ACEMD: Accelerating bio-molecular dynamics in the microsecond time-scale

    CERN Document Server

    Harvey, M J; De Fabritiis, G

    2009-01-01

    The high arithmetic performance and intrinsic parallelism of recent graphical processing units (GPUs) can offer a technological edge for molecular dynamics simulations. ACEMD is a production-class bio-molecular dynamics (MD) simulation program designed specifically for GPUs which is able to achieve supercomputing scale performance of 40 nanoseconds/day for all-atom protein systems with over 23,000 atoms. We illustrate the characteristics of the code, its validation and performance. We also run a microsecond-long trajectory for an all-atom molecular system in explicit TIP3P water on a single workstation computer equipped with just 3 GPUs. This performance on cost effective hardware allows ACEMD to reach microsecond timescales routinely with important implications in terms of scientific applications.

  5. A Review of Salam Phase Transition in Protein Amino Acids Implication for Biomolecular Homochirality

    CERN Document Server

    Bai, F; Bai, Fan; Wang, Wenqing

    2002-01-01

    The origin of chirality, closely related to the evolution of life on the earth, has long been debated. In 1991, Abdus Salam suggested a novel approach to achieve biomolecular homochirality by a phase transition. In his subsequent publication, he predicted that this phase transition could eventually change D-amino acids to L-amino acids as C -H bond would break and H atom became a superconductive atom. Since many experiments denied the configuration change in amino acids, Salam hypothesis aroused suspicion. This paper is aimed to provide direct experimental evidence of a phase transition in alanine, valine single crystals but deny the configuration change of D- to L- enantiomers. New views on Salam phase transition are presented to revalidate its great importance in the origin of homochirality.

  6. Astronomy with Radioactivities: Chapter 9, Nuclear Reactions

    OpenAIRE

    Wiescher, M.; Rauscher, T.

    2010-01-01

    Nuclear reaction rates determine the abundances of isotopes in stellar burning processes. A multitude of reactions determine the reaction flow pattern which is described in terms of reaction network simulations. The reaction rates are determined by laboratory experiments supplemented by nuclear reaction and structure theory. We will discuss the experimental approach as well as the theoretical tools for obtaining the stellar reaction rates. A detailed analysis of a reaction is only possible fo...

  7. Biomolecular Characterization of Diazotrophs Isolated from the Tropical Soil in Malaysia

    Directory of Open Access Journals (Sweden)

    Zulkifli H Shamsuddin

    2013-08-01

    Full Text Available This study was conducted to evaluate selected biomolecular characteristics of rice root-associated diazotrophs isolated from the Tanjong Karang rice irrigation project area of Malaysia. Soil and rice plant samples were collected from seven soil series belonging to order Inceptisol (USDA soil taxonomy. A total of 38 diazotrophs were isolated using a nitrogen-free medium. The biochemical properties of the isolated bacteria, such as nitrogenase activity, indoleacetic acid (IAA production and sugar utilization, were measured. According to a cluster analysis of Jaccard’s similarity coefficients, the genetic similarities among the isolated diazotrophs ranged from 10% to 100%. A dendogram constructed using the unweighted pair-group method with arithmetic mean (UPGMA showed that the isolated diazotrophs clustered into 12 groups. The genomic DNA rep-PCR data were subjected to a principal component analysis, and the first four principal components (PC accounted for 52.46% of the total variation among the 38 diazotrophs. The 10 diazotrophs that tested highly positive in the acetylene reduction assay (ARA were identified as Bacillus spp. (9 diazotrophs and Burkholderia sp. (Sb16 using the partial 16S rRNA gene sequence analysis. In the analysis of the biochemical characteristics, three principal components were accounted for approximately 85% of the total variation among the identified diazotrophs. The examination of root colonization using scanning electron microscopy (SEM and transmission electron microscopy (TEM proved that two of the isolated diazotrophs (Sb16 and Sb26 were able to colonize the surface and interior of rice roots and fixed 22%–24% of the total tissue nitrogen from the atmosphere. In general, the tropical soils (Inceptisols of the Tanjong Karang rice irrigation project area in Malaysia harbor a diverse group of diazotrophs that exhibit a large variation of biomolecular characteristics.

  8. Versatile single-molecule multi-color excitation and detection fluorescence setup for studying biomolecular dynamics

    KAUST Repository

    Sobhy, M. A.

    2011-11-07

    Single-molecule fluorescence imaging is at the forefront of tools applied to study biomolecular dynamics both in vitro and in vivo. The ability of the single-molecule fluorescence microscope to conduct simultaneous multi-color excitation and detection is a key experimental feature that is under continuous development. In this paper, we describe in detail the design and the construction of a sophisticated and versatile multi-color excitation and emission fluorescence instrument for studying biomolecular dynamics at the single-molecule level. The setup is novel, economical and compact, where two inverted microscopes share a laser combiner module with six individual laser sources that extend from 400 to 640 nm. Nonetheless, each microscope can independently and in a flexible manner select the combinations, sequences, and intensities of the excitation wavelengths. This high flexibility is achieved by the replacement of conventional mechanical shutters with acousto-optic tunable filter (AOTF). The use of AOTF provides major advancement by controlling the intensities, duration, and selection of up to eight different wavelengths with microsecond alternation time in a transparent and easy manner for the end user. To our knowledge this is the first time AOTF is applied to wide-field total internal reflection fluorescence (TIRF) microscopy even though it has been commonly used in multi-wavelength confocal microscopy. The laser outputs from the combiner module are coupled to the microscopes by two sets of four single-mode optic fibers in order to allow for the optimization of the TIRF angle for each wavelength independently. The emission is split into two or four spectral channels to allow for the simultaneous detection of up to four different fluorophores of wide selection and using many possible excitation and photoactivation schemes. We demonstrate the performance of this new setup by conducting two-color alternating excitation single-molecule fluorescence resonance energy

  9. A New Selective Neural Network Ensemble Method Based on Error Vectorization and Its Application in High-density Polyethylene (HDPE) Cascade Reaction Process%A New Selective Neural Network Ensemble Method Based on Error Vectorization and Its Application in High-density Polyethylene (HDPE) Cascade Reaction Process

    Institute of Scientific and Technical Information of China (English)

    朱群雄; 赵乃伟; 徐圆

    2012-01-01

    Chemical processes are complex, for which traditional neural network models usually can not lead to satisfactory accuracy. Selective neural network ensemble is an effective way to enhance the generalization accuracy of networks, but there are some problems, e.g., lacking of unified definition of diversity among component neural networks and difficult to improve the accuracy by selecting if the diversities of available networks are small. In this study, the output errors of networks are vectorized, the diversity of networks is defined based on the error vectors, and the size of ensemble is analyzed. Then an error vectorization based selective neural network ensemble (EVSNE) is proposed, in which the error vector of each network can offset that of the other networks by training the component networks orderly. Thus the component networks have large diversity. Experiments and comparisons over standard data sets and actual chemical process data set for production of high-density polyethylene demonstrate that EVSNE performs better in generalization ability.

  10. Detection and kinetic studies of triplex formation by oligodeoxynucleotides using real-time biomolecular interaction analysis (BIA).

    OpenAIRE

    Bates, P. J.; Dosanjh, H. S.; S. Kumar; Jenkins, T. C.; Laughton, C A; Neidle, S

    1995-01-01

    Real-time biomolecular interaction analysis (BIA) has been applied to triplex formation between oligodeoxynucleotides. 5'-Biotinylated oligonucleotides were immobilised on the streptavidin-coated surface of a biosensor chip and subsequently hybridised to their complementary strand. Sequence-specific triplex formation was observed when a suitable third-strand oligopyrimidine was injected over the surface-bound duplex. In addition, a single-stranded oligonucleotide immobilised on the chip surfa...

  11. Phase sensitive spectral domain interferometry for label free biomolecular interaction analysis and biosensing applications

    Science.gov (United States)

    Chirvi, Sajal

    Biomolecular interaction analysis (BIA) plays vital role in wide variety of fields, which include biomedical research, pharmaceutical industry, medical diagnostics, and biotechnology industry. Study and quantification of interactions between natural biomolecules (proteins, enzymes, DNA) and artificially synthesized molecules (drugs) is routinely done using various labeled and label-free BIA techniques. Labeled BIA (Chemiluminescence, Fluorescence, Radioactive) techniques suffer from steric hindrance of labels on interaction site, difficulty of attaching labels to molecules, higher cost and time of assay development. Label free techniques with real time detection capabilities have demonstrated advantages over traditional labeled techniques. The gold standard for label free BIA is surface Plasmon resonance (SPR) that detects and quantifies the changes in refractive index of the ligand-analyte complex molecule with high sensitivity. Although SPR is a highly sensitive BIA technique, it requires custom-made sensor chips and is not well suited for highly multiplexed BIA required in high throughput applications. Moreover implementation of SPR on various biosensing platforms is limited. In this research work spectral domain phase sensitive interferometry (SD-PSI) has been developed for label-free BIA and biosensing applications to address limitations of SPR and other label free techniques. One distinct advantage of SD-PSI compared to other label-free techniques is that it does not require use of custom fabricated biosensor substrates. Laboratory grade, off-the-shelf glass or plastic substrates of suitable thickness with proper surface functionalization are used as biosensor chips. SD-PSI is tested on four separate BIA and biosensing platforms, which include multi-well plate, flow cell, fiber probe with integrated optics and fiber tip biosensor. Sensitivity of 33 ng/ml for anti-IgG is achieved using multi-well platform. Principle of coherence multiplexing for multi

  12. Transient assembly of active materials fueled by a chemical reaction

    Science.gov (United States)

    Boekhoven, Job; Hendriksen, Wouter E.; Koper, Ger J. M.; Eelkema, Rienk; van Esch, Jan H.

    2015-09-01

    Fuel-driven self-assembly of actin filaments and microtubules is a key component of cellular organization. Continuous energy supply maintains these transient biomolecular assemblies far from thermodynamic equilibrium, unlike typical synthetic systems that spontaneously assemble at thermodynamic equilibrium. Here, we report the transient self-assembly of synthetic molecules into active materials, driven by the consumption of a chemical fuel. In these materials, reaction rates and fuel levels, instead of equilibrium composition, determine properties such as lifetime, stiffness, and self-regeneration capability. Fibers exhibit strongly nonlinear behavior including stochastic collapse and simultaneous growth and shrinkage, reminiscent of microtubule dynamics.

  13. Chemical networks

    Science.gov (United States)

    Thi, Wing-Fai

    2015-09-01

    This chapter discusses the fundamental ideas of how chemical networks are build, their strengths and limitations. The chemical reactions that occur in disks combine the cold phase reactions used to model cold molecular clouds with the hot chemistry applied to planetary atmosphere models. With a general understanding of the different types of reactions that can occur, one can proceed in building a network of chemical reactions and use it to explain the abundance of species seen in disks. One on-going research subject is finding new paths to synthesize species either in the gas-phase or on grain surfaces. Specific formation routes for water or carbon monoxide are discussed in more details. 13th Lecture of the Summer School "Protoplanetary Disks: Theory and Modelling Meet Observations"

  14. A Quick-responsive DNA Nanotechnology Device for Bio-molecular Homeostasis Regulation

    Science.gov (United States)

    Wu, Songlin; Wang, Pei; Xiao, Chen; Li, Zheng; Yang, Bing; Fu, Jieyang; Chen, Jing; Wan, Neng; Ma, Cong; Li, Maoteng; Yang, Xiangliang; Zhan, Yi

    2016-01-01

    Physiological processes such as metabolism, cell apoptosis and immune responses, must be strictly regulated to maintain their homeostasis and achieve their normal physiological functions. The speed with which bio-molecular homeostatic regulation occurs directly determines the ability of an organism to adapt to conditional changes. To produce a quick-responsive regulatory system that can be easily utilized for various types of homeostasis, a device called nano-fingers that facilitates the regulation of physiological processes was constructed using DNA origami nanotechnology. This nano-fingers device functioned in linked open and closed phases using two types of DNA tweezers, which were covalently coupled with aptamers that captured specific molecules when the tweezer arms were sufficiently close. Via this specific interaction mechanism, certain physiological processes could be simultaneously regulated from two directions by capturing one biofactor and releasing the other to enhance the regulatory capacity of the device. To validate the universal application of this device, regulation of the homeostasis of the blood coagulant thrombin was attempted using the nano-fingers device. It was successfully demonstrated that this nano-fingers device achieved coagulation buffering upon the input of fuel DNA. This nano-device could also be utilized to regulate the homeostasis of other types of bio-molecules. PMID:27506964

  15. Toxicity evaluation of PEDOT/biomolecular composites intended for neural communication electrodes

    Energy Technology Data Exchange (ETDEWEB)

    Asplund, M; Thaning, E; Von Holst, H [Division of Neuronic Engineering, School of Technology and Health, Royal Institute of Technology, SE-14152 Huddinge (Sweden); Lundberg, J [Section for Neuroradiology, R2:02 NKK-lab, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Solna, SE-171 76, Stockholm (Sweden); Sandberg-Nordqvist, A C [Section of Clinical CNS Research, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, Solna, SE-171 76, Stockholm (Sweden); Kostyszyn, B [Center for Hearing and Communication Research, Department of Clinical Neuroscience, Karolinska Institutet, Karolinska University Hospital, M1:01, SE-171 76 Stockholm (Sweden); Inganaes, O, E-mail: maria.asplund@sth.kth.s [Biomolecular and Organic Electronics, IFM, Linkoeping University, SE-581 83 Linkoeping (Sweden)

    2009-08-15

    Electrodes coated with the conducting polymer poly(3,4-ethylene dioxythiophene) (PEDOT) possess attractive electrochemical properties for stimulation or recording in the nervous system. Biomolecules, added as counter ions in electropolymerization, could further improve the biomaterial properties, eliminating the need for surfactant counter ions in the process. Such PEDOT/biomolecular composites, using heparin or hyaluronic acid, have previously been investigated electrochemically. In the present study, their biocompatibility is evaluated. An agarose overlay assay using L929 fibroblasts, and elution and direct contact tests on human neuroblastoma SH-SY5Y cells are applied to investigate cytotoxicity in vitro. PEDOT:heparin was further evaluated in vivo through polymer-coated implants in rodent cortex. No cytotoxic response was seen to any of the PEDOT materials tested. The examination of cortical tissue exposed to polymer-coated implants showed extensive glial scarring irrespective of implant material (Pt:polymer or Pt). However, quantification of immunological response, through distance measurements from implant site to closest neuron and counting of ED1+ cell density around implant, was comparable to those of platinum controls. These results indicate that PEDOT:heparin surfaces were non-cytotoxic and show no marked difference in immunological response in cortical tissue compared to pure platinum controls.

  16. A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis.

    Science.gov (United States)

    Larimer, Curtis; Winder, Eric; Jeters, Robert; Prowant, Matthew; Nettleship, Ian; Addleman, Raymond Shane; Bonheyo, George T

    2016-01-01

    The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms. PMID:26643074

  17. Solving the 0/1 Knapsack Problem by a Biomolecular DNA Computer

    Directory of Open Access Journals (Sweden)

    Hassan Taghipour

    2013-01-01

    Full Text Available Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.

