Search results for "Modeling and simulation"

showing 10 items of 1561 documents

On a set of data for the membrane potential in a neuron

2006

We consider a set of data where the membrane potential in a pyramidal neuron is measured almost continuously in time, under varying experimental conditions. We use nonparametric estimates for the diffusion coefficient and the drift in view to contribute to the discussion which type of diffusion process is suitable to model the membrane potential in a neuron (more exactly: in a particular type of neuron under particular experimental conditions).

Statistics and ProbabilityModels NeurologicalNeural ConductionAction PotentialsTetrodotoxinType (model theory)Statistics NonparametricGeneral Biochemistry Genetics and Molecular BiologyMembrane PotentialsSet (abstract data type)MiceStatisticsAnimalsDiffusion (business)MathematicsCerebral CortexNeuronsMembrane potentialStochastic ProcessesQuantitative Biology::Neurons and CognitionGeneral Immunology and MicrobiologyStochastic processPyramidal CellsApplied MathematicsNonparametric statisticsGeneral MedicineElectrophysiologyElectrophysiologynervous systemDiffusion processModeling and SimulationPotassiumGeneral Agricultural and Biological SciencesBiological systemAlgorithmsMathematical Biosciences
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Immune networks: Multi-tasking capabilities at medium load

2013

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low load regime, where the number $P$ of simultaneously retrievable patterns scales with the number $N$ of nodes as $P\sim \log N$. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium load r…

Statistics and ProbabilityModularity (networks)Theoretical computer scienceDegree (graph theory)Associative networkComputer scienceGeneral Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksModeling and SimulationFOS: Biological sciencesCell Behavior (q-bio.CB)Human multitaskingQuantitative Biology - Cell BehaviorRelevance (information retrieval)Cluster analysisImmune Network Statistical Mechanics Hopfield model Parallel RetrievalMathematical Physics
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Product and moment formulas for iterated stochastic integrals (associated with Lévy processes)

2019

In this paper, we obtain explicit product and moment formulas for products of iterated integrals generated by families of square integrable martingales associated with an arbitrary Levy process. We...

Statistics and ProbabilityMoment (mathematics)Pure mathematicsMathematics::ProbabilitySquare-integrable functionIterated integralsIterated functionModeling and SimulationProduct (mathematics)Lévy processMathematicsStochastics
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Some extensions of multivariate sliced inverse regression

2007

Multivariate sliced inverse regression (SIR) is a method for achieving dimension reduction in regression problems when the outcome variable y and the regressor x are both assumed to be multidimensional. In this paper, we extend the existing approaches, based on the usual SIR I which only uses the inverse regression curve, to methods using properties of the inverse conditional variance. Contrary to the existing ones, these new methods are not blind for symmetric dependencies and rely on the SIR II or SIRα. We also propose their corresponding pooled slicing versions. We illustrate the usefulness of these approaches on simulation studies.

Statistics and ProbabilityMultivariate statisticsApplied MathematicsDimensionality reductionInverseOutcome variableModeling and SimulationStatisticsSliced inverse regressionStatistics::MethodologyStatistics Probability and UncertaintyConditional varianceRegression problemsMathematicsRegression curveJournal of Statistical Computation and Simulation
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RNA viruses as complex adaptive systems

2004

RNA viruses have high mutation rates and so their populations exist as dynamic and complex mutant distributions. It has been consistently observed that when challenged with a new environment, viral populations adapt following hyperbolic-like kinetics: adaptation is initially very rapid, but then slows down as fitness reaches an asymptotic value. These adaptive dynamics have been explained in terms of populations moving towards the top of peaks on rugged fitness landscapes. Fitness fluctuations of varying magnitude are observed during adaptation. Often the presence of fluctuations in the evolution of physical systems indicates some form of self-organization, or where many components of the s…

Statistics and ProbabilityMutation rateTime FactorsFitness landscapePhysical systemSystems TheoryProbability density functionBiologyVesicular stomatitis Indiana virusGeneral Biochemistry Genetics and Molecular BiologyEvolution MolecularRNA VirusesWeibull distributionGeneticsExperimental evolutionModels StatisticalModels GeneticComputersSystems BiologyApplied MathematicsGeneral MedicineBiological EvolutionSelf-organized criticalityEvolutionary biologyModeling and SimulationMutationAdaptationBiosystems
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Gamma Kernel Intensity Estimation in Temporal Point Processes

2011

In this article, we propose a nonparametric approach for estimating the intensity function of temporal point processes based on kernel estimators. In particular, we use asymmetric kernel estimators characterized by the gamma distribution, in order to describe features of observed point patterns adequately. Some characteristics of these estimators are analyzed and discussed both through simulated results and applications to real data from different seismic catalogs.

