Search results for " Simulation"

showing 10 items of 4034 documents

DRUDIT: Web-based DRUgs DIscovery Tools to design small molecules as modulators of biological targets

2019

Abstract Motivation New in silico tools to predict biological affinities for input structures are presented. The tools are implemented in the DRUDIT (DRUgs DIscovery Tools) web service. The DRUDIT biological finder module is based on molecular descriptors that are calculated by the MOLDESTO (MOLecular DEScriptors TOol) software module developed by the same authors, which is able to calculate more than one thousand molecular descriptors. At this stage, DRUDIT includes 250 biological targets, but new external targets can be added. This feature extends the application scope of DRUDIT to several fields. Moreover, two more functions are implemented: the multi- and on/off-target tasks. These tool…

Statistics and ProbabilityService (systems architecture)PolypharmacologyComputer scienceIn silicoMachine learningcomputer.software_genre01 natural sciencesBiochemistrybiological target