  18. Extension of the GLYCAM06 Biomolecular Force Field to Lipids, Lipid Bilayers and Glycolipids.

    Science.gov (United States)

    Tessier, Matthew B; Demarco, Mari L; Yongye, Austin B; Woods, Robert J

    2008-01-01

    GLYCAM06 is a generalisable biomolecular force field that is extendible to diverse molecular classes in the spirit of a small-molecule force field. Here we report parameters for lipids, lipid bilayers and glycolipids for use with GLYCAM06. Only three lipid-specific atom types have been introduced, in keeping with the general philosophy of transferable parameter development. Bond stretching, angle bending, and torsional force constants were derived by fitting to quantum mechanical data for a collection of minimal molecular fragments and related small molecules. Partial atomic charges were computed by fitting to ensemble-averaged quantum-computed molecular electrostatic potentials.In addition to reproducing quantum mechanical internal rotational energies and experimental valence geometries for an array of small molecules, condensed-phase simulations employing the new parameters are shown to reproduce the bulk physical properties of a DMPC lipid bilayer. The new parameters allow for molecular dynamics simulations of complex systems containing lipids, lipid bilayers, glycolipids, and carbohydrates, using an internally consistent force field. By combining the AMBER parameters for proteins with the GLYCAM06 parameters, it is also possible to simulate protein-lipid complexes and proteins in biologically relevant membrane-like environments. PMID:22247593

  19. Bridge- and Solvent-Mediated Intramolecular Electronic Communications in Ubiquinone-Based Biomolecular Wires

    Science.gov (United States)

    Liu, Xiao-Yuan; Ma, Wei; Zhou, Hao; Cao, Xiao-Ming; Long, Yi-Tao

    2015-05-01

    Intramolecular electronic communications of molecular wires play a crucial role for developing molecular devices. In the present work, we describe different degrees of intramolecular electronic communications in the redox processes of three ubiquinone-based biomolecular wires (Bis-CoQ0s) evaluated by electrochemistry and Density Functional Theory (DFT) methods in different solvents. We found that the bridges linkers have a significant effect on the electronic communications between the two peripheral ubiquinone moieties and solvents effects are limited and mostly depend on the nature of solvents. The DFT calculations for the first time indicate the intensity of the electronic communications during the redox processes rely on the molecular orbital elements VL for electron transfer (half of the energy splitting of the LUMO and LUMO+1), which is could be affected by the bridges linkers. The DFT calculations also demonstrates the effect of solvents on the latter two-electron transfer of Bis-CoQ0s is more significant than the former two electrons transfer as the observed electrochemical behaviors of three Bis-CoQ0s. In addition, the electrochemistry and theoretical calculations reveal the intramolecular electronic communications vary in the four-electron redox processes of three Bis-CoQ0s.

  20. Chemical and biomolecular characterization of Artemisia umbelliformis Lam., an important ingredient of the alpine liqueur "Genepi".

    Science.gov (United States)

    Rubiolo, Patrizia; Matteodo, Maura; Bicchi, Carlo; Appendino, Giovanni; Gnavi, Giorgio; Bertea, Cinzia; Maffei, Massimo

    2009-05-13

    Artemisia umbelliformis Lam., an important alpine plant used for the preparation of flavored beverages, showed a remarkable intraspecific variability, at both genomic and gene product (secondary metabolites) levels. The variability of A. umbelliformis Lam. currently cultivated in Piedmont (Italy, Au1) and in Switzerland (Au2) was investigated by combining the chemical analysis of essential oil and sesquiterpene lactones and the molecular characterization of the 5S-rRNA-NTS gene by PCR and PCR-RFLP. Marked differences were observed between the two plants. Au1 essential oil contained alpha- and beta-thujones as the main components, whereas Au2 contained 1,8-cineole, borneol, and beta-pinene. Au1 sesquiterpene lactone fractions contained cis-8-eudesmanolide derivatives and Au2 the trans-6-germacranolide costunolide. Specific A. umbelliformis Au1 and Au2 primers were designed on the sequence of the 5S-rRNA gene spacer region. Furthermore, a PCR-restriction fragment length polymorphism (PCR-RFLP) method was applied using RsaI and TaqI restriction enzymes. Chemical and biomolecular data contributed to the characterization of A. umbeliformis chemotypes. PMID:19326948

  1. Bio-objectifying European bodies: standardisation of biobanks in the Biobanking and Biomolecular Resources Research Infrastructure.

    Science.gov (United States)

    Tamminen, Sakari

    2015-01-01

    The article traces the genealogy of the Minimum Information About Biobank Data Sharing model, created in the European Biobanking and Biomolecular Resources Research Infrastructure to facilitate collaboration among biobanks and to foster the exchange of biological samples and data. This information model is aimed at the identification of biobanks; unification of databases; and objectification of the information, samples, and related studies - to create a completely new 'bio-object infrastructure' within the EU. The paper discusses key challenges in creating a 'universal' information model of such a kind, the most important technical translations of European research policy needed for a standardised model for biobank information, and how this model creates new bio-objects. The author claims that this amounts to redefinition of biobanks and technical governance over virtually bio-objectified European populations. It is argued here that old governance models based on the nation-state need radical reconsideration so that we are prepared for a new and changing situation wherein bodies of information that lack organs flow from one database to another with a click of a mouse. PMID:26626620

  2. Magneto-optical relaxation measurements for the characterization of biomolecular interactions

    International Nuclear Information System (INIS)

    Measurements of the magneto-optical relaxation of ferrofluids (MORFF) were applied as a novel homogeneous immunoassay for the investigation of biomolecular interactions. The technique is based on magnetic nanoparticles (MNP) functionalized with antibodies. The relaxation time of the optical birefringence that occurs when a pulsed magnetic field is applied to the nanoparticle suspension depends on the particle size. This enables the detection of particle aggregates formed after the addition of the antigen coupling partner. MORFF size measurements on the original ferrofluid and its fractions obtained by magnetic fractionation are comparable with results from other methods such as atomic force microscopy and photon correlation spectroscopy. In kinetic studies, the binding properties of five antigens and their polyclonal antibodies were investigated: human immunoglobulin G (hIgG), human immunoglobulin M (hIgM), human Eotaxin (hEotaxin), human carcinoembryonic antigen (hCEA), and human insulin (hInsulin). The enlargement of the relaxation time observed during the coupling experiments is expressed in terms of a size distribution function, which includes MNP monomers as well as aggregates. The kinetic process can be described by a model of stepwise polymerization. The kinetic parameters obtained are compared to results of surface plasmon resonance measurements

  3. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

    Science.gov (United States)

    Pardee, Keith; Green, Alexander A; Takahashi, Melissa K; Braff, Dana; Lambert, Guillaume; Lee, Jeong Wook; Ferrante, Tom; Ma, Duo; Donghia, Nina; Fan, Melina; Daringer, Nichole M; Bosch, Irene; Dudley, Dawn M; O'Connor, David H; Gehrke, Lee; Collins, James J

    2016-05-19

    The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP. PMID:27160350

  4. Review of Transducer Principles for Label-Free Biomolecular Interaction Analysis

    Directory of Open Access Journals (Sweden)

    Janos Vörös

    2011-07-01

    Full Text Available Label-free biomolecular interaction analysis is an important technique to study the chemical binding between e.g., protein and protein or protein and small molecule in real-time. The parameters obtained with this technique, such as the affinity, are important for drug development. While the surface plasmon resonance (SPR instruments are most widely used, new types of sensors are emerging. These developments are generally driven by the need for higher throughput, lower sample consumption or by the need of complimentary information to the SPR data. This review aims to give an overview about a wide range of sensor transducers, the working principles and the peculiarities of each technology, e.g., concerning the set-up, sensitivity, sensor size or required sample volume. Starting from optical technologies like the SPR and waveguide based sensors, acoustic sensors like the quartz crystal microbalance (QCM and the film bulk acoustic resonator (FBAR, calorimetric and electrochemical sensors are covered. Technologies long established in the market are presented together with those newly commercially available and with technologies in the early development stage. Finally, the commercially available instruments are summarized together with their sensitivity and the number of sensors usable in parallel and an outlook for potential future developments is given.

  5. Photodamage and the importance of photoprotection in biomolecular-powered device applications.

    Science.gov (United States)

    Vandelinder, Virginia; Bachand, George D

    2014-01-01

    In recent years, an enhanced understanding of the mechanisms underlying photobleaching and photoblinking of fluorescent dyes has led to improved photoprotection strategies, such as reducing and oxidizing systems (ROXS) that reduce blinking and oxygen scavenging systems to reduce bleaching. Excitation of fluorescent dyes can also result in damage to catalytic proteins (e.g., biomolecular motors), affecting the performance of integrated devices. Here, we characterized the motility of microtubules driven by kinesin motor proteins using various photoprotection strategies, including a microfluidic deoxygenation device. Impaired motility of microtubules was observed at high excitation intensities in the absence of photoprotection as well as in the presence of an enzymatic oxygen scavenging system. In contrast, using a polydimethylsiloxane (PDMS) microfluidic deoxygenation device and ROXS, not only were the fluorophores slower to bleach but also moving the velocity and fraction of microtubules over time remained unaffected even at high excitation intensities. Further, we demonstrate the importance of photoprotection by examining the effect of photodamage on the behavior of a switchable mutant of kinesin. Overall, these results demonstrate that improved photoprotection strategies may have a profound impact on functional fluorescently labeled biomolecules in integrated devices. PMID:24350711

  6. Evaluation of Emerging Energy-Efficient Heterogeneous Computing Platforms for Biomolecular and Cellular Simulation Workloads

    Science.gov (United States)

    Stone, John E.; Hallock, Michael J.; Phillips, James C.; Peterson, Joseph R.; Luthey-Schulten, Zaida; Schulten, Klaus

    2016-01-01

    Many of the continuing scientific advances achieved through computational biology are predicated on the availability of ongoing increases in computational power required for detailed simulation and analysis of cellular processes on biologically-relevant timescales. A critical challenge facing the development of future exascale supercomputer systems is the development of new computing hardware and associated scientific applications that dramatically improve upon the energy efficiency of existing solutions, while providing increased simulation, analysis, and visualization performance. Mobile computing platforms have recently become powerful enough to support interactive molecular visualization tasks that were previously only possible on laptops and workstations, creating future opportunities for their convenient use for meetings, remote collaboration, and as head mounted displays for immersive stereoscopic viewing. We describe early experiences adapting several biomolecular simulation and analysis applications for emerging heterogeneous computing platforms that combine power-efficient system-on-chip multi-core CPUs with high-performance massively parallel GPUs. We present low-cost power monitoring instrumentation that provides sufficient temporal resolution to evaluate the power consumption of individual CPU algorithms and GPU kernels. We compare the performance and energy efficiency of scientific applications running on emerging platforms with results obtained on traditional platforms, identify hardware and algorithmic performance bottlenecks that affect the usability of these platforms, and describe avenues for improving both the hardware and applications in pursuit of the needs of molecular modeling tasks on mobile devices and future exascale computers.

  7. A new source for quantum optics with biomolecules and biomolecular clusters

    Science.gov (United States)

    Marksteiner, Markus; Haslinger, Philipp; Ulbricht, Hendrik; Arndt, Markus

    2008-03-01

    We present recent progress towards matter wave experiments with amino acids, polypeptides and large biomolecular clusters. All successful experiments on macromolecule interferometry so far, with fullerenes, fullerene derivates and large perfluoroalkyl-functionalized azobenzenes used effusive beam sources. The combination of Stark deflectometry with quantum interferometry also allowed us to create a new device for precisely measuring electric susceptibilities of large molecules in the gas phase. In order to apply quantum interference to molecules of biological interest, we have now implemented a pulsed laser desorption source. The combination of UV laser desorption into an intense noble gas jet and single-photon ionization by a VUV excimer laser (157nm) allows us to observe intense neutral jets of amino acids (e.g. Tryptophan), nucleotides (e.g. Guanin) and polypeptides ranging from tri-peptides to Gramicidin. Remarkably, we also found a new method for producing large neutral amino acid clusters, such as for instance Trp30, with masses exceeding 6000 amu: the addition of alkaline Earth salts in the desorption process leads to the inclusion of at least one metal atom per complex and is sufficient to catalyze the cluster formation process.

  8. An Atomic Force Microscope with Dual Actuation Capability for Biomolecular Experiments

    Science.gov (United States)

    Sevim, Semih; Shamsudhin, Naveen; Ozer, Sevil; Feng, Luying; Fakhraee, Arielle; Ergeneman, Olgaç; Pané, Salvador; Nelson, Bradley J.; Torun, Hamdi

    2016-06-01

    We report a modular atomic force microscope (AFM) design for biomolecular experiments. The AFM head uses readily available components and incorporates deflection-based optics and a piezotube-based cantilever actuator. Jetted-polymers have been used in the mechanical assembly, which allows rapid manufacturing. In addition, a FeCo-tipped electromagnet provides high-force cantilever actuation with vertical magnetic fields up to 0.55 T. Magnetic field calibration has been performed with a micro-hall sensor, which corresponds well with results from finite element magnetostatics simulations. An integrated force resolution of 1.82 and 2.98 pN, in air and in DI water, respectively was achieved in 1 kHz bandwidth with commercially available cantilevers made of Silicon Nitride. The controller and user interface are implemented on modular hardware to ensure scalability. The AFM can be operated in different modes, such as molecular pulling or force-clamp, by actuating the cantilever with the available actuators. The electromagnetic and piezoelectric actuation capabilities have been demonstrated in unbinding experiments of the biotin-streptavidin complex.

  9. Potential-of-mean-force description of ionic interactions and structural hydration in biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Hummer, G.; Garcia, A.E. [Los Alamos National Lab., NM (United States). Theoretical Biology and Biophysics Group; Soumpasis, D.M. [Max-Planck-Inst for Biophysical Chemistry, Goettingen (Germany). Biocomputation Group

    1994-10-01

    To understand the functioning of living organisms on a molecular level, it is crucial to dissect the intricate interplay of the immense number of biological molecules. Most of the biochemical processes in cells occur in a liquid environment formed mainly by water and ions. This solvent environment plays an important role in biological systems. The potential-of-mean-force (PMF) formalism attempts to describe quantitatively the interactions of the solvent with biological macromolecules on the basis of an approximate statistical-mechanical representation. At its current status of development, it deals with ionic effects on the biomolecular structure and with the structural hydration of biomolecules. The underlying idea of the PMF formalism is to identify the dominant sources of interactions and incorporate these interactions into the theoretical formalism using PMF`s (or particle correlation functions) extracted from bulk-liquid systems. In the following, the authors shall briefly outline the statistical-mechanical foundation of the PMF formalism and introduce the PMF expansion formalism, which is intimately linked to superposition approximations for higher-order particle correlation functions. The authors shall then sketch applications, which describe the effects of the ionic environment on nucleic-acid structure. Finally, the authors shall present the more recent extension of the PMF idea to describe quantitatively the structural hydration of biomolecules. Results for the interface of ice and water and for the hydration of deoxyribonucleic acid (DNA) will be discussed.

  10. Biomolecular environment, quantification, and intracellular interaction of multifunctional magnetic SERS nanoprobes.

    Science.gov (United States)

    Büchner, Tina; Drescher, Daniela; Merk, Virginia; Traub, Heike; Guttmann, Peter; Werner, Stephan; Jakubowski, Norbert; Schneider, Gerd; Kneipp, Janina

    2016-08-15

    Multifunctional composite nanoprobes consisting of iron oxide nanoparticles linked to silver and gold nanoparticles, Ag-Magnetite and Au-Magnetite, respectively, were introduced by endocytic uptake into cultured fibroblast cells. The cells containing the non-toxic nanoprobes were shown to be displaceable in an external magnetic field and can be manipulated in microfluidic channels. The distribution of the composite nanostructures that are contained in the endosomal system is discussed on the basis of surface-enhanced Raman scattering (SERS) mapping, quantitative laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) micromapping, and cryo soft X-ray tomography (cryo soft-XRT). Cryo soft-XRT of intact, vitrified cells reveals that the composite nanoprobes form intra-endosomal aggregates. The nanoprobes provide SERS signals from the biomolecular composition of their surface in the endosomal environment. The SERS data indicate the high stability of the nanoprobes and of their plasmonic properties in the harsh environment of endosomes and lysosomes. The spectra point at the molecular composition at the surface of the Ag-Magnetite and Au-Magnetite nanostructures that is very similar to that of other composite structures, but different from the composition of pure silver and gold SERS nanoprobes used for intracellular investigations. As shown by the LA-ICP-MS data, the uptake efficiency of the magnetite composites is approximately two to three times higher than that of the pure gold and silver nanoparticles. PMID:27353290

  11. Biomolecular Nano-Flow-Sensor to Measure Near-Surface Flow

    Directory of Open Access Journals (Sweden)

    Noji Hiroyuki

    2009-01-01

    Full Text Available Abstract We have proposed and experimentally demonstrated that the measurement of the near-surface flow at the interface between a liquid and solid using a 10 nm-sized biomolecular motor of F1-ATPase as a nano-flow-sensor. For this purpose, we developed a microfluidic test-bed chip to precisely control the liquid flow acting on the F1-ATPase. In order to visualize the rotation of F1-ATPase, several hundreds nanometer-sized particle was immobilized at the rotational axis of F1-ATPase to enhance the rotation to be detected by optical microscopy. The rotational motion of F1-ATPase, which was immobilized on an inner surface of the test-bed chip, was measured to obtain the correlation between the near-surface flow and the rotation speed of F1-ATPase. As a result, we obtained the relationship that the rotation speed of F1-ATPase was linearly decelerated with increasing flow velocity. The mechanism of the correlation between the rotation speed and the near-surface flow remains unclear, however the concept to use biomolecule as a nano-flow-sensor was proofed successfully. (See supplementary material 1 Electronic supplementary material The online version of this article (doi:10.1007/s11671-009-9479-3 contains supplementary material, which is available to authorized users. Click here for file

  12. The Effect of Biomolecular Gradients on Mesenchymal Stem Cell Chondrogenesis under Shear Stress

    Directory of Open Access Journals (Sweden)

    Alexander L. Rivera

    2015-03-01

    Full Text Available Tissue engineering is viewed as a promising option for long-term repair of cartilage lesions, but current engineered cartilage constructs fail to match the mechanical properties of native tissue. The extracellular matrix of adult human articular cartilage contains highly organized collagen fibrils that enhance the mechanical properties of the tissue. Unlike articular cartilage, mesenchymal stem cell (MSC based tissue engineered cartilage constructs lack this oriented microstructure and therefore display much lower mechanical strength. The goal of this study was to investigate the effect of biomolecular gradients and shear stress on MSCs undergoing chondrogenesis within a microfluidic device. Via poly(dimethyl siloxane soft-lithography, microfluidic devices containing a gradient generator were created. Human MSCs were seeded within these chambers and exposed to flow-based transforming growth factor β1 (TGF-β1 gradients. When the MSCs were both confluent and exposed to shear stress, the cells aligned along the flow direction. Exposure to TGF-β1 gradients led to chondrogenesis of MSCs, indicated by positive type II collagen staining. These results, together with a previous study that showed that aligned MSCs produce aligned collagen, suggest that oriented cartilage tissue structures with superior mechanical properties can be obtained by aligning MSCs along the flow direction and exposing MSCs to chondrogenic gradients.

