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At least 1,729 records · Page 96Linked to original sources
PubMed2005

Towards building the silicon cell: a modular approach.

Systems Biology aims to understand quantitatively how properties of biological systems can be understood as functions of the characteristics of, and interactions between their macromolecular components. Whereas, traditional biochemistry focused on isolation and characterization of cellular components, the challenge for Systems Biology lies in integration of this knowledge and the knowledge about molecular interactions. Computer models play an important role in this integration. We here discuss an approach with which we aim to link kinetic models on small parts of metabolism together, so as to form detailed kinetic models of larger chunks of metabolism, and ultimately of the entire living cell. Specifically, we will discuss techniques that can be used to model a sub-network in isolation of a larger network of which it is a part, while still maintaining the dynamics of the larger complete network. We will start by outlining the JWS online system, the silicon cell project, and the type of models we propose. JWS online is a model repository, which can be used for the storage, simulation and analysis of kinetic models. We advocate to integrate a top-down approach, where measurements on the complete system are used to derive fluxes in a detailed structural model, with a bottom-up approach, consisting of the integration of molecular mechanism-based detailed kinetic models into the structural model.

Animals↗
PubMed2002

Chaotic function generator: complex dynamics and its control in a loss-modulated Nd:YAG laser.

The complex dynamics resulting from electronic feedback of a laser's intensity are explored and characterized. Distinct stable and chaotic regimes can be elicited from the laser by tuning the bias of the feedback loop. An additional branch of the feedback loop, containing a derivative filter, provides access to new kinds of dynamics, including a more gradual transition to chaos. The whole feedback network together allows the laser dynamics to be selected from among a wide range of chaotic wave forms distinguished by statistical or spectral information. In other words, this laser system can be used as a tunable generator of chaotic functions.

Journal Article↗
PubMed2002

An image analysis algorithm for dendritic spines.

The structure of neuronal dendrites and their spines underlie the connectivity of neural networks. Dendrites, spines, and their dynamics are shaped by genetic programs as well as sensory experience. Dendritic structures and dynamics may therefore be important predictors of the function of neural networks. Based on new imaging approaches and increases in the speed of computation, it has become possible to acquire large sets of high-resolution optical micrographs of neuron structure at length scales small enough to resolve spines. This advance in data acquisition has not been accompanied by comparable advances in data analysis techniques; the analysis of dendritic and spine morphology is still accomplished largely manually. In addition to being extremely time intensive, manual analysis also introduces systematic and hard-to-characterize biases. We present a geometric approach for automatically detecting and quantifying the three-dimensional structure of dendritic spines from stacks of image data acquired using laser scanning microscopy. We present results on the measurement of dendritic spine length, volume, density, and shape classification for both static and time-lapse images of dendrites of hippocampal pyramidal neurons. For spine length and density, the automated measurements in static images are compared with manual measurements. Comparisons are also made between automated and manual spine length measurements for a time-series data set. The algorithm performs well compared to a human analyzer, especially on time-series data. Automated analysis of dendritic spine morphology will enable objective analysis of large morphological data sets. The approaches presented here are generalizable to other aspects of neuronal morphology.

Algorithms↗
PubMed2006

Deformations in actin comets from rocketing beads.

The mechanical and dynamical properties of the actin network are essential for many cellular processes like motility or division, and there is a growing body of evidence that they are also important for adhesion and trafficking. The leading edge of migrating cells is pushed out by the polymerization of actin networks, a process orchestrated by cross-linkers and other actin-binding proteins. In vitro physical characterizations show that these same proteins control the elastic properties of actin gels. Here we use a biomimetic system of Listeria monocytogenes, beads coated with an activator of actin polymerization, to assess the role of various actin-binding proteins in propulsion. We find that the properties of actin-based movement are clearly affected by the presence of cross-linkers. By monitoring the evolution of marked parts of the comet, we provide direct experimental evidence that the actin gel continuously undergoes deformations during the growth of the comet. Depending on the protein composition in the motility medium, deformations arise from either gel elasticity or monomer diffusion through the actin comet. Our findings demonstrate that actin-based movement is governed by the mechanical properties of the actin network, which are fine-tuned by proteins involved in actin dynamics and assembly.

Actin-Related Protein 2-3 Complex↗
PubMed2004

Properties of a two-dimensional asphaltene network at the water-cyclohexane interface deduced from dynamic tensiometry.

Static and dynamic tensiometries show that a newly prepared water/asphaltenated cyclohexane interface behaves as expected: the mean area occupied per asphaltene molecule is 2 nm2, and variations of interfacial tension and dilatational elastic modulus with time indicate that equilibrium is reached more slowly than that for usual surfactants. The use of the time/temperature superposition principle allows a detailed rheological study of a 2 day old interface of the same type which has reached equilibrium. It is found that the two-dimensional asphaltene network exhibits a glass transition zone, behaves as a gel near its gelation point, and is built by a universal process of aggregation.