Statistics and ProbabilityNonparametric statisticsEstimatorKernel principal component analysisPoint processVariable kernel density estimationKernel embedding of distributionsModeling and SimulationKernel (statistics)Bounded domainStatisticsGamma distributionGamma kernel estimatorIntensity functionTemporal point processes.Settore SECS-S/01 - StatisticaMathematicsCommunications in Statistics - Simulation and Computation
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An Extended Filament Based Lamellipodium Model Produces Various Moving Cell Shapes in the Presence of Chemotactic Signals

2015

The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional continuum model, describing the dynamcis of two interacting families of locally parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move? Mathematical modeling of cytoskeleton dynamics and cell migration. Cell mechanics: from single scale-based models to multiscale modeling. Chapman and Hall, 2010). It contains accounts of the filaments' bending stiffness, of adhesion to the substrate, and of cross-links connecting the two families. An extension of the model is presented with contributions from nucleation of filaments by branching, from capping, from contraction by actin-myosin interaction, and from a pr…

Statistics and ProbabilityNucleationNanotechnologymacromolecular substancesMyosinsBranching (polymer chemistry)Models BiologicalGeneral Biochemistry Genetics and Molecular BiologyPolymerizationQuantitative Biology::Cell BehaviorProtein filamentQuantitative Biology::Subcellular ProcessesCell Behavior (q-bio.CB)CoulombAnimalsComputer SimulationPseudopodiaCytoskeletonCell ShapeActinPhysicsGeneral Immunology and MicrobiologyApplied MathematicsChemotaxisChemotaxisNumerical Analysis Computer-AssistedGeneral Medicine92C17Actin CytoskeletonClassical mechanicsModeling and SimulationFOS: Biological sciencesQuantitative Biology - Cell BehaviorLamellipodiumGeneral Agricultural and Biological SciencesSignal Transduction
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A Hooke's law-based approach to protein folding rate

2014

Kinetics is a key aspect of the renowned protein folding problem. Here, we propose a comprehensive approach to folding kinetics where a polypeptide chain is assumed to behave as an elastic material described by the Hooke[U+05F3]s law. A novel parameter called elastic-folding constant results from our model and is suggested to distinguish between protein with two-state and multi-state folding pathways. A contact-free descriptor, named folding degree, is introduced as a suitable structural feature to study protein-folding kinetics. This approach generalizes the observed correlations between varieties of structural descriptors with the folding rate constant. Additionally several comparisons am…

Statistics and ProbabilityPROTDCALStructure analysisGeneral Biochemistry Genetics and Molecular BiologyArticleProtein Structure SecondaryAmino acid sequencesymbols.namesakeProtein structureEnergeticsFeature (machine learning)Statistical physicsProtein foldingTheoretical modelProtein secondary structureReaction kineticsGeneral Immunology and MicrobiologyChemical modelApplied MathematicsProteinHooke's lawModelingProteinsGeneral MedicineDNAComputer simulationElasticityFolding degreeFolding (chemistry)ChemistryKineticsModels ChemicalModeling and SimulationPeptidesymbolsProtein structureElastic folding constantPhysical chemistryProtein secondary structureThermodynamicsProtein foldingDownhill foldingPolypeptideGeneral Agricultural and Biological SciencesConstant (mathematics)Folding kinetics
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Dynamics of the Selkov oscillator.

2018

A classical example of a mathematical model for oscillations in a biological system is the Selkov oscillator, which is a simple description of glycolysis. It is a system of two ordinary differential equations which, when expressed in dimensionless variables, depends on two parameters. Surprisingly it appears that no complete rigorous analysis of the dynamics of this model has ever been given. In this paper several properties of the dynamics of solutions of the model are established. With a view to studying unbounded solutions a thorough analysis of the Poincar\'e compactification of the system is given. It is proved that for any values of the parameters there are solutions which tend to inf…

Statistics and ProbabilityPeriodicityQuantitative Biology - Subcellular ProcessesClassical exampleFOS: Physical sciencesDynamical Systems (math.DS)01 natural sciencesModels BiologicalGeneral Biochemistry Genetics and Molecular Biology010305 fluids & plasmassymbols.namesake0103 physical sciencesFOS: MathematicsPhysics - Biological PhysicsMathematics - Dynamical Systems0101 mathematicsSubcellular Processes (q-bio.SC)MathematicsGeneral Immunology and MicrobiologyCompactification (physics)Applied Mathematics010102 general mathematicsMathematical analysisGeneral MedicineMathematical ConceptsKineticsMonotone polygonBiological Physics (physics.bio-ph)FOS: Biological sciencesModeling and SimulationBounded functionOrdinary differential equationPoincaré conjecturesymbolsGeneral Agricultural and Biological SciencesGlycolysisDimensionless quantityMathematical biosciences
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Generalized Heisenberg algebra and (non linear) pseudo-bosons

2018

We propose a deformed version of the generalized Heisenberg algebra by using techniques borrowed from the theory of pseudo-bosons. In particular, this analysis is relevant when non self-adjoint Hamiltonians are needed to describe a given physical system. We also discuss relations with nonlinear pseudo-bosons. Several examples are discussed.

Statistics and ProbabilityPhysical systemGeneral Physics and AstronomyFOS: Physical sciences01 natural sciencesbiorthogonal bases in quantum mechanicPhysics and Astronomy (all)0103 physical sciencesMathematical PhysicAlgebra over a field010306 general physicsSettore MAT/07 - Fisica MatematicaMathematical PhysicsComputingMilieux_MISCELLANEOUSMathematicsBoson[PHYS]Physics [physics]Quantum Physics010308 nuclear & particles physicsStatistical and Nonlinear PhysicsMathematical Physics (math-ph)pseudo-bosonAlgebraNonlinear systemModeling and Simulationgeneralized Heisenberg algebraQuantum Physics (quant-ph)[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Statistical and Nonlinear Physic
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