  13. A computational study of the interaction of graphene structures with biomolecular units.

    Science.gov (United States)

    Carballeira, Diego López; Ramos-Berdullas, Nicolás; Pérez-Juste, Ignacio; Fajín, José Luis Cagide; Cordeiro, M Natália D S; Mandado, Marcos

    2016-06-01

    Due to the great interest that biochemical sensors constructed from graphene nanostructures have raised recently, in this work we analyse in detail the electronic factors responsible for the large affinity of biomolecular units for graphene surfaces using ab initio quantum chemical tools based on density functional theory. Both finite and periodic graphene structures have been employed in our study. Whereas the former allows the analysis of the different energy components contributing to the interaction energy separately, the periodic structure provides a more realistic calculation of the total adsorption energy in an extended graphene surface and serves to validate the results obtained using the finite model. In addition, qualitative relations between interaction energy and electron polarization upon adsorption have been established using the finite model. In this work, we have analysed thermodynamically stable adsorption complexes formed by glycine, melamine, pyronin cation, porphine, tetrabenzoporphine and phthalocyanine with a 2D structure of ninety six carbons and periodic structures formed by cells of fifty and seventy two carbons. Differences in the electrostatic, Pauli repulsion, induction and dispersion energies among aromatic and non-aromatic molecules, charged and non-charged molecules and H-π and stacking interactions have been thoroughly analysed in this work. PMID:27210053

  14. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    Science.gov (United States)

    Doster, W.; Nakagawa, H.; Appavou, M. S.

    2013-07-01

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at Td from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature Tg. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature Td.

  15. Improved model of hydrated calcium ion for molecular dynamics simulations using classical biomolecular force fields.

    Science.gov (United States)

    Yoo, Jejoong; Wilson, James; Aksimentiev, Aleksei

    2016-10-01

    Calcium ions (Ca(2+) ) play key roles in various fundamental biological processes such as cell signaling and brain function. Molecular dynamics (MD) simulations have been used to study such interactions, however, the accuracy of the Ca(2+) models provided by the standard MD force fields has not been rigorously tested. Here, we assess the performance of the Ca(2+) models from the most popular classical force fields AMBER and CHARMM by computing the osmotic pressure of model compounds and the free energy of DNA-DNA interactions. In the simulations performed using the two standard models, Ca(2+) ions are seen to form artificial clusters with chloride, acetate, and phosphate species; the osmotic pressure of CaAc2 and CaCl2 solutions is a small fraction of the experimental values for both force fields. Using the standard parameterization of Ca(2+) ions in the simulations of Ca(2+) -mediated DNA-DNA interactions leads to qualitatively wrong outcomes: both AMBER and CHARMM simulations suggest strong inter-DNA attraction whereas, in experiment, DNA molecules repel one another. The artificial attraction of Ca(2+) to DNA phosphate is strong enough to affect the direction of the electric field-driven translocation of DNA through a solid-state nanopore. To address these shortcomings of the standard Ca(2+) model, we introduce a custom model of a hydrated Ca(2+) ion and show that using our model brings the results of the above MD simulations in quantitative agreement with experiment. Our improved model of Ca(2+) can be readily applied to MD simulations of various biomolecular systems, including nucleic acids, proteins and lipid bilayer membranes. © 2016 Wiley Periodicals, Inc. Biopolymers 105: 752-763, 2016. PMID:27144470

  16. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    Energy Technology Data Exchange (ETDEWEB)

    Doster, W. [Physik-Department, Technische Universität München, D-85748 Garching (Germany); Nakagawa, H. [Jülich Centre for Neutron Science, Forschungszentrum Jülich GmbH, Outstation at MLZ, Lichtenbergstraße 1, 85747 Garching (Germany); Japan Atomic Energy Agency, Quantum Beam Science Directorate, Tokai, Ibaraki 319-1195 (Japan); Appavou, M. S. [Jülich Centre for Neutron Science, Forschungszentrum Jülich GmbH, Outstation at MLZ, Lichtenbergstraße 1, 85747 Garching (Germany)

    2013-07-28

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at T{sub d} from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature T{sub g}. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature T{sub d}.

  17. Scaling analysis of bio-molecular dynamics derived from elastic incoherent neutron scattering experiments

    International Nuclear Information System (INIS)

    Numerous neutron scattering studies of bio-molecular dynamics employ a qualitative analysis of elastic scattering data and atomic mean square displacements. We provide a new quantitative approach showing that the intensity at zero energy exchange can be a rich source of information of bio-structural fluctuations on a pico- to nano-second time scale. Elastic intensity scans performed either as a function of the temperature (back-scattering) and/or by varying the instrumental resolution (time of flight spectroscopy) yield the activation parameters of molecular motions and the approximate structural correlation function in the time domain. The two methods are unified by a scaling function, which depends on the ratio of correlation time and instrumental resolution time. The elastic scattering concept is illustrated with a dynamic characterization of alanine-dipeptide, protein hydration water, and water-coupled protein motions of lysozyme, per-deuterated c-phycocyanin (CPC) and hydrated myoglobin. The complete elastic scattering function versus temperature, momentum exchange, and instrumental resolution is analyzed instead of focusing on a single cross-over temperature of mean square displacements at the apparent onset temperature of an-harmonic motions. Our method predicts the protein dynamical transition (PDT) at Td from the collective (α) structural relaxation rates of the solvation shell as input. By contrast, the secondary (β) relaxation enhances the amplitude of fast local motions in the vicinity of the glass temperature Tg. The PDT is specified by step function in the elastic intensity leading from elastic to viscoelastic dynamic behavior at a transition temperature Td

  18. A synergic simulation-optimization approach for analyzing biomolecular dynamics in living organisms.

    Science.gov (United States)

    Sadegh Zadeh, Kouroush

    2011-01-01

    A synergic duo simulation-optimization approach was developed and implemented to study protein-substrate dynamics and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study dynamics of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate dynamics of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study dynamics of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by optimization. PMID:21106190

  19. An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution

    Energy Technology Data Exchange (ETDEWEB)

    Fluitt, Aaron M. [Univ. of Chicago, IL (United States); de Pablo, Juan J. [Argonne National Lab. (ANL), Argonne, IL (United States)

    2015-09-01

    Polyglutamine (polyQ) peptides are a useful model system for biophysical studies of protein folding and aggregation, both for their intriguing aggregation properties and their own relevance to human disease. The genetic expansion of a polyQ tract triggers the formation of amyloid aggregates associated with nine neurodegenerative diseases. Several clearly identifiable and separable factors, notably the length of the polyQ tract, influence the mechanism of aggregation, its associated kinetics, and the ensemble of structures formed. Atomistic simulations are well positioned to answer open questions regarding the thermodynamics and kinetics of polyQ folding and aggregation. The additional, explicit representation of water permits deeper investigation of the role of solvent dynamics, and it permits a direct comparison of simulation results with infrared spectroscopy experiments. The generation of meaningful simulation results hinges on satisfying two essential criteria: achieving sufficient conformational sampling to draw statistically valid conclusions, and accurately reproducing the intermolecular forces that govern system structure and dynamics. In this work, we examine the ability of 12 biomolecular force fields to reproduce the properties of a simple, 30-residue polyQ peptide (Q30) in explicit water. In addition to secondary and tertiary structure, we consider generic structural properties of polymers that provide additional dimensions for analysis of the highly degenerate disordered states of the molecule. We find that the 12 force fields produce a wide range of predictions. We identify AMBER ff99SB, AMBER ff99SB*, and OPLS-AA/L to be most suitable for studies of polyQ folding and aggregation.

  20. Evolução biomolecular homoquiral: a origem e a amplificação da quiralidade nas moléculas da vida Homochiral biomolecular evolution: the origin and the amplification of chirality in life molecules

    Directory of Open Access Journals (Sweden)

    José Augusto R. Rodrigues

    2010-01-01

    Full Text Available The fact that biologically relevant molecules exist only as one of the two enantiomers is a fascinating example of complete symmetry breaking of chirality and has long intrigued our curiosity. The origin of this selective chirality has remained a fundamental enigma with regard to the origin of life since the time of Pasteur, 160 years ago. The symmetry breaking processes, which include autocatalytic crystallization, asymmetric autocatalysis, spontaneous crystallization, adsorption and polymerization of amino acids on mineral surfaces, provide new insights into the origin of biomolecular homochirality.

  1. Synthetic tetracycline-inducible regulatory networks: computer-aided design of dynamic phenotypes

    Directory of Open Access Journals (Sweden)

    Kaznessis Yiannis N

    2007-01-01

    Full Text Available Abstract Background Tightly regulated gene networks, precisely controlling the expression of protein molecules, have received considerable interest by the biomedical community due to their promising applications. Among the most well studied inducible transcription systems are the tetracycline regulatory expression systems based on the tetracycline resistance operon of Escherichia coli, Tet-Off (tTA and Tet-On (rtTA. Despite their initial success and improved designs, limitations still persist, such as low inducer sensitivity. Instead of looking at these networks statically, and simply changing or mutating the promoter and operator regions with trial and error, a systematic investigation of the dynamic behavior of the network can result in rational design of regulatory gene expression systems. Sophisticated algorithms can accurately capture the dynamical behavior of gene networks. With computer aided design, we aim to improve the synthesis of regulatory networks and propose new designs that enable tighter control of expression. Results In this paper we engineer novel networks by recombining existing genes or part of genes. We synthesize four novel regulatory networks based on the Tet-Off and Tet-On systems. We model all the known individual biomolecular interactions involved in transcription, translation, regulation and induction. With multiple time-scale stochastic-discrete and stochastic-continuous models we accurately capture the transient and steady state dynamics of these networks. Important biomolecular interactions are identified and the strength of the interactions engineered to satisfy design criteria. A set of clear design rules is developed and appropriate mutants of regulatory proteins and operator sites are proposed. Conclusion The complexity of biomolecular interactions is accurately captured through computer simulations. Computer simulations allow us to look into the molecular level, portray the dynamic behavior of gene regulatory

  2. Evaluation of kinetic constants of biomolecular interaction on optical surface plasmon resonance sensor with Newton Iteration Method

    Science.gov (United States)

    Zhao, Yuanyuan; Jiang, Guoliang; Hu, Jiandong; Hu, Fengjiang; Wei, Jianguang; Shi, Liang

    2010-10-01

    In the immunology, there are two important types of biomolecular interaction: antigens-antibodies and receptors-ligands. Monitoring the response rate and affinity of biomolecular interaction can help analyze the protein function, drug discover, genomics and proteomics research. Moreover the association rate constant and dissociation rate constant of receptors-ligands are the important parameters for the study of signal transmission between cells. Recent advances in bioanalyzer instruments have greatly simplified the measurement of the kinetics of molecular interactions. Non-destructive and real-time monitoring the response to evaluate the parameters between antigens and antibodies can be performed by using optical surface plasmon resonance (SPR) biosensor technology. This technology provides a quantitative analysis that is carried out rapidly with label-free high-throughput detection using the binding curves of antigens-antibodies. Consequently, the kinetic parameters of interaction between antigens and antibodies can be obtained. This article presents a low cost integrated SPR-based bioanalyzer (HPSPR-6000) designed by ourselves. This bioanalyzer is mainly composed of a biosensor TSPR1K23, a touch-screen monitor, a microprocessor PIC24F128, a microflow cell with three channels, a clamp and a photoelectric conversion device. To obtain the kinetic parameters, sensorgrams may be modeled using one of several binding models provided with BIAevaluation software 3.0, SensiQ or Autolab. This allows calculation of the association rate constant (ka) and the dissociation rate constant (kd). The ratio of ka to kd can be used to estimate the equilibrium constant. Another kind is the analysis software OriginPro, which can process the obtained data by nonlinear fitting and then get some correlative parameters, but it can't be embedded into the bioanalyzer, so the bioanalyzer don't support the use of OriginPro. This paper proposes a novel method to evaluate the kinetic parameters

  3. Catalytic Oxidized Reaction of Paraffin Wax Based on BP Neural Network%基于BP神经网络的石蜡催化氧化反应的研究

    Institute of Scientific and Technical Information of China (English)

    黄玮; 丛玉凤; 郭大鹏

    2012-01-01

    The oxidized wax was prepared by catalytic oxidized reaction of paraffin wax which used BP neural network to build mathematical model of acid value and saponification value influenced by the amount of reactive catalyst and accessory ingredient, airflow rate, reaction temperature and time, and utilized the model of neutral network to calculate the technology condition of preparing oxidized wax through catalyzing and oxidizing paraffin wax. Consequently, optimum technology conditions were gained in order to achieve the objective of reducing experimental number of times.%在石蜡催化氧化反应制备氧化蜡的研究中,利用BP神经网络建立反应催化剂用量、助剂用量、空气流量、反应温度和反应时间对酸值和皂化值影响的数学模型,并利用该神经网络模型对石蜡催化氧化制备氧化蜡的工艺条件进行预测,从而获得最优工艺条件,达到缩短实验次数的目的.

  4. Heuristics-Guided Exploration of Reaction Mechanisms

    CERN Document Server

    Bergeler, Maike; Proppe, Jonny; Reiher, Markus

    2015-01-01

    For the investigation of chemical reaction networks, the efficient and accurate determination of all relevant intermediates and elementary reactions is inevitable. The complexity of such a network may grow rapidly, in particular if reactive species are involved that might cause a myriad of side reactions. Without automation, a complete investigation of complex reaction mechanisms is tedious and possibly unfeasible. Therefore, only the expected dominant reaction paths of a chemical reaction network (e.g., a catalytic cycle or an enzymatic cascade) are usually explored in practice. Here, we present a computational protocol that constructs such networks in a parallelized and automated manner. Molecular structures of reactive complexes are generated based on heuristic rules and subsequently optimized by electronic-structure methods. Pairs of reactive complexes related by an elementary reaction are then automatically detected and subjected to an automated search for the connecting transition state. The results are...

  5. Nanomechanical force transducers for biomolecular and intracellular measurements: is there room to shrink and why do it?