Journal Article↗
PubMed2001

Molecular recognition: identifying compounds and their targets.

As a result of gene sequencing and proteomic efforts, thousands of new genes and proteins are now available as potential drug targets. The milieu of these proteins is complex and interactive; thousands of proteins activate, inhibit, and control each other's actions. The effect of blocking or activating a protein in a cell is far-reaching, and can affect whole, as well as adjacent pathways. This network of pathways is dynamic and a cellular response can change depending on the stimulus. In this section, the identification and role of individual proteins within the context of networked pathways, and the regulation of the activity of these proteins is discussed. Diverse chemical libraries, combinatorial libraries, natural products, as well as unnatural natural products that are derived from combinatorial biology (Chiu [2001] Proc. Natl. Acad. Sci. USA. 98:8548-8553), provide the chemical diversity in the search for new drugs to block new targets. Identifying new compounds that can become drugs is a long, expensive, and arduous task and potential targets must be carefully defined so as not to waste valuable resources. Equally important is the selection of compounds to be future drug candidates. Target selectivity in no way guarantees clinical efficacy, as the compound must meet pharmaceutical requirements, such as solubility, absorption, tissue distribution, and lack of toxicity. Thus matching biological diversity with chemical diversity involves something more than tight interactions, it involves interactions of the compounds with a variety host factors that can modulate its activity.

Combinatorial Chemistry Techniques↗
PubMed2003

On the constructive role of noise in stabilizing itinerant trajectories in chaotic dynamical systems.

This work aims at studying dynamical models of neural networks, which exhibit phase transitions between states of various complexities. We use the biologically motivated KIII model, which has demonstrated excellent performance as a robust dynamical memory device. KIII is a high-dimensional dynamical system with extremely fragmented boundaries between limit cycles, tori, fixed points, and chaotic attractors. We study the role of additive noise in the development of itinerant trajectories. Noise not only stabilizes aperiodic trajectories, but there is an optimum noise level with highly itinerant behavior. We speculate that the previously found optimum classification performance of KIII as a function of the noise level, also identified as chaotic resonance, is related to chaotic itinerant oscillations among various ordered states.

Animals↗
PubMed2006

Adaptive reconfiguration of fractal small-world human brain functional networks.

Brain function depends on adaptive self-organization of large-scale neural assemblies, but little is known about quantitative network parameters governing these processes in humans. Here, we describe the topology and synchronizability of frequency-specific brain functional networks using wavelet decomposition of magnetoencephalographic time series, followed by construction and analysis of undirected graphs. Magnetoencephalographic data were acquired from 22 subjects, half of whom performed a finger-tapping task, whereas the other half were studied at rest. We found that brain functional networks were characterized by small-world properties at all six wavelet scales considered, corresponding approximately to classical delta (low and high), , alpha, beta, and gamma frequency bands. Global topological parameters (path length, clustering) were conserved across scales, most consistently in the frequency range 2-37 Hz, implying a scale-invariant or fractal small-world organization. Dynamical analysis showed that networks were located close to the threshold of order/disorder transition in all frequency bands. The highest-frequency gamma network had greater synchronizability, greater clustering of connections, and shorter path length than networks in the scaling regime of (lower) frequencies. Behavioral state did not strongly influence global topology or synchronizability; however, motor task performance was associated with emergence of long-range connections in both beta and gamma networks. Long-range connectivity, e.g., between frontal and parietal cortex, at high frequencies during a motor task may facilitate sensorimotor binding. Human brain functional networks demonstrate a fractal small-world architecture that supports critical dynamics and task-related spatial reconfiguration while preserving global topological parameters.

Brain↗
PubMed2005

Influence of homologous disaccharides on the hydrogen-bond network of water: complementary Raman scattering experiments and molecular dynamics simulations.

A comparative investigation of trehalose, sucrose, and maltose in water solution has been performed using Raman scattering experiments and Molecular Dynamics simulations. From the analysis of the O-H stretching region in the [2500,4000] cm(-1) Raman spectral range, which includes for the first time the contribution of 'free' water, and the statistical distribution of water HB probabilities from MD simulations, this study confirms the privileged interaction of trehalose with water above a peculiar threshold weight concentration of about 30%. The role of the hydration number of sugars--found higher for trehalose--on the destructuring effect of the water hydrogen bond network is also addressed. The analysis of the water O-H-O bending spectral range [1500,1800] cm(-1) reveals a change of the homogeneity of water molecules influenced by sugars, but the three investigated sugars are found to behave similarly.