    International Nuclear Information System (INIS)

    Over the past couple of decades there has been a tremendous amount of progress on the development of ultrasensitive nanomechanical instruments, which has enabled scientists to peer for the first time into the mechanical world of biomolecular systems. Currently, work-horse instruments such as the atomic force microscope and optical/magnetic tweezers have provided the resolution necessary to extract quantitative force data from various molecular systems down to the femtonewton range, but it remains difficult to access the intracellular environment with these analytical tools as they have fairly large sizes and complicated feedback systems. This review is focused on highlighting some of the major milestones and discoveries in the field of biomolecular mechanics that have been made possible by the development of advanced atomic force microscope and tweezer techniques as well as on introducing emerging state-of-the-art nanomechanical force transducers that are addressing the size limitations presented by these standard tools. We will first briefly cover the basic setup and operation of these instruments, and then focus heavily on summarizing advances in in vitro force studies at both the molecular and cellular level. The last part of this review will include strategies for shrinking down the size of force transducers and provide insight into why this may be important for gaining a more complete understanding of cellular activity and function. (report on progress)

  6. Real-time and label-free detection of biomolecular interactions by oblique-incidence reflectivity difference method

    Science.gov (United States)

    Wang, Xu; Lu, Heng; Dai, Jun; Wen, Juan; Yuan, Kun; Lü, Hui-Bin; Jin, Kui-Juan; Zhou, Yue-Liang; Yang, Guo-Zhen

    2011-01-01

    We successfully conduct the label-free and real-time detection of the interactions between epoxy groups and rabbit IgG and 5' CTT CAG GTC ATG AGC CTG AT 3' oligonucleotide, and between the hybridization of 5' CTT CAG GTC ATG AGC CTG AT 3' and its complementary 3' GAA GTC CAG TAC TCG GAC TA 5' oligonucleotide, by the oblique-incidence reflectivity difference (OI-RD) method. The dynamic curves of OI-RD signals, corresponding to the kinetic processes of biomolecular combination or hybridization, are acquired. In our case, the combination of epoxy groups with rabbit IgG and 5' CTT CAG GTC ATG AGC CTG AT 3' oligonucleotide need almost one and a half hours and about two hundred seconds, respectively; and the hybridization of the two oligonucleotides needs about five hundred seconds. The experimental results show that the OI-RD is a promising method for the real-time and label-free detection of biomolecular interactions.

  7. Bioactive membranes for bone regeneration applications: effect of physical and biomolecular signals on mesenchymal stem cell behavior.

    Science.gov (United States)

    Tejeda-Montes, Esther; Smith, Katherine H; Rebollo, Elena; Gómez, Raúl; Alonso, Matilde; Rodriguez-Cabello, J Carlos; Engel, Elisabeth; Mata, Alvaro

    2014-01-01

    This study focuses on the in vitro characterization of bioactive elastin-like recombinamer (ELR) membranes for bone regeneration applications. Four bioactive ELRs exhibiting epitopes designed to promote mesenchymal stem cell adhesion (RGDS), endothelial cell adhesion (REDV), mineralization (HAP), and both cell adhesion and mineralization (HAP-RGDS) were synthesized using standard recombinant protein techniques. The materials were then used to fabricate ELR membranes incorporating a variety of topographical micropatterns including channels, holes and posts. Primary rat mesenchymal stem cells (rMSCs) were cultured on the different membranes and the effects of biomolecular and physical signals on cell adhesion, morphology, proliferation, and differentiation were evaluated. All results were analyzed using a custom-made MATLAB program for high throughput image analysis. Effects on cell morphology were mostly dependent on surface topography, while cell proliferation and cell differentiation were largely dependent on the biomolecular signaling from the ELR membranes. In particular, osteogenic differentiation (evaluated by staining for the osteoblastic marker osterix) was significantly enhanced on cells cultured on HAP membranes. Remarkably, cells growing on membranes containing the HAP sequence in non-osteogenic differentiation media exhibited significant up-regulation of the osteogenic marker as early as day 5, while those growing on fibronectin-coated glass in osteogenic differentiation media did not. These results are part of our ongoing effort to develop an optimized molecularly designed periosteal graft. PMID:24035887

  8. Production and detection of neutral molecular beams : from single amino acids to biomolecular complexes

    International Nuclear Information System (INIS)

    biomolecular complexes. The largest observed complex is a gramicidin tetramer with a mass of 7,536amu. Furthermore, desorption of tryptophan together with alkaline earth salts, such as calcium-carbonate results in the formation of two different kinds of massive tryptophan clusters: Tryptophan clusters containing a single calcium atom with a mass of up to 6,800amu and also pure clusters with a mass of up to 7,100amu are observed. The inclusion of a metal atom into tryptophan clusters is observed also for strontium, barium ,sodium and copper. The cluster formation is studied additionally for other amino acids such as phenylalanine, the tripeptide tyrosine-tryptophan-glycine and the nucleotide guanine. The cluster formation between two different molecular species was observed after the simultaneous desorption of gramicidin and tryptophan and resulted in the attachment of tryptophan molecules to a single gramicidin. An alternative detection method to photo-ionization is examined by testing a superconducting single photon detector (SSPD) for its ability to detect individual neutral molecules. The sensitivity of the nanostructured SSPD seems not to be limited to small molecules. The superconducting detector is able to record velocity distributions of neutral insulin (∼5,700amu), myoglobin(∼17 kDa) and hemoglobin (∼66 kDa) beams. A check if the intact molecules leave the source is missing due to the lack of alternative detection methods for these molecules. The working principle of the SSPD relies on the fact, that an impinging particle leads to a breakdown of superconductivity. Further developments of the SSPD appear possible and promising in order to increase the mass range of detected neutral organic molecules, which cannot be detected in photo-ionization. The source is developed in order to fulfil the criteria needed for a combination with a Talbot-Lau interferometer. Interference of biomolecules is, beside the prove of the wave-particle duality, interesting for the

  9. BioSCAN: a network sharable computational resource for searching biosequence databases.

    Science.gov (United States)

    Singh, R K; Hoffman, D L; Tell, S G; White, C T

    1996-06-01

    We describe a network sharable, interactive computational tool for rapid and sensitive search and analysis of biomolecular sequence databases such as GenBank, GenPept, Protein Identification Resource, and SWISS-PROT. The resource is accessible via the World Wide Web using popular client software such as Mosaic and Netscape. The client software is freely available on a number of computing platforms including Macintosh, IBM-PC, and Unix workstations. PMID:8872387

  10. Enzymatic reactions in confined environments

    Science.gov (United States)

    Küchler, Andreas; Yoshimoto, Makoto; Luginbühl, Sandra; Mavelli, Fabio; Walde, Peter

    2016-05-01

    Within each biological cell, surface- and volume-confined enzymes control a highly complex network of chemical reactions. These reactions are efficient, timely, and spatially defined. Efforts to transfer such appealing features to in vitro systems have led to several successful examples of chemical reactions catalysed by isolated and immobilized enzymes. In most cases, these enzymes are either bound or adsorbed to an insoluble support, physically trapped in a macromolecular network, or encapsulated within compartments. Advanced applications of enzymatic cascade reactions with immobilized enzymes include enzymatic fuel cells and enzymatic nanoreactors, both for in vitro and possible in vivo applications. In this Review, we discuss some of the general principles of enzymatic reactions confined on surfaces, at interfaces, and inside small volumes. We also highlight the similarities and differences between the in vivo and in vitro cases and attempt to critically evaluate some of the necessary future steps to improve our fundamental understanding of these systems.

  11. Nuclear Reactions

    OpenAIRE

    Bertulani, C. A.

    2009-01-01

    Nuclear reactions generate energy in nuclear reactors, in stars, and are responsible for the existence of all elements heavier than hydrogen in the universe. Nuclear reactions denote reactions between nuclei, and between nuclei and other fundamental particles, such as electrons and photons. A short description of the conservation laws and the definition of basic physical quantities is presented, followed by a more detailed account of specific cases: (a) formation and decay of compound nuclei;...

  12. Dynamic analysis of biochemical network using complex network method

    OpenAIRE

    Wang Shuqiang; Shen Yanyan; Hu Jinxing; Li Ning; Zeng Dewei

    2015-01-01

    In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger ...

  13. Survey of Network-Based Approaches to Research of Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Anida Sarajlić

    2014-01-01

    Full Text Available Cardiovascular diseases (CVDs are the leading health problem worldwide. Investigating causes and mechanisms of CVDs calls for an integrative approach that would take into account its complex etiology. Biological networks generated from available data on biomolecular interactions are an excellent platform for understanding interconnectedness of all processes within a living cell, including processes that underlie diseases. Consequently, topology of biological networks has successfully been used for identifying genes, pathways, and modules that govern molecular actions underlying various complex diseases. Here, we review approaches that explore and use relationships between topological properties of biological networks and mechanisms underlying CVDs.

  14. High energy halogen atom reactions activated by nuclear transformations. Progress report, February 15-December 31, 1984

    International Nuclear Information System (INIS)

    Energetic halogen atoms or ions, activated by various nuclear transformations are studied in gas, high pressure and condensed phase saturated and unsaturated hydrocarbons, halomethanes, and liquid and solid aqueous solutions of biomolecular and organic solutes in order to understand better the mechanisms and dynamics of high energy monovalent species. The experimental program and its goals remain the same, consisting of four interrelated areas: (1) The stereochemistry of energetic 18F, /sup 34m/Cl, and 38Cl substitution reactions with chiral molecules in the gas and condensed phase is studied. (2) The gas to condensed state transition in halogen high energy chemistry, involving energetic chlorine, bromine, and iodine reactions in halomethanes, saturated and unsaturated hydrocarbons and aqueous solutions of biomolecules and alkyl halides is being investigated in more detail. Current attention is given to defining the nature of the enhancement yields in the condensed phase. Specifically, energetic halogen reactions in liquid and frozen aqueous solutions or organic and biomolecular solutes are studied. (3) Reactions of bromine and iodine activated by isomeric transition with halogenated biomolecular and organic solutes in liquid and frozen aqueous solutions are being studied in an attempt to learn more about the activation events in the condensed phase. (4) The applications of hot chemistry techniques and theory to neutron activation analysis of biological systems are being continued. Current attention is given to developing procedures for trace molecular determinations in biological systems. The applications of hot halogen atoms as site indicators in liquid and frozen aqueous solutions of halogenated bases and nucleosides are currently being developed. 14 references

  15. 利用回声状态网络建立管式聚合反应的灰箱模型%An approach of grey-box modeling with echo state network for tubular polymerization reaction

    Institute of Scientific and Technical Information of China (English)

    秦松; 曹柳林

    2014-01-01

    提出一种利用回声状态网络(echo state network, ESN)建立复杂分布参数系统模型的灰箱建模方法。此建模方法可以充分利用已知机理模型的结构信息和回声状态网络的逼近能力,可更好地描述和解释出系统各变量之间的因果关系,使模型的“灰箱”化程度更高。首先,根据系统方程和先验知识将初始系统特征团引入ESN储备池中,赋予网络节点实际物理意义,并以此建立结构逼近神经网络模型;然后,通过逐步回归分析方法,结合递归最小二乘算法选择最优系统特征团,并对网络结构进行优化,建立起描述系统特性关系的灰箱模型。本文以实验室规模的管式聚合反应过程作为实验对象,建立以温度分布为输出的数学模型,结果表明所提出的灰箱建模方法行之有效。%An approach of grey-box modeling with Echo State Network (ESN) is developed for modeling dynamic processes with nonlinear characteristics. This method can take full advantage of the already known structural information of the mechanism model at the early stage of modeling and make better use of the approximation ability of neural networks, thus resulting in higher accuracy of grey-box modeling. By combination the prior knowledge and systematic equations into ESN state pool, structure approaching neural network (SAAN) is established based on system feature block, and it is given actual significance. Then the optimal fundamental genes were chosen through recursive least square method with stepwise regression analysis to optimize the structure of SANN, so as to get the grey-box model. Detailed process of modeling was described in modeling of tubular polymerization reaction in laboratory scale. The simulation result proves that the approach is effective.ocesses heat exchanger network synthesis by taking place.

  16. Dissecting lipid metabolism in meibomian glands of humans and mice: An integrative study reveals a network of metabolic reactions not duplicated in other tissues.

    Science.gov (United States)

    Butovich, Igor A; McMahon, Anne; Wojtowicz, Jadwiga C; Lin, Feng; Mancini, Ronald; Itani, Kamel

    2016-06-01

    Lipids comprise the bulk of the meibomian gland secretion (meibum) which is produced by meibocytes. Complex arrays of lipogenic reactions in meibomian glands, which we collectively call meibogenesis, have not been explored on a molecular level yet. Our goals were to elucidate the possible biosynthetic pathways that underlie the generation of meibum, reveal similarities in, and differences between, lipid metabolism in meibomian glands and other organs and tissues, and integrate meibomian gland studies into the field of general metabolomics. Specifically, we have conducted detailed analyses of human and mouse specimens using genomic, immunohistochemical, and lipidomic approaches. Among equally highly expressed genes found in meibomian glands of both species were those related to fatty acid elongation, branching, desaturation, esterification, reduction of fatty acids to alcohols, and cholesterol biosynthesis. Importantly, corresponding lipid products were detected in meibum of both species using lipidomic approaches. For the first time, a cohesive, unifying biosynthetic scheme that connects genomic, lipidomic, and immunohistochemical observations is outlined and discussed. PMID:27032494

  17. Study of castor oil polyurethane - poly(methyl methacrylate semi-interpenetrating polymer network (SIPN reaction parameters using a 2³ factorial experimental design

    Directory of Open Access Journals (Sweden)

    Fernanda Oliveira Vieira da Cunha

    2004-12-01

    Full Text Available In this work was employed a 2³ factorial experiment design to evaluate the castor oil polyurethane-poly(methyl methacrylate semi-IPN synthesis. The reaction parameters used as independent variables were NCO/OH molar ratio, polyurethane polymerization time and methyl methacrylate (MMA content. The semi-IPNs were cured over 28 h using two thermal treatments. The polymers were characterized by infrared and Raman spectroscopy, thermal analysis and swelling profiles in n-hexane. The glass transition temperature (Tg and the swelling were more affect by the NCO/OH molar ratio variation. The semi-IPNs showed Tg from - 27 to - 6 °C and the swelling range was from 3 to 22%, according to the crosslink density. The IPN mechanical properties were dependent on the cure temperature and MMA content in it. Lower elastic modulus values were observed in IPNs cured at room temperature.

  18. Studies of the charge instabilities in the complex nano-objects: clusters and bio-molecular systems

    International Nuclear Information System (INIS)

    For the last 6 years, my main research works focused on i) the Coulomb instabilities and the fragmentation processes of fullerenes and clusters of fullerenes ii) the stability and the reactivity of complex bio-molecular systems. Concerning the clusters of fullerenes, which are van der Waals type clusters, we have shown that the multiply charged species, obtained in collisions with slow highly charged ions, keep their structural properties but become very good electric conductor. In another hand, with the aim to understand the role of the biologic environment at the molecular scale in the irradiation damage of complex biomolecules, we have studied the charge stabilities of clusters of small biomolecules and the dissociation processes of larger nano-hydrated biomolecules. Theses studies have shown that first, specific molecular recognition mechanisms continue to exist in gas phase and secondly, a small and very simple biochemical environment is enough to change the dynamics of instabilities. (author)

  19. Evaluation of Pore Networks in Caprocks at Geologic Storage Sites: A Combined Study using High Temperature and Pressure Reaction Experiments, Small Angle Neutron Scattering, and Focused Ion Beam-Scanning Electron Microscopy

    Science.gov (United States)

    Mouzakis, K. M.; Sitchler, A.; Wang, X.; McCray, J. E.; Kaszuba, J. P.; Rother, G.; Dewers, T. A.; Heath, J. E.

    2011-12-01

    Low permeability rock units, often shales or mudstones, that overlie geologic formations under consideration for CO2 sequestration will help contain injected CO2. CO2 that does flow through these rocks will dissolve into the porewaters, creating carbonic acid lowering the pH. This perturbation of the system may result in mineral dissolution or precipitation, which can change the pore structure and impact the flow properties of the caprocks. In order to investigate the impacts that reaction can have on caprock pore structure, we performed a combination of high pressure high temperature reaction experiments, small angle neutron scattering (SANS) experiments and high resolution focused ion beam-scanning electron microscope (FIB-SEM) imaging on samples from the Gothic shale and Marine Tuscaloosa Group. Small angle neutron scattering was performed on unreacted and reacted caprocks at the High Flux Isotope Reactor at Oak Ridge National Laboratory. New precipitates and pores are observed in high-resolution images of the reacted samples. The precipitates have been preliminarily identified as gypsum or anhydrite, and sulfide minerals. Results from small angle neutron scattering, a technique that provides information about pores and pore/mineral interfaces at scales ~ 5 to 300 nm, show an increased porosity and specific surface area after reaction with brine and CO2. However, there appear to be differences in how the pore networks change between the two samples that are related to sample mineralogy and original pore network structure. Changes to pores and formation of new pores may lead to different capillary sealing behavior and permeability. This combination of controlled laboratory experiments, neutron scattering and high-resolution imaging provides detailed information about the geochemical processes that occur at the pore scale as CO2 reacts with rocks underground. Such information is integral to the evaluation of large-scale CO2 sequestration as a feasible technology

  20. Comparative effect of physicomechanical and biomolecular cues on zone-specific chondrogenic differentiation of mesenchymal stem cells.

    Science.gov (United States)

    Moeinzadeh, Seyedsina; Pajoum Shariati, Seyed Ramin; Jabbari, Esmaiel

    2016-06-01

    Current tissue engineering approaches to regeneration of articular cartilage rarely restore the tissue to its normal state because the generated tissue lacks the intricate zonal organization of the native cartilage. Zonal regeneration of articular cartilage is hampered by the lack of knowledge for the relation between physical, mechanical, and biomolecular cues and zone-specific chondrogenic differentiation of progenitor cells. This work investigated in 3D the effect of TGF-β1, zone-specific growth factors, optimum matrix stiffness, and adding nanofibers on the expression of chondrogenic markers specific to the superficial, middle, and calcified zones of articular cartilage by the differentiating human mesenchymal stem cells (hMSCs). Growth factors included BMP-7, IGF-1, and hydroxyapatite (HA) for the superficial, middle, and calcified zones, respectively; optimum matrix stiffness was 80 kPa, 2.1 MPa, and 320 MPa; and nanofibers were aligned horizontal, random, and perpendicular to the gel surface. hMSCs with zone-specific cell densities were encapsulated in engineered hydrogels and cultured with or without TGF-β1, zone-specific growth factor, optimum matrix modulus, and fiber addition and cultured in basic chondrogenic medium. The expression of encapsulated cells was measured by mRNA, protein, and biochemical analysis. Results indicated that zone-specific matrix stiffness had a dominating effect on chondrogenic differentiation of hMSCs to the superficial and calcified zone phenotypes. Addition of aligned nanofibers parallel to the direction of gel surface significantly enhanced expression of Col II in the superficial zone chondrogenic differentiation of hMSCs. Conversely, biomolecular factor IGF-1 in combination with TGF-β1 had a dominating effect on the middle zone chondrogenic differentiation of hMSCs. Results of this work could potentially lead to the development of multilayer grafts mimicking the zonal organization of articular cartilage. PMID:27038568

  1. A Unified Monte Carlo Treatment of Gas-Grain Chemistry for Large Reaction Networks. II. A Multiphase Gas-Surface-Layered Bulk Model

    CERN Document Server

    Vasyunin, A I

    2012-01-01

    The observed gas-phase molecular inventory of hot cores is believed to be significantly impacted by the products of chemistry in interstellar ices. In this study, we report the construction of a full macroscopic Monte Carlo model of both the gas-phase chemistry and the chemistry occurring in the icy mantles of interstellar grains. Our model treats icy grain mantles in a layer-by-layer manner, which incorporates laboratory data on ice desorption correctly. The ice treatment includes a distinction between a reactive ice surface and an inert bulk. The treatment also distinguishes between zeroth and first order desorption, and includes the entrapment of volatile species in more refractory ice mantles. We apply the model to the investigation of the chemistry in hot cores, in which a thick ice mantle built up during the previous cold phase of protostellar evolution undergoes surface reactions and is eventually evaporated. For the first time, the impact of a detailed multilayer approach to grain mantle formation on ...

  2. A UNIFIED MONTE CARLO TREATMENT OF GAS-GRAIN CHEMISTRY FOR LARGE REACTION NETWORKS. II. A MULTIPHASE GAS-SURFACE-LAYERED BULK MODEL

    International Nuclear Information System (INIS)

    The observed gas-phase molecular inventory of hot cores is believed to be significantly impacted by the products of chemistry in interstellar ices. In this study, we report the construction of a full macroscopic Monte Carlo model of both the gas-phase chemistry and the chemistry occurring in the icy mantles of interstellar grains. Our model treats icy grain mantles in a layer-by-layer manner, which incorporates laboratory data on ice desorption correctly. The ice treatment includes a distinction between a reactive ice surface and an inert bulk. The treatment also distinguishes between zeroth- and first-order desorption, and includes the entrapment of volatile species in more refractory ice mantles. We apply the model to the investigation of the chemistry in hot cores, in which a thick ice mantle built up during the previous cold phase of protostellar evolution undergoes surface reactions and is eventually evaporated. For the first time, the impact of a detailed multilayer approach to grain mantle formation on the warm-up chemistry is explored. The use of a multilayer ice structure has a mixed impact on the abundances of organic species formed during the warm-up phase. For example, the abundance of gaseous HCOOCH3 is lower in the multilayer model than in previous grain models that do not distinguish between layers (so-called two phase models). Other gaseous organic species formed in the warm-up phase are affected slightly. Finally, we find that the entrapment of volatile species in water ice can explain the two-jump behavior of H2CO previously found in observations of protostars.

  3. High energy halogen atom reactions activated by nuclear transformations. Progress report, February 15, 1980-February 14, 1981

    International Nuclear Information System (INIS)

    The stereochemistry of high energy 18F, /sup 34m/Cl, and 76Br substitution reactions involving enantiomeric molecules in the gas and condensed phase is studied. The gas to condensed state transition in halogen high energy chemistry, involving chlorine, bromine, and iodine activated by the (n,γ) and (I.T.) processes in halomethanes, saturated and unsaturated hydrocarbons is being investigated in more detail. Special attention is given to defining the nature of the enhancement yields in the condensed phase. High energy halogen reactions in liquid and frozen aqueous solutions of organic and biomolecular solutes are studied in an attempt to learn more about these reactions. The applications of high energy chemistry techniques and theory to neutron activation analysis of biological systems are being continued. Special attention is given to developing procedures for trace molecular determinations in biological systems. The applications of hot halogen atoms as indicators of solute-solute interactions in liquid and frozen aqueous solutions of halogenated bases and nucleosides are being developed. Experiments are designed to explain the mechanisms of the radioprotection offered biomolecular solutes trapped within the frozen ice lattice. Reactions of bromine and iodine activated by isomeric transition with halogenated biomolecular solutes in liquid and frozen aqueous solutions are studied. The high energy reactions of iodine with the isomers of pentene have been studied in low pressure gaseous systems employing additives and rare gas moderators and liquid systems. Reactivity of excited complex formation and structural effects of electrophilic iodine attack on the pi-bond systems are studied

  4. Networks in Cognitive Science

    CERN Document Server

    Baronchelli, Andrea; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

    2013-01-01

    Networks of interconnected nodes have long played a key role in cognitive science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions or collaborations among scientists. Today, the inclusion of network theory into cognitive sciences, and the expansion of complex systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the cognitive sciences.

  5. Binomial moment equations for stochastic reaction systems.

    Science.gov (United States)

    Barzel, Baruch; Biham, Ofer

    2011-04-15

    A highly efficient formulation of moment equations for stochastic reaction networks is introduced. It is based on a set of binomial moments that capture the combinatorics of the reaction processes. The resulting set of equations can be easily truncated to include moments up to any desired order. The number of equations is dramatically reduced compared to the master equation. This formulation enables the simulation of complex reaction networks, involving a large number of reactive species much beyond the feasibility limit of any existing method. It provides an equation-based paradigm to the analysis of stochastic networks, complementing the commonly used Monte Carlo simulations. PMID:21568538

  6. GraphAlignment: Bayesian pairwise alignment of biological networks

    Directory of Open Access Journals (Sweden)

    Kolář Michal

    2012-11-01

    Full Text Available Abstract Background With increased experimental availability and accuracy of bio-molecular networks, tools for their comparative and evolutionary analysis are needed. A key component for such studies is the alignment of networks. Results We introduce the Bioconductor package GraphAlignment for pairwise alignment of bio-molecular networks. The alignment incorporates information both from network vertices and network edges and is based on an explicit evolutionary model, allowing inference of all scoring parameters directly from empirical data. We compare the performance of our algorithm to an alternative algorithm, Græmlin 2.0. On simulated data, GraphAlignment outperforms Græmlin 2.0 in several benchmarks except for computational complexity. When there is little or no noise in the data, GraphAlignment is slower than Græmlin 2.0. It is faster than Græmlin 2.0 when processing noisy data containing spurious vertex associations. Its typical case complexity grows approximately as O(N2.6. On empirical bacterial protein-protein interaction networks (PIN and gene co-expression networks, GraphAlignment outperforms Græmlin 2.0 with respect to coverage and specificity, albeit by a small margin. On large eukaryotic PIN, Græmlin 2.0 outperforms GraphAlignment. Conclusions The GraphAlignment algorithm is robust to spurious vertex associations, correctly resolves paralogs, and shows very good performance in identification of homologous vertices defined by high vertex and/or interaction similarity. The simplicity and generality of GraphAlignment edge scoring makes the algorithm an appropriate choice for global alignment of networks.

  7. Learning Networks, Networked Learning

    OpenAIRE

    Sloep, Peter; Berlanga, Adriana

    2011-01-01

    Learning Networks are on-line social networks through which users share knowledge with each other and jointly develop new knowledge. This way, Learning Networks may enrich the experience of formal, school-based learning and form a viable setting for professional development. Although networked learning enjoys an increasing interest, many questions remain on how exactly learning in such networked contexts can contribute to successful education and training. Put differently, how should networke...

  8. Acrolein: Sources, metabolism, and biomolecular interactions relevant to human health and disease

    OpenAIRE

    Stevens, Jan F.; Maier, Claudia S.

    2008-01-01

    Acrolein (2-propenal) is ubiquitously present in (cooked) foods and in the environment. It is formed from carbohydrates, vegetable oils and animal fats, amino acids during heating of foods, and by combustion of petroleum fuels and biodiesel. Chemical reactions responsible for release of acrolein include heat-induced dehydration of glycerol, retro-aldol cleavage of dehydrated carbohydrates, lipid peroxidation of polyunsaturated fatty acids, and Strecker degradation of methionine and threonine....

  9. Piezonuclear Reactions

    CERN Document Server

    Cardone, Fabio; Petrucci, Andrea

    2010-01-01

    In this paper, we deal with the subject of piezonuclear reactions, namely nuclear reactions (of new type) triggered by pressure waves. We discuss the experimental evidences obtained in the last two decades, which can be summarized essentially as follows: experiments in cavitation of liquids, where transmutation of elements, creation of elements and emission of neutrons have been observed; emission of neutrons in brittle failure of solids subjected to mechanical pressure; alteration of the lifetime of un unstable element (thorium) subjected to cavitation. A theoretical model to explain these facts is proposed. Future perspectives of these experimental and theoretical investigations are also underlined.

  10. Reaction mechanisms

    International Nuclear Information System (INIS)

    The 1988 progress report of the Reaction Mechanisms laboratory (Polytechnic School, France), is presented. The research topics are: the valence bond methods, the radical chemistry, the modelling of the transition states by applying geometric constraints, the long range interactions (ion - molecule) in gaseous phase, the reaction sites in gaseous phase and the mass spectroscopy applications. The points of convergence between the investigations of the mass spectroscopy and the theoretical chemistry teams, as well as the purposes guiding the research programs, are discussed. The published papers, the conferences, the congress communications and the thesis, are also reported

  11. PREFACE: 1st Nano-IBCT Conference 2011 - Radiation Damage of Biomolecular Systems: Nanoscale Insights into Ion Beam Cancer Therapy

    Science.gov (United States)

    Huber, Bernd A.; Malot, Christiane; Domaracka, Alicja; Solov'yov, Andrey V.

    2012-07-01

    The 1st Nano-IBCT Conference entitled 'Radiation Damage in Biomolecular Systems: Nanoscale Insights into Ion Beam Cancer Therapy' was held in Caen, France, in October 2011. The Meeting was organised in the framework of the COST Action MP1002 (Nano-IBCT) which was launched in December 2010 (http://fias.uni-frankfurt.de/nano-ibct). This action aims to promote the understanding of mechanisms and processes underlying the radiation damage of biomolecular systems at the molecular and nanoscopic level and to use the findings to improve the strategy of Ion Beam Cancer Therapy. In the hope of achieving this, participants from different disciplines were invited to represent the fields of physics, biology, medicine and chemistry, and also included those from industry and the operators of hadron therapy centres. Ion beam therapy offers the possibility of excellent dose localization for treatment of malignant tumours, minimizing radiation damage in normal healthy tissue, while maximizing cell killing within the tumour. Several ion beam cancer therapy clinical centres are now operating in Europe and elsewhere. However, the full potential of such therapy can only be exploited by better understanding the physical, chemical and biological mechanisms that lead to cell death under ion irradiation. Considering a range of spatio-temporal scales, the proposed action therefore aims to combine the unique experimental and theoretical expertise available within Europe to acquire greater insight at the nanoscopic and molecular level into radiation damage induced by ion impact. Success in this endeavour will be both an important scientific breakthrough and give great impetus to the practical improvement of this innovative therapeutic technique. Ion therapy potentially provides an important advance in cancer therapy and the COST action MP1002 will be very significant in ensuring Europe's leadership in this field, providing the scientific background, required data and mechanistic insight which

  12. Event Detection and Sub-state Discovery from Bio-molecular Simulations Using Higher-Order Statistics: Application To Enzyme Adenylate Kinase

    OpenAIRE

    Ramanathan, Arvind; Savol, Andrej J.; Agarwal, Pratul K.; Chennubhotla, Chakra S.

    2012-01-01

    Biomolecular simulations at milli-second and longer timescales can provide vital insights into functional mechanisms. Since post-simulation analyses of such large trajectory data-sets can be a limiting factor in obtaining biological insights, there is an emerging need to identify key dynamical events and relating these events to the biological function online, that is, as simulations are progressing. Recently, we have introduced a novel computational technique, quasi-anharmonic analysis (QAA)...

  13. Context-dependent metabolic networks

    CERN Document Server

    Beguerisse-Díaz, Mariano; Oyarzún, Diego; Picó, Jesús; Barahona, Mauricio

    2016-01-01

    Cells adapt their metabolism to survive changes in their environment. We present a framework for the construction and analysis of metabolic reaction networks that can be tailored to reflect different environmental conditions. Using context-dependent flux distributions from Flux Balance Analysis (FBA), we produce directed networks with weighted links representing the amount of metabolite flowing from a source reaction to a target reaction per unit time. Such networks are analyzed with tools from network theory to reveal salient features of metabolite flows in each biological context. We illustrate our approach with the directed network of the central carbon metabolism of Escherichia coli, and study its properties in four relevant biological scenarios. Our results show that both flow and network structure depend drastically on the environment: networks produced from the same metabolic model in different contexts have different edges, components, and flow communities, capturing the biological re-routing of metab...

  14. Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

    Energy Technology Data Exchange (ETDEWEB)

    Trewhella, J.; Cross, T.A.; Unkefer, C.J. [eds.

    1994-12-01

    Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database.

  15. Stable isotope applications in biomolecular structure and mechanisms. A meeting to bring together producers and users of stable-isotope-labeled compounds to assess current and future needs

    International Nuclear Information System (INIS)

    Knowledge of biomolecular structure is a prerequisite for understanding biomolecular function, and stable isotopes play an increasingly important role in structure determination of biological molecules. The first Conference on Stable Isotope Applications in Biomolecular Structure and Mechanisms was held in Santa Fe, New Mexico, March 27--31, 1994. More than 120 participants from 8 countries and 44 institutions reviewed significant developments, discussed the most promising applications for stable isotopes, and addressed future needs and challenges. Participants focused on applications of stable isotopes for studies of the structure and function of proteins, peptides, RNA, and DNA. Recent advances in NMR techniques neutron scattering, EPR, and vibrational spectroscopy were highlighted in addition to the production and synthesis of labeled compounds. This volume includes invited speaker and poster presentations as well as a set of reports from discussion panels that focused on the needs of the scientific community and the potential roles of private industry, the National Stable Isotope Resource, and the National High Magnetic Field Laboratory in serving those needs. This is the leading abstract. Individual papers are processed separately for the database

  16. Histopathological, immunohistochemical and biomolecular diagnosis of myocarditis due to Clostridium chauvoei in a bovine

    Directory of Open Access Journals (Sweden)

    Renata Assis Casagrande

    2015-08-01

    Full Text Available The aim of this study was to report a case of clostridial myocarditis in a bovine in Brazil with emphasis on the pathological findings, isolation and molecular identification associated with the in situ localization of C. chauvoei. The animal, a male Brangus bull with nine months of age, was found dead without prior clinical signs. Multifocal and coalescent areas of necrosis were observed in the myocardium. Rod cells in the cardiac muscle fibers were positive immunostaining for C. chauvoei, while this bacterium was also isolated and identified by polymerase chain reaction (PCR.