Computer Simulation↗
PubMed2006

Polarization and movement of keratocytes: a multiscale modelling approach.

Eukariotic cell motility is a complex phenomenon, in which the cytoskeleton and its major constituent, actin, play an essential role. Actin forms polymers of long, stiff filaments that are cross-linked into an anisotropic network inside a thin sheet-like cellular protrusion, the lamellipod. At the leading edge of this structure, polymerization of actin filaments creates the force that pushes out the membrane and leads to translocation of a motile cell. Dynamics of the actin network account for changes in cell shape, crawling motion and turning of the cell in response to external cues. Regulating the dynamics of the cytoskeleton, and playing a central role in signal transduction in the cell, are Cdc42, Rac and Rho (GTPases of the rho family, collectively known as the small G-proteins) and the actin nucleating complex, Arp2/3. In this paper, we use a multiscale modelling approach in a 2D model of a motile cell. We describe the mutual interactions of the small G-proteins, and their effects on capping and side-branching of actin filaments. We incorporate the pushing exerted by oriented actin filament ends on the cell edge, and a Rho-dependent contraction force. Combining these biochemical and mechanical aspects, we investigate the dynamics of a model epidermal fish keratocyte through in silico experiments. Our model gives insight into how, in response to some cue, a cell can polarize, form a leading edge, and move; concomitantly it explains how a keratocyte cell can maintain its shape and polarity, even after removal of the initial stimulus, and how it can change direction quickly in response to changes in its environment. We show that establishment of polarity stems from interactions of Cdc42, Rac and Rho, while maintenance and robustness of polarity is due to the rapid cytosolic diffusion of the inactive (GDI-bound) forms of the small G-proteins. Our model produces a cell shape that closely resembles the keratocytes and correct speeds for biologically reasonable parameter values. Movies of the simulations can be obtained from http://theory.bio.uu.nl/stan/keratocyte.

Actins↗
PubMed1998

Adaptive response organizer network for space-time patterns in low level vision.

In this paper we present a biologically-inspired generalized artificial model of retinal neural response organization that can serve as a useful framework for analysis of response dynamics in artificial neural networks, specially in the visual systems. Adaptive Response Organizer (ARO), is an ON-centre OFF-surround class of artificial neural network models for feature abstraction and object identification under varying background conditions. The proposed architecture utilizes the existing literature on retinal functionality to develop a self-organized scheme to form visually evoked activation maps in response to arbitrary sequences of analog (gray scale) visual input patterns. It is conceptually organized into three processing layers, where visual information flows vertically through the layers and reorganized laterally by interneuronal action. The temporal response configuration of visually responsive neurons acquire the antagonistic centre-surround characteristics to promote detection of weak contrasts and rapid changes to transient and steady state stimulus at early stages of vision, for optical scene interpretation.

Journal Article↗
PubMed2004

Modeling of cell signaling pathways in macrophages by semantic networks.

BACKGROUND: Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. RESULTS: We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. CONCLUSIONS: We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed investigation of connections among various essential molecules and reflected the cause-effect relationships among signaling events. The simulation demonstrated the dynamics of the semantic network, where a change of states on a molecule can alter its function and potentially cause a chain-reaction effect in the system.

Computer Simulation↗
PubMed2004

Inactivation of calcium-binding protein genes induces 160 Hz oscillations in the cerebellar cortex of alert mice.

Oscillations in neuronal populations may either be imposed by intrinsically oscillating pacemakers neurons or emerge from specific attributes of a distributed network of connected neurons. Calretinin and calbindin are two calcium-binding proteins involved in the shaping of intraneuronal Ca2+ fluxes. However, although their physiological function has been studied extensively at the level of a single neuron, little is known about their role at the network level. Here we found that null mutations of genes encoding calretinin or calbindin induce 160 Hz local field potential oscillations in the cerebellar cortex of alert mice. These oscillations reached maximum amplitude just beneath the Purkinje cell bodies and are reinforced in the cerebellum of mice deficient in both calretinin and calbindin. Purkinje cells fired simple spikes phase locked to the oscillations and synchronized along the parallel fiber axis. The oscillations reversibly disappeared when gap junctions or either GABA(A) or NMDA receptors were blocked. Cutaneous stimulation of the whisker region transiently suppressed the oscillations. However, the intrinsic somatic excitability of Purkinje cells recorded in slice preparation was not significantly altered in mutant mice. Functionally, these results suggest that 160 Hz oscillation emerges from a network mechanism combining synchronization of Purkinje cell assemblies through parallel fiber excitation and the network of coupled interneurons of the molecular layer. These findings demonstrate that subtle genetically induced modifications of Ca2+ homeostasis in specific neuron types can alter the observed dynamics of the global network.