  17. LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

    Energy Technology Data Exchange (ETDEWEB)

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

  18. Structure network analysis to gain insights into GPCR function.

    Science.gov (United States)

    Fanelli, Francesca; Felline, Angelo; Raimondi, Francesco; Seeber, Michele

    2016-04-15

    G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM-NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor. PMID:27068978

  19. Photoabsorption and resonance energy transfer phenomenon in CdTe-protein bioconjugates: an insight into QD-biomolecular interactions.

    Science.gov (United States)

    Vinayaka, Aaydha C; Thakur, Munna S

    2011-05-18

    Luminescent quantum dots (QDs) possess unique photophysical properties, which are advantageous in the development of new generation robust fluorescent probes based on Forster resonance energy transfer (FRET) phenomena. Bioconjugation of these QDs with biomolecules create hybrid materials having unique photophysical properties along with biological activity. The present study is aimed at characterizing QD bioconjugates in terms of optical behavior. Colloidal CdTe QDs capped with 3-mercaptopropionic acid (MPA) were conjugated to different proteins by the carbodiimide protocol using N-(3-dimethylaminopropyl)-N-ethylcarbodiimide hydrochloride (EDC) and a coupling reagent like N-hydroxysuccinimide (NHS). The photoabsorption of these QD-protein bioconjugates demonstrated an effective coupling of electronic orbitals of constituents. A linear variation in absorbance of bioconjugates at 330 nm proportionate to conjugation suggests a covalent attachment as confirmed by gel electrophoresis. A red shift in the fluorescence of bovine serum albumin (BSA) due to conjugation inferred a decrease in Stokes shift and solvent polarization effects on protein. A proportionate quenching in BSA fluorescence followed by an enhancement of QD fluorescence point toward nonradiative dipolar interactions. Further, reduction in photobleaching of BSA suggests QD-biomolecular interactions. Bioconjugation has significantly influenced the photoabsorption spectrum of QD bioconjugates suggesting the formation of a possible protein shell on the surface of QD. The experimental result suggests that these bioconjugates can be considered nanoparticle (NP) superstructures for the development of a new generation of robust nanoprobes. PMID:21452896

  20. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

    Directory of Open Access Journals (Sweden)

    Irena Cosic

    2016-06-01

    Full Text Available The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM. The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1 the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2 the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3 the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4 the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health.

  1. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model.

    Science.gov (United States)

    Cosic, Irena; Cosic, Drasko; Lazar, Katarina

    2016-01-01

    The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

  2. Extension of the CHARMM General Force Field to sulfonyl-containing compounds and its utility in biomolecular simulations.

    Science.gov (United States)

    Yu, Wenbo; He, Xibing; Vanommeslaeghe, Kenno; MacKerell, Alexander D

    2012-12-01

    Presented is an extension of the CHARMM General Force Field (CGenFF) to enable the modeling of sulfonyl-containing compounds. Model compounds containing chemical moieties such as sulfone, sulfonamide, sulfonate, and sulfamate were used as the basis for the parameter optimization. Targeting high-level quantum mechanical and experimental crystal data, the new parameters were optimized in a hierarchical fashion designed to maintain compatibility with the remainder of the CHARMM additive force field. The optimized parameters satisfactorily reproduced equilibrium geometries, vibrational frequencies, interactions with water, gas phase dipole moments, and dihedral potential energy scans. Validation involved both crystalline and liquid phase calculations showing the newly developed parameters to satisfactorily reproduce experimental unit cell geometries, crystal intramolecular geometries, and pure solvent densities. The force field was subsequently applied to study conformational preference of a sulfonamide based peptide system. Good agreement with experimental IR/NMR data further validated the newly developed CGenFF parameters as a tool to investigate the dynamic behavior of sulfonyl groups in a biological environment. CGenFF now covers sulfonyl group containing moieties allowing for modeling and simulation of sulfonyl-containing compounds in the context of biomolecular systems including compounds of medicinal interest. PMID:22821581

  3. Bi-stability of amplitude modulation AFM in air: deterministic and stochastic outcomes for imaging biomolecular systems

    International Nuclear Information System (INIS)

    The dynamics of the oscillating microcantilever for amplitude modulation atomic force microscopy (AM AFM) operating in air is well understood theoretically but the experimental outcomes are still emerging. We use double-stranded DNA on mica as a model biomolecular system for investigating the connection between theory and experiment. A demonstration that the switching between the two cantilever oscillation states is stochastic in nature is achieved, and it can be induced by means of topographical anomalies on the surface. Whether one or the other attractor basin is accessed depends on the tip-sample separation history used to achieve the imaging conditions, and we show that the behaviour is reproducible when the tip is stable and well characterized. Emergence of background noise occurs in certain regions of parameter space regardless of whether two cantilever oscillation states coexist. The low state has been explored in detail and we note that at low to intermediate values of the free amplitude, noise-free imaging is achieved. The outcomes shown here are general and demonstrate that a thorough and systematic experimental approach in conjunction with standard modelling gives insight into the mechanisms behind image contrast formation in AM AFM in air.

  4. Environmental Light and Its Relationship with Electromagnetic Resonances of Biomolecular Interactions, as Predicted by the Resonant Recognition Model

    Science.gov (United States)

    Cosic, Irena; Cosic, Drasko; Lazar, Katarina

    2016-01-01

    The meaning and influence of light to biomolecular interactions, and consequently to health, has been analyzed using the Resonant Recognition Model (RRM). The RRM proposes that biological processes/interactions are based on electromagnetic resonances between interacting biomolecules at specific electromagnetic frequencies within the infra-red, visible and ultra-violet frequency ranges, where each interaction can be identified by the certain frequency critical for resonant activation of specific biological activities of proteins and DNA. We found that: (1) the various biological interactions could be grouped according to their resonant frequency into super families of these functions, enabling simpler analyses of these interactions and consequently analyses of influence of electromagnetic frequencies to health; (2) the RRM spectrum of all analyzed biological functions/interactions is the same as the spectrum of the sun light on the Earth, which is in accordance with fact that life is sustained by the sun light; (3) the water is transparent to RRM frequencies, enabling proteins and DNA to interact without loss of energy; (4) the spectrum of some artificial sources of light, as opposed to the sun light, do not cover the whole RRM spectrum, causing concerns for disturbance to some biological functions and consequently we speculate that it can influence health. PMID:27367714

  5. Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation

    Energy Technology Data Exchange (ETDEWEB)

    Lei, Huan; Yang, Xiu; Zheng, Bin; Lin, Guang; Baker, Nathan A.

    2015-12-31

    Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance of the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.

  6. Preparation of LiNbO{sub 3} nanoparticles using poly(L-lysine) as a biomolecular additive

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Youngjoon; Lee, Sang-Yup, E-mail: leessy@yonsei.ac.kr

    2014-03-01

    The effects of poly(L-lysine) as a biomolecular additive on the synthesis of LiNbO{sub 3} were investigated. PLL is a widely-studied biomolecule containing amino groups that can interact with solid inorganic clusters. The addition of PLL to a LiNbO{sub 3} precursor solution enhanced the aggregation of the produced LiNbO{sub 3} nanoparticles. This aggregation was induced by the electrical attraction of PLL with LiNbO{sub 3} nanoparticles, and was enhanced with increasing PLL molecular weight. Furthermore, the association of PLL with LiNbO{sub 3} nanoparticles was increased by the addition of methanol, which enhanced the miscibility of PLL with the precursor solution working as a co-solvent. The LiNbO{sub 3} nanoparticles generated with PLL exhibited piezoelectric properties without post-thermal treatment, suggesting that PLL contributes to the piezoelectricity. The results of this study are intriguing in terms of the potential for diverse engineering nanomaterials synthesis through a biomolecule that can also improve the physicochemical properties. - Highlights: • Piezoelectric lithium niobate nanoparticles were synthesized with poly(L-lysine). • High molecular weight poly(L-lysine) and co-solvent promoted aggregation of nanoparticles. • Poly(L-lysine) enhanced piezoelectricity of lithium niobate nanoparticles.

  7. Preparation of LiNbO3 nanoparticles using poly(L-lysine) as a biomolecular additive

    International Nuclear Information System (INIS)

    The effects of poly(L-lysine) as a biomolecular additive on the synthesis of LiNbO3 were investigated. PLL is a widely-studied biomolecule containing amino groups that can interact with solid inorganic clusters. The addition of PLL to a LiNbO3 precursor solution enhanced the aggregation of the produced LiNbO3 nanoparticles. This aggregation was induced by the electrical attraction of PLL with LiNbO3 nanoparticles, and was enhanced with increasing PLL molecular weight. Furthermore, the association of PLL with LiNbO3 nanoparticles was increased by the addition of methanol, which enhanced the miscibility of PLL with the precursor solution working as a co-solvent. The LiNbO3 nanoparticles generated with PLL exhibited piezoelectric properties without post-thermal treatment, suggesting that PLL contributes to the piezoelectricity. The results of this study are intriguing in terms of the potential for diverse engineering nanomaterials synthesis through a biomolecule that can also improve the physicochemical properties. - Highlights: • Piezoelectric lithium niobate nanoparticles were synthesized with poly(L-lysine). • High molecular weight poly(L-lysine) and co-solvent promoted aggregation of nanoparticles. • Poly(L-lysine) enhanced piezoelectricity of lithium niobate nanoparticles

  8. Biomolecular urease thin films grown by laser techniques for blood diagnostic applications

    International Nuclear Information System (INIS)

    Matrix assisted pulsed laser evaporation (MAPLE) was used for growing urease thin films designed for bio-sensor applications in clinical diagnostics. The targets exposed to laser radiation were made from a frozen composite manufactured by dissolving biomaterials in distilled water. We used a UV KrF* (λ = 248 nm, τFWHM ≅ 30 ns, ν = 10 Hz) excimer source for multipulse laser irradiation of the frozen targets cooled with Peltier elements. The laser source was operated at an incident fluence of 0.4 J/cm2. Urease activity and kinetics were assayed by the Worthington method that monitors urea hydrolysis by coupling ammonia production to a glutamate dehydrogenase reaction. A decrease in absorbance was measured at 340 nm and correlated with the enzymatic activity of urease. We show that the urease films obtained by MAPLE techniques remain active up to three months after deposition.

  9. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011). Learning Networks, Networked Learning. Presentation at Annual Assembly of the European Society for the Systemic Innovation of Education - ESSIE. May, 27, 2011, Leuven, Belgium: Open University in the Netherlands.

  10. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  11. Nuclear reactions

    International Nuclear Information System (INIS)

    Nuclear reactions' marks a new development in the study of television as an agency of public policy debate. During the Eighties, nuclear energy became a major international issue. The disasters at Three-mile Island and Chernobyl created a global anxiety about its risks and a new sensitivity to it among politicians and journalists. This book is a case-study into documentary depictions of nuclear energy in television and video programmes and into the interpretations and responses of viewers drawn from many different occupational groupings. How are the complex and specialist arguments about benefit, risk and proof conveyed through the different conventions of commentary, interview and film sequence? What symbolic associations does the visual language of television bring to portrayals of the issue? And how do viewers make sense of various and conflicting accounts, connecting what they see and hear on the screen with their pre-existing knowledge, experience and 'civic' expectations. The authors examine some of the contrasting forms and themes which have been used by programme makers to explain and persuade, and then give a sustained analysis of the nature and sources of viewers' own accounts. 'Nuclear Reactions' inquires into the public meanings surrounding energy and the environment, spelling out in its conclusion some of the implications for future media treatments of this issue. It is also a key contribution to the international literature on 'television knowledge' and the processes of active viewing. (author)

  12. Ion interaction with biomolecular systems and the effect of the environment

    Science.gov (United States)

    Domaracka, Alicja; Capron, Michael; Maclot, Sylvain; Chesnel, Jean-Yves; Méry, Alain; Poully, Jean-Christophe; Rangama, Jimmy; Adoui, Lamri; Rousseau, Patrick; Huber, Bernd A.

    2012-07-01

    To fully understand the mechanisms of radiation damage in living tissues, a detailed knowledge of the processes occurring at the molecular level is needed. In the gas phase, most of the investigations concerning the ionization and fragmentation of biologically relevant molecular systems are performed with isolated molecules. The importance of such studies is limited to the intrinsic properties of these molecules because of the lack of a chemical environment. To probe the effect of such an environment on the behavior of small biomolecules under irradiation, the molecules (α-amino acids, adenine) were embedded into clusters. The present results, obtained with multiply charged ions, clearly indicate the protective role of the clusters since the total fragmentation yield is reduced for all systems. The surrounding molecules allow for a redistribution of the excess energy and of the charge within the cluster. In the case of adenine clusters, a new fragmentation channel is identified. Moreover, for hydrated adenine clusters, low-energy ion induced chemical reactions are observed, namely the proton transfer from the water cluster to the adenine molecule.

  13. Ion interaction with biomolecular systems and the effect of the environment

    International Nuclear Information System (INIS)

    To fully understand the mechanisms of radiation damage in living tissues, a detailed knowledge of the processes occurring at the molecular level is needed. In the gas phase, most of the investigations concerning the ionization and fragmentation of biologically relevant molecular systems are performed with isolated molecules. The importance of such studies is limited to the intrinsic properties of these molecules because of the lack of a chemical environment. To probe the effect of such an environment on the behavior of small biomolecules under irradiation, the molecules (α-amino acids, adenine) were embedded into clusters. The present results, obtained with multiply charged ions, clearly indicate the protective role of the clusters since the total fragmentation yield is reduced for all systems. The surrounding molecules allow for a redistribution of the excess energy and of the charge within the cluster. In the case of adenine clusters, a new fragmentation channel is identified. Moreover, for hydrated adenine clusters, low-energy ion induced chemical reactions are observed, namely the proton transfer from the water cluster to the adenine molecule.

  14. Membraneless organelles can melt nucleic acid duplexes and act as biomolecular filters

    Science.gov (United States)

    Nott, Timothy J.; Craggs, Timothy D.; Baldwin, Andrew J.

    2016-06-01

    Membraneless organelles are cellular compartments made from drops of liquid protein inside a cell. These compartments assemble via the phase separation of disordered regions of proteins in response to changes in the cellular environment and the cell cycle. Here we demonstrate that the solvent environment within the interior of these cellular bodies behaves more like an organic solvent than like water. One of the most-stable biological structures known, the DNA double helix, can be melted once inside the liquid droplet, and simultaneously structures formed from regulatory single-stranded nucleic acids are stabilized. Moreover, proteins are shown to have a wide range of absorption or exclusion from these bodies, and can act as importers for otherwise-excluded nucleic acids, which suggests the existence of a protein-mediated trafficking system. A common strategy in organic chemistry is to utilize different solvents to influence the behaviour of molecules and reactions. These results reveal that cells have also evolved this capability by exploiting the interiors of membraneless organelles.

  15. REACH coarse-grained biomolecular simulation: transferability between different protein structural classes.

    Science.gov (United States)

    Moritsugu, Kei; Smith, Jeremy C

    2008-08-01

    Coarse graining of protein interactions provides a means of simulating large biological systems. The REACH (Realistic Extension Algorithm via Covariance Hessian) coarse-graining method, in which the force constants of a residue-scale elastic network model are calculated from the variance-covariance matrix obtained from atomistic molecular dynamics (MD) simulation, involves direct mapping between scales without the need for iterative optimization. Here, the transferability of the REACH force field is examined between protein molecules of different structural classes. As test cases, myoglobin (all alpha), plastocyanin (all beta), and dihydrofolate reductase (alpha/beta) are taken. The force constants derived are found to be closely similar in all three proteins. An MD version of REACH is presented, and low-temperature coarse-grained (CG) REACH MD simulations of the three proteins are compared with atomistic MD results. The mean-square fluctuations of the atomistic MD are well reproduced by the CGMD. Model functions for the CG interactions, derived by averaging over the three proteins, are also shown to produce fluctuations in good agreement with the atomistic MD. The results indicate that, similarly to the use of atomistic force fields, it is now possible to use a single, generic REACH force field for all protein studies, without having first to derive parameters from atomistic MD simulation for each individual system studied. The REACH method is thus likely to be a reliable way of determining spatiotemporal motion of a variety of proteins without the need for expensive computation of long atomistic MD simulations. PMID:18469078

  16. Dynamic analysis of biochemical network using complex network method

    Directory of Open Access Journals (Sweden)

    Wang Shuqiang

    2015-01-01

    Full Text Available In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger information capacity and is more efficient in information transmission. This is consistent with theory of evolution.

  17. Biomolecular Analysis Capability for Cellular and Omics Research on the International Space Station

    Science.gov (United States)

    Guinart-Ramirez, Y.; Cooley, V. M.; Love, J. E.

    2016-01-01

    International Space Station (ISS) assembly complete ushered a new era focused on utilization of this state-of-the-art orbiting laboratory to advance science and technology research in a wide array of disciplines, with benefits to Earth and space exploration. ISS enabling capability for research in cellular and molecular biology includes equipment for in situ, on-orbit analysis of biomolecules. Applications of this growing capability range from biomedicine and biotechnology to the emerging field of Omics. For example, Biomolecule Sequencer is a space-based miniature DNA sequencer that provides nucleotide sequence data for entire samples, which may be used for purposes such as microorganism identification and astrobiology. It complements the use of WetLab-2 SmartCycler"TradeMark", which extracts RNA and provides real-time quantitative gene expression data analysis from biospecimens sampled or cultured onboard the ISS, for downlink to ground investigators, with applications ranging from clinical tissue evaluation to multigenerational assessment of organismal alterations. And the Genes in Space-1 investigation, aimed at examining epigenetic changes, employs polymerase chain reaction to detect immune system alterations. In addition, an increasing assortment of tools to visualize the subcellular distribution of tagged macromolecules is becoming available onboard the ISS. For instance, the NASA LMM (Light Microscopy Module) is a flexible light microscopy imaging facility that enables imaging of physical and biological microscopic phenomena in microgravity. Another light microscopy system modified for use in space to image life sciences payloads is initially used by the Heart Cells investigation ("Effects of Microgravity on Stem Cell-Derived Cardiomyocytes for Human Cardiovascular Disease Modeling and Drug Discovery"). Also, the JAXA Microscope system can perform remotely controllable light, phase-contrast, and fluorescent observations. And upcoming confocal microscopy

  18. Study on Disproportionation Reaction of FCC Gasoline on Acid Catalyst

    Institute of Scientific and Technical Information of China (English)

    Xu Youhao; Wang Xieqing

    2004-01-01

    Based on the experimental data relating to the reaction of FCC gasoline on acid catalyst the analysis of product distribution, and composition of gasoline and diesel fractions have been analyzed. The occurrence of disproportionation reaction of FCC gasoline on acid catalyst and the network of disproportionation reaction have been identified. Study has also shown that different reaction temperatures can result in different pathways of disproportionation reactions on acid catalyst.

  19. Inhibition of zinc-dependent peptidases by Maillard reaction products

    OpenAIRE

    Missagia de Marco, Leticia

    2015-01-01

    The Maillard reaction is a network of different non-enzymatic reactions between carbonyl groups of reducing sugars and amino groups from amino acids, peptides, or proteins, which progresses in three major stages and originates a very heterogeneous mixture of reaction products. It is also known as non-enzymatic browning, due to the brown macromolecular pigments formed in the final stage of the reaction. The chemistry underlying the Maillard reaction is complex. It encloses not only one reactio...

  20. Network Potentials

    OpenAIRE

    Chakrabarti, Subhadip; Gilles, Robert Paul

    2005-01-01

    A network payoff function assigns a utility to all participants in a (social) network. In this paper we discuss properties of such network payoff functions that guarantee the existence of certain types of pairwise stable networks and the convergence of certain network formation processes. In particular we investigate network payoff functions that admit an exact network potential or an ordinal network potential. We relate these network potentials to exact and ordinal potentials of a non-cooper...

  1. Chain reaction

    International Nuclear Information System (INIS)

    Chain Reaction is a work of recent American political history. It seeks to explain how and why America came to depend so heavily on its experts after World War II, how those experts translated that authority into political clout, and why that authority and political discretion declined in the 1970s. The author's research into the internal memoranda of the Atomic Energy Commission substantiates his argument in historical detail. It was not the ravages of American anti-intellectualism, as so many scholars have argued, that brought the experts back down to earth. Rather, their decline can be traced to the very roots of their success after World War II. The need to over-state anticipated results in order to garner public support, incessant professional and bureaucratic specialization, and the sheer proliferation of expertise pushed arcane and insulated debates between experts into public forums at the same time that a broad cross section of political participants found it easier to gain access to their own expertise. These tendencies ultimately undermined the political influence of all experts. (author)

  2. Applicability of carbon and boron nitride nanotubes as biosensors: Effect of biomolecular adsorption on the transport properties of carbon and boron nitride nanotubes

    Science.gov (United States)

    Zhong, Xiaoliang; Mukhopadhyay, Saikat; Gowtham, S.; Pandey, Ravindra; Karna, Shashi P.

    2013-04-01

    The effect of molecular adsorption on the transport properties of single walled carbon and boron nitride nanotubes (CNTs and BNNTs) is investigated using density functional theory and non-equilibrium Green's function methods. The calculated I-V characteristics predict noticeable changes in the conductivity of semiconducting BNNTs due to physisorption of nucleic acid base molecules. Specifically, guanine which binds to the side wall of BNNT significantly enhances its conductivity by introducing conduction channels near the Fermi energy of the bioconjugated system. For metallic CNTs, a large background current masks relatively small changes in current due to the biomolecular adsorption. The results therefore suggest the suitability of BNNTs for biosensing applications.

  3. Complex networks: Patterns of complexity

    Science.gov (United States)

    Pastor-Satorras, Romualdo; Vespignani, Alessandro

    2010-07-01

    The Turing mechanism provides a paradigm for the spontaneous generation of patterns in reaction-diffusion systems. A framework that describes Turing-pattern formation in the context of complex networks should provide a new basis for studying the phenomenon.

  4. Network Competition with Local Network

    OpenAIRE

    Oystein Fjeldstad; Moen, Espen R; Christian Riis

    2007-01-01

    Local network externalities are present when the network externalities associated with entering a certain network depends not only on the total number of agents in the network, but on the identity of the agents in the network. We explore the consequences of local network externalities within a framework where two networks compete on the Hotelling circle. We first show that local network externalities, in contrast to global network externalities, do not sharpen competition. Then we show that t...

  5. Asian collaboration on nuclear reaction data compilation

    International Nuclear Information System (INIS)

    Nuclear reaction data are essential for research and development in nuclear engineering, radiation therapy, nuclear physics and astrophysics. Experimental data must be compiled in a database and be accessible to nuclear data users. One of the nuclear reaction databases is the EXFOR database maintained by the International Network of Nuclear Reaction Data Centres (NRDC) under the auspices of the International Atomic Energy Agency. Recently, collaboration among the Asian NRDC members is being further developed under the support of the Asia-Africa Science Platform Program of the Japan Society for the Promotion of Science. We report the activity for three years to develop the Asian collaboration on nuclear reaction data compilation. (author)

  6. Using artificial neural network tools to analyze microbial biomarker data

    Energy Technology Data Exchange (ETDEWEB)

    Brandt, C.C.; Schryver, J.C.; Almeida, J.S.; Pfiffner, S.M.; Palumbo, A.V.

    2004-03-17

    A major challenge in the successful implementation of bioremediation is understanding the structure of the indigenous microbial community and how this structure is affected by environmental conditions. Culture-independent approaches that use biomolecular markers have become the key to comparative microbial community analysis. However, the analysis of biomarkers from environmental samples typically generates a large number of measurements. The large number and complex nonlinear relationships among these measurements makes conventional linear statistical analysis of the data difficult. New data analysis tools are needed to help understand these data. We adapted artificial neural network (ANN) tools for relating changes in microbial biomarkers to geochemistry. ANNs are nonlinear pattern recognition methods that can learn from experience to improve their performance. We have successfully applied these techniques to the analysis of membrane lipids and nucleic acid biomarker data from both laboratory and field studies. Although ANNs typically outperform linear data analysis techniques, the user must be aware of several considerations and issues to ensure that analysis results are not misleading: (1) Overfitting, especially in small sample size data sets; (2) Model selection; (3) Interpretation of analysis results; and (4) Availability of tools (code). This poster summarizes approaches for addressing each of these issues. The objectives are: (1) Develop new nonlinear data analysis tools for relating microbial biomolecular markers to geochemical conditions; (2) Apply these nonlinear tools to field and laboratory studies relevant to the NABIR Program; and (3) Provide these tools and guidance in their use to other researchers.

  7. Prebiotic metabolic networks?

    OpenAIRE

    Luisi, Pier Luigi

    2014-01-01

    A prebiotic origin of metabolism has been proposed as one of several scenarios for the origin of life. In their recent work, Ralser and colleagues (Keller et al, 2014) observe an enzyme‐free, metabolism‐like reaction network under conditions reproducing a possible prebiotic environment.

  8. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  9. Organic & Biomolecular Chemistry

    OpenAIRE

    Zhang, Wenyu; Bryson, David I.; Crumpton, Jason B.; Wynn, Jessica; Santos, Webster L.

    2013-01-01

    On-bead high-throughput screening of a medium-sized (1000_2000 Da) branched peptideboronic acid (BPBA) library consisting of 46 656 unique sequences against HIV-1 RRE RNA generated peptides with binding affinities in the low micromolar range. In particular, BPBA1 had a Kd of 1.4 _M with RRE IIB, preference for RNA over DNA (27 fold), and selectivity of up to >75 fold against a panel of RRE IIB variants. Structure_activity studies suggest that the boronic acid moiety and ͐branching in peptide...

  10. Abstractions for biomolecular computations

    CERN Document Server

    Okunoye, Babatunde O

    2008-01-01

    Deoxyribonucleic acid is increasingly being understood to be an informational molecule, capable of information processing.It has found application in the determination of non-deterministic algorithms and in the design of molecular computing devices. This is a theoretical analysis of the mathematical properties and relations of the molecules which constituting DNA, which explains in part why DNA is a successful computing molecule.

  11. Biomolecular computation for bionanotechnology

    CERN Document Server

    Liu, Jian-Qin

    2006-01-01

    Computers built with moleware? The drive toward non-silicon computing is underway, and this first-of-its-kind guide to molecular computation gives researchers a firm grasp of the technologies, biochemical details, and theoretical models at the cutting edge. It explores advances in molecular biology and nanotechnology and illuminates how the convergence of various technologies is propelling computational capacity beyond the limitations of traditional hardware technology and into the realm of moleware.

  12. Multiscale modeling of droplet interface bilayer membrane networks.

    Science.gov (United States)

    Freeman, Eric C; Farimani, Amir B; Aluru, Narayana R; Philen, Michael K

    2015-11-01

    Droplet interface bilayer (DIB) networks are considered for the development of stimuli-responsive membrane-based materials inspired by cellular mechanics. These DIB networks are often modeled as combinations of electrical circuit analogues, creating complex networks of capacitors and resistors that mimic the biomolecular structures. These empirical models are capable of replicating data from electrophysiology experiments, but these models do not accurately capture the underlying physical phenomena and consequently do not allow for simulations of material functionalities beyond the voltage-clamp or current-clamp conditions. The work presented here provides a more robust description of DIB network behavior through the development of a hierarchical multiscale model, recognizing that the macroscopic network properties are functions of their underlying molecular structure. The result of this research is a modeling methodology based on controlled exchanges across the interfaces of neighboring droplets. This methodology is validated against experimental data, and an extension case is provided to demonstrate possible future applications of droplet interface bilayer networks. PMID:26594262

  13. Controlling Hybridization Chain Reactions with pH.

    Science.gov (United States)

    Idili, Andrea; Porchetta, Alessandro; Amodio, Alessia; Vallée-Bélisle, Alexis; Ricci, Francesco

    2015-08-12

    By taking inspiration from nature, where self-organization of biomolecular species into complex systems is finely controlled through different stimuli, we propose here a rational approach by which the assembly and disassembly of DNA-based concatemers can be controlled through pH changes. To do so we used the hybridization chain reaction (HCR), a process that, upon the addition of an initiator strand, allows to create DNA-based concatemers in a controlled fashion. We re-engineered the functional units of HCR through the addition of pH-dependent clamp-like triplex-forming domains that can either inhibit or activate the polymerization reaction at different pHs. This allows to finely regulate the HCR-induced assembly and disassembly of DNA concatemers at either basic or acidic pHs in a reversible way. The strategies we present here appear particularly promising as novel tools to achieve better spatiotemporal control of self-assembly processes of DNA-based nanostructures. PMID:26177980

  14. Reactive biomolecular divergence in genetically altered yeast cells and isolated mitochondria as measured by biocavity laser spectroscopy : a rapid diagnostic method for studying cellular responses to stress and disease.

    Energy Technology Data Exchange (ETDEWEB)

    Yaffe, Michael P. (University of California, San Diego, CA); Gourley, Paul Lee; Copeland, Robert Guild; McDonald, Anthony Eugene; Hendricks, Judy K.; Naviaux, Robert K. (Univesity of California, San Diego, CA)

    2006-12-01

    We report an analysis of four strains of baker's yeast (Saccharomyces cerevisiae) using biocavity laser spectroscopy. The four strains are grouped in two pairs (wild type and altered), in which one strain differs genetically at a single locus, affecting mitochondrial function. In one pair, the wild-type rho+ and a rho0 strain differ by complete removal of mitochondrial DNA (mtDNA). In the second pair, the wild-type rho+ and a rho- strain differ by knock-out of the nuclear gene encoding Cox4, an essential subunit of cytochrome c oxidase. The biocavity laser is used to measure the biophysical optic parameter Deltalambda, a laser wavelength shift relating to the optical density of cell or mitochondria that uniquely reflects its size and biomolecular composition. As such, Deltalambda is a powerful parameter that rapidly interrogates the biomolecular state of single cells and mitochondria. Wild-type cells and mitochondria produce Gaussian-like distributions with a single peak. In contrast, mutant cells and mitochondria produce leptokurtotic distributions that are asymmetric and highly skewed to the right. These distribution changes could be self-consistently modeled with a single, log-normal distribution undergoing a thousand-fold increase in variance of biomolecular composition. These features reflect a new state of stressed or diseased cells that we call a reactive biomolecular divergence (RBD) that reflects the vital interdependence of mitochondria and the nucleus.

  15. Neural network computation with DNA strand displacement cascades.

    Science.gov (United States)

    Qian, Lulu; Winfree, Erik; Bruck, Jehoshua

    2011-07-21

    The impressive capabilities of the mammalian brain--ranging from perception, pattern recognition and memory formation to decision making and motor activity control--have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the 'intelligent' behaviour required for survival. However, the study of how molecules can 'think' has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically, experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment. PMID:21776082

  16. On thermonuclear reaction rates

    OpenAIRE

    Hans J. Haubold; Mathai, Arak Mathai

    1996-01-01

    Nuclear reactions govern major aspects of the chemical evolution of galaxies and stars. Analytic study of the reaction rates and reaction probability integrals is attempted here. Exact expressions for the reaction rates and reaction probability integrals for nuclear reactions in the cases of nonresonant, modified nonresonant, screened nonresonant and resonant cases are given. These are expressed in terms of H-functions, G-functions and in computable series forms. Computational aspects are als...

  17. Network Experiments

    OpenAIRE

    Michael Kosfeld

    2003-01-01

    This paper provides a survey of recent experimental work in eco- nomics focussing on social and economic networks.The experiments consider networks of coordination and cooperation,buyer-seller net- works,and network formation.