Action Potentials↗
PubMed1995

Switching dynamics and the transient memory storage in a model enzyme network involving Ca2+/calmodulin-dependent protein kinase II in synapses.

The signal processing through a chain of phosphorylation-dephosphorylations mediated by a pair of enzymes, Ca2+/calmodulin-dependent protein kinase II and the associated phosphatase, is formulated as a nonautonomous dynamical system in the framework of nonautocatalytic, intraholoenzyme reaction dynamics. A classification of switching characteristics of the system is made in the parameter space comprising the three controllable system parameters: an input-pulse intensity and initial concentrations of the two associated enzymes. It is found that a region of parameter space exists termed the transition zone, that exhibits a quasi-switching behaviour characterized by a signal storage time being prolonged by more than several orders of magnitude (10(4) times in certain cases) for the increase of two orders of magnitude in the input signal intensity. The effect of alterations of certain rate constants on the quasi-switching property is explored. It is numerically demonstrated that the Ca2+/calmodulin-dependent kinase II-related phosphatase is the most important key enzyme for regulating the signal storage time.

Calcium-Calmodulin-Dependent Protein Kinase Type 2↗
PubMed2005

Understanding microtubule dynamics for improved cancer therapy.

Microtubules (MTs), key components of the cytoskeleton, are dynamic polymers of tubulin that form a well-organized network of polarized tube filaments. MT dynamics are highly regulated both spacially and temporally by several MT-related proteins, themselves regulated by several kinases and phosphatases via signaling cascades, and also by coordinated interactions with actin cytoskeleton and adhesion sites. Regulation of MT dynamics is crucial for mitosis, cell migration, cell signaling and trafficking. MT-targeted drugs (MTDs), which constitute a major anticancer drug family with antimitotic and antiangiogenic properties, inhibit tumor progression mainly by altering MT dynamics in both cancer and endothelial cells. Identification of proteins regulating the MT network will lead to a better understanding of tumor progression regulators and will be helpful in improving cancer therapy.

Animals↗
PubMed2006

Packet traffic analysis of scale-free networks for large-scale network-on-chip design.

Recent progress in integrated circuit technologies requires precise evaluation between dynamic characteristics and topological architecture design. In this paper, we have investigated the performance evaluation of network-on-chip (NoC) architectures constructed with diverse scale-free network topologies by dynamic packet traffic simulation and theoretical network analysis. Topological differences of scale-free networks are evaluated by the degree-degree correlations that indicate topological tendency between the degree of a node and that of the nearest neighbors. Our simulation results quantitatively show that the NoC architecture constructed with the topology where hubs mostly connect to lower-degree nodes is found to achieve short latency and low packet loss ratio since it can disperse traffic load and avoid the extreme concentration of load on hubs.

Journal Article↗
PubMed1982

Simulation of learning processes in neuronal networks of the cerebellum.

A dynamic model of learning that is based on the specific neuronal system of the cerebellum, including some of its structural-functional peculiarities, is proposed. It allows to simulate modification processes of the parallel fiber synapse that influences the Purkinje cell. regularities of synaptic modifications are obtained by extrapolating well-known experimental data bout changes of synaptic efficiency as resulting from release, refilling and mobilization of the mediator. It is shown that a mathematical description of synaptic processes corresponds to experimental data on the changes of synaptic efficiency under rhythmical stimulation and gives objective quantitative estimates for long-term (refilling of the mediator) and short-term (mobilization of the mediator) effects which are caused by presynaptic stimulation. Computer simulations have been conducted to investigate the characteristics of learning for different values of the following parameters: intensity of unconditioned stimulus (US, activity of the climbing fibre), intensity of conditioned stimulus (CS, activity of the parallel fibre), temporal shift between US and CS, temporal interval between reinforcements. It is shown that the temporal shift between CS and US is one of the major factors that influence the learning procedures. Analysis of the data obtained shows that the model enables us to simulate the main regularities of establishment and extinction of conditioned reflexes.

Animals↗
PubMed2005

Regulatory network for cell shape changes during Drosophila ventral furrow formation.

Rapid and sequential cell shape changes take place during the formation of the ventral furrow (VF) at the beginning of Drosophila gastrulation. At the cellular level, this morphogenetic event demands close coordination of the proteins involved in actin cytoskeletal reorganization. In order to construct a regulatory network that describes these cell shape changes, we have used published genetic and molecular data for 18 genes encoding transcriptional regulators and signaling pathway components. Based on the dynamic behavior of this network we explored the hypothesis that the combination of three recognizable phenotypes describing wild type or mutant cell types, during VF invagination, correspond to different activation states of a specific set of these gene products, which are point attractors of the regulatory network. From our results, we recognize missing components in the regulatory network and suggest alternative pathways in the regulation of cell shape changes during VF formation.

Animals↗