  18. Quantifying Systemic Evolutionary Changes by Color Coding Confidence-Scored PPI Networks

    Science.gov (United States)

    Dao, Phuong; Schönhuth, Alexander; Hormozdiari, Fereydoun; Hajirasouliha, Iman; Sahinalp, S. Cenk; Ester, Martin

    A current major challenge in systems biology is to compute statistics on biomolecular network motifs, since this can reveal significant systemic differences between organisms. We extend the “color coding” technique to weighted edge networks and apply it to PPI networks where edges are weighted by probabilistic confidence scores, as provided by the STRING database. This is a substantial improvement over the previously available studies on, still heavily noisy, binary-edge-weight data. Following up on such a study, we compute the expected number of occurrences of non-induced subtrees with k ≤ 9 vertices. Beyond the previously reported differences between unicellular and multicellular organisms, we reveal major differences between prokaryotes and unicellular eukaryotes. This establishes, for the first time on a statistically sound data basis, that evolutionary distance can be monitored in terms of elevated systemic arrangements.

  19. Spatial Networks

    OpenAIRE

    Barthelemy, Marc

    2010-01-01

    Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields ranging from urbanism t...

  20. Network Security

    OpenAIRE

    Sunil Kumar

    2012-01-01

    The rapid increase in computer, mobile applications and wireless networks has globally changed the features of network security. A series of Internet attack and fraudulent acts on companies and individual network have shown us that open computer networks have no immunity from intrusions. The traditional way of protecting computer networks, such as firewalls and software encryption are insufficient and ineffective. The wireless ad-hoc network is susceptible to physical attack or harm due to...

  1. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter;

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  2. Evaluation of biomolecular distributions in rat brain tissues by means of ToF-SIMS using a continuous beam of Ar clusters.

    Science.gov (United States)

    Nakano, Shusuke; Yokoyama, Yuta; Aoyagi, Satoka; Himi, Naoyuki; Fletcher, John S; Lockyer, Nicholas P; Henderson, Alex; Vickerman, John C

    2016-06-01

    Time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides detailed chemical structure information and high spatial resolution images. Therefore, ToF-SIMS is useful for studying biological phenomena such as ischemia. In this study, in order to evaluate cerebral microinfarction, the distribution of biomolecules generated by ischemia was measured with ToF-SIMS. ToF-SIMS data sets were analyzed by means of multivariate analysis for interpreting complex samples containing unknown information and to obtain biomolecular mapping indicated by fragment ions from the target biomolecules. Using conventional ToF-SIMS (primary ion source: Bi cluster ion), it is difficult to detect secondary ions beyond approximately 1000 u. Moreover, the intensity of secondary ions related to biomolecules is not always high enough for imaging because of low concentration even if the masses are lower than 1000 u. However, for the observation of biomolecular distributions in tissues, it is important to detect low amounts of biological molecules from a particular area of tissue. Rat brain tissue samples were measured with ToF-SIMS (J105, Ionoptika, Ltd., Chandlers Ford, UK), using a continuous beam of Ar clusters as a primary ion source. ToF-SIMS with Ar clusters efficiently detects secondary ions related to biomolecules and larger molecules. Molecules detected by ToF-SIMS were examined by analyzing ToF-SIMS data using multivariate analysis. Microspheres (45 μm diameter) were injected into the rat unilateral internal carotid artery (MS rat) to cause cerebral microinfarction. The rat brain was sliced and then measured with ToF-SIMS. The brain samples of a normal rat and the MS rat were examined to find specific secondary ions related to important biomolecules, and then the difference between them was investigated. Finally, specific secondary ions were found around vessels incorporating microspheres in the MS rat. The results suggest that important biomolecules related to cerebral

  3. Thermo-responsive cell culture carriers based on poly(vinyl methyl ether)—the effect of biomolecular ligands to balance cell adhesion and stimulated detachment

    Science.gov (United States)

    Teichmann, Juliane; Nitschke, Mirko; Pette, Dagmar; Valtink, Monika; Gramm, Stefan; Härtel, Frauke V.; Noll, Thomas; Funk, Richard H. W.; Engelmann, Katrin; Werner, Carsten

    2015-08-01

    Two established material systems for thermally stimulated detachment of adherent cells were combined in a cross-linked polymer blend to merge favorable properties. Through this approach poly(N-isopropylacrylamide) (PNiPAAm) with its superior switching characteristic was paired with a poly(vinyl methyl ether)-based composition that allows adjusting physico-chemical and biomolecular properties in a wide range. Beyond pure PNiPAAm, the proposed thermo-responsive coating provides thickness, stiffness and swelling behavior, as well as an apposite density of reactive sites for biomolecular functionalization, as effective tuning parameters to meet specific requirements of a particular cell type regarding initial adhesion and ease of detachment. To illustrate the strength of this approach, the novel cell culture carrier was applied to generate transplantable sheets of human corneal endothelial cells (HCEC). Sheets were grown, detached, and transferred onto planar targets. Cell morphology, viability and functionality were analyzed by immunocytochemistry and determination of transepithelial electrical resistance (TEER) before and after sheet detachment and transfer. HCEC layers showed regular morphology with appropriate TEER. Cells were positive for function-associated marker proteins ZO-1, Na+/K+-ATPase, and paxillin, and extracellular matrix proteins fibronectin, laminin and collagen type IV before and after transfer. Sheet detachment and transfer did not impair cell viability. Subsequently, a potential application in ophthalmology was demonstrated by transplantation onto de-endothelialized porcine corneas in vitro. The novel thermo-responsive cell culture carrier facilitates the generation and transfer of functional HCEC sheets. This paves the way to generate tissue engineered human corneal endothelium as an alternative transplant source for endothelial keratoplasty.

  4. Physics and chemistry on the surface of interstellar dust grains : the effect of O-atom diffusion and chemical desorption on the H-C-N-O reaction network

    OpenAIRE

    Minissale, Marco

    2014-01-01

    The interstellar medium is the matter that exists in the space between the star systems in a galaxy. It is composed of gas and elongated tiny dust grains. To date, plenty of molecules (> 170) are known to exist in the interstellar medium. The presence of most of them can be understood in terms of gas phase reactions but the synthesis of some key species (H2, H2O, CO2) need the intervention of solid-state reactions on dust grains surface. The aims of this thesis are to understand what are the ...

  5. The Glyoxal Clock Reaction

    Science.gov (United States)

    Ealy, Julie B.; Negron, Alexandra Rodriguez; Stephens, Jessica; Stauffer, Rebecca; Furrow, Stanley D.

    2007-01-01

    Research on the glyoxal clock reaction has led to adaptation of the clock reaction to a general chemistry experiment. This particular reaction is just one of many that used formaldehyde in the past. The kinetics of the glyoxal clock makes the reaction suitable as a general chemistry lab using a Calculator Based Laboratory (CBL) or a LabPro. The…

  6. Ultrananocrystalline diamond thin films functionalized with therapeutically active collagen networks.

    Energy Technology Data Exchange (ETDEWEB)

    Huang, H.; Chen, M.; Bruno, P.; Lam, R.; Robinson, E.; Gruen, D.; Ho, D.; Materials Science Division; Northwestern Univ.

    2009-01-01

    The fabrication of biologically amenable interfaces in medicine bridges translational technologies with their surrounding biological environment. Functionalized nanomaterials catalyze this coalescence through the creation of biomimetic and active substrates upon which a spectrum of therapeutic elements can be delivered to adherent cells to address biomolecular processes in cancer, inflammation, etc. Here, we demonstrate the robust functionalization of ultrananocrystalline diamond (UNCD) with type I collagen and dexamethasone (Dex), an anti-inflammatory drug, to fabricate a hybrid therapeutically active substrate for localized drug delivery. UNCD oxidation coupled with a pH-mediated collagen adsorption process generated a comprehensive interface between the two materials, and subsequent Dex integration, activity, and elution were confirmed through inflammatory gene expression assays. These studies confer a translational relevance to the biofunctionalized UNCD in its role as an active therapeutic network for potent regulation of cellular activity toward applications in nanomedicine.

  7. Allosteric transitions of supramolecular systems explored by network models: application to chaperonin GroEL.

    Directory of Open Access Journals (Sweden)

    Zheng Yang

    2009-04-01

    Full Text Available Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM, for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s, most of which involve conserved residues.

  8. Practice Gaps: Drug Reactions.

    Science.gov (United States)

    Wolverton, Stephen E

    2016-07-01

    The term "drug reactions" is relevant to dermatology in three categories of reactions: cutaneous drug reactions without systemic features, cutaneous drug reactions with systemic features, and systemic drugs prescribed by the dermatologist with systematic adverse effects. This article uses examples from each of these categories to illustrate several important principles central to drug reaction diagnosis and management. The information presented will help clinicians attain the highest possible level of certainty before making clinical decisions. PMID:27363888

  9. Genetically designed biomolecular capping system for mesoporous silica nanoparticles enables receptor-mediated cell uptake and controlled drug release

    Czech Academy of Sciences Publication Activity Database

    Datz, S.; Argyo, C.; Gattner, M.; Weiss, V.; Brunner, K.; Bretzler, J.; von Schirnding, C.; Torrano, A. A.; Spada, F.; Vrábel, Milan; Engelke, H.; Bräuchle, C.; Carell, T.; Bein, T.

    2016-01-01

    Roč. 8, č. 15 (2016), s. 8101-8110. ISSN 2040-3364 Institutional support: RVO:61388963 Keywords : responsive controlled release * Diels-Alder reactions * human carbonic anhydrase Subject RIV: CC - Organic Chemistry Impact factor: 7.394, year: 2014

  10. Green networking

    CERN Document Server

    Krief, Francine

    2012-01-01

    This book focuses on green networking, which is an important topic for the scientific community composed of engineers, academics, researchers and industrialists working in the networking field. Reducing the environmental impact of the communications infrastructure has become essential with the ever increasing cost of energy and the need for reducing global CO2 emissions to protect our environment.Recent advances and future directions in green networking are presented in this book, including energy efficient networks (wired networks, wireless networks, mobile networks), adaptive networ

  11. A Topological Characterization of Medium-Dependent Essential Metabolic Reactions

    OpenAIRE

    Nikolaus Sonnenschein; Carsten Marr; Marc-Thorsten Hütt

    2012-01-01

    Metabolism has frequently been analyzed from a network perspective. A major question is how network properties correlate with biological features like growth rates, flux patterns and enzyme essentiality. Using methods from graph theory as well as established topological categories of metabolic systems, we analyze the essentiality of metabolic reactions depending on the growth medium and identify the topological footprint of these reactions. We find that the typical topological context of a me...

  12. Mass Action Dynamics of Coupled Reactions using Fluctuation Theory

    OpenAIRE

    Cannon, William R.; Baker, Scott E.

    2015-01-01

    Comprehensive and predictive simulation of coupled reaction networks has long been a goal of biology and other fields. Currently, metabolic network models that utilize enzyme mass action kinetics have predictive power but are limited in scope and application by the fact that the determination of enzyme rate constants is laborious and low throughput. We present a statistical thermodynamic formulation of the law of mass action for coupled reactions at both steady states and non-stationary state...

  13. On the Positive Reaction to Network Police-related Public Opinion-Taking Fenghuang 9.4 Case as an Example%论网络涉警舆情的主动性应对——以凤凰“9·4案件”为例

    Institute of Scientific and Technical Information of China (English)

    刘劲青

    2011-01-01

    With the rapid development of modern network,network police-related public opinion tends to increase in amount,which provides new opportunities for the construction of police-related public opinion while posing new challenges for public security administration and law enforcement.This paper mainly discusses the positive reaction of police to network police-related public opinion by taking Fenghuang 9.4 case as an example and proposes ways for the cultivation of police good image.%随着现代网络的快速发展,网络涉警舆情也大量增加,既为警察公共关系建设创造了新的机遇,也为公安行政与执法带来了新挑战。应吸取凤凰"9·4案件"教训,警察应顺势而为,掌握涉警舆情应对主动权,以塑造警察良好形象。

  14. Simultaneous optimization of transit network and public bicycle station network

    Institute of Scientific and Technical Information of China (English)

    刘洋; 朱宁; 马寿峰

    2015-01-01

    The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization (CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container. Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

  15. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  16. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.;

    2003-01-01

    environment were included. A total of 708 structural open reading frames (ORFs) were accounted for in the reconstructed network, corresponding to 1035 metabolic reactions. Further, 140 reactions were included on the basis of biochemical evidence resulting in a genome-scale reconstructed metabolic network...... Escherichia coli. The reconstructed metabolic network is the first comprehensive network for a eukaryotic organism, and it may be used as the basis for in silico analysis of phenotypic functions....

  17. Incomplete fusion reactions

    International Nuclear Information System (INIS)

    Various aspects of the mechanism of heavy-ion induced reactions in the range of bombarding energies from a few to about 20 MeV/A are reviewed with special emphasis on the reactions for very asymmetric systems. Results of the experimental studies of binary reactions and particularly of the incomplete fusion reactions (selected by means of various coincidence techniques)are discussed. A model of generalized critical angular momentum is formulated. The model explains essential features of the incomplete fusion reactions and predicts that particular reaction channels are localized in well defined regions of angular momenta. An extension of this model (the sum-rule model) is also proposed in attempt to consistently describe the complete fusion reactions, incomplete fusion reactions and multibody reactions in the framework of statistical competition constrained by the angular momentum limitations. (author)

  18. Classical swine fever virus detection: results of a real-time reverse transcription polymerase chain reaction ring trial conducted in the framework of the European network of excellence for epizootic disease diagnosis and control

    DEFF Research Database (Denmark)

    Hoffmann, Bernd; Blome, Sandra; Bonilauri, Paolo;

    2011-01-01

    The current study reports on a real-time reverse transcription polymerase chain reaction (real-time RT-PCR) ring trial for the detection of Classical swine fever virus (CSFV) genomic RNA undertaken by 10 European laboratories. All laboratories were asked to use their routine in-house real-time RT......-PCR protocols and a standardized protocol commonly used by the Friedrich-Loeffler-Institute (FLI) on a panel of well-characterized samples. In general, all participants produced results within the acceptable range. The FLI assay, several in-house assays, and the commercial kits had high analytical sensitivity...... and specificity values. Nevertheless, some in-house systems had unspecific reactions or suboptimal sensitivity with only a single CSFV genotype. Follow-up actions involved either improvement of suboptimal assays or replacement of specific laboratory assays with the FLI protocol, with or without...

  19. Linking Drugs to Obscure Illnesses: Lessons from Pure Red Cell Aplasia, Nephrogenic Systemic Fibrosis, and Reye’s Syndrome. A Report From the Southern Network on Adverse Reactions (SONAR)

    OpenAIRE

    Bennett, Charles L.; Starko, Karen M.; Thomsen, Henrik S; Cowper, Shawn; Sartor, Oliver; Macdougall, Iain C.; Qureshi, Zaina P; Bookstaver, P. Brandon; Miller, April D; Norris, LeAnn B.; Xirasagar, Sudha; Trenery, Alyssa; Lopez, Isaac; Kahn, Adam; Murday, Alanna

    2012-01-01

    Identification of serious adverse drug reactions (sADRS) associated with commonly used drugs can elude detection for years. Reye’s syndrome (RS), nephrogenic systemic fibrosis (NSF), and pure red cell aplasia (PRCA) among chronic kidney disease (CKD) patients were recognized in 1951, 2000, and 1998, respectively. Reports associating these syndromes with aspirin, gadodiamide, and epoetin, were published 29, 6, and 4 years later, respectively. We obtained primary information from clinicians who...

  20. The Branchings of the Main s-process: Their Sensitivity to alpha-induced Reactions on 13C and 22Ne and to the Uncertainties of the Nuclear Network

    CERN Document Server

    Bisterzo, Sara; Kaeppeler, Franz; Wiescher, Michael; Imbriani, Gianluca; Straniero, Oscar; Cristallo, Sergio; Goerres, Joachim; deBoer, Richard

    2015-01-01

    This paper provides a detailed analysis of the main component of the slow neutron capture process (the s-process), which accounts for the solar abundances of half of the nuclei with 90 <~ A <~ 208. We examine the impact of the uncertainties of the two neutron sources operating in low-mass asymptotic giant branch (AGB) stars: the 13C(alpha, n)16O reaction, which releases neutrons radiatively during interpulse periods (kT ~ 8 keV), and the 22Ne(alpha, n)25Mg reaction, partially activated during the convective thermal pulses (TPs). We focus our attention on the branching points that mainly influence the abundance of s-only isotopes. In our AGB models, the 13C is fully consumed radiatively during interpulse. In this case, we find that the present uncertainty associated to the 13C(alpha, n)16O reaction has marginal effects on s-only nuclei. On the other hand, a reduction of this rate may increase the amount of residual (or unburned) 13C at the end of the interpulse: in this condition, the residual 13C is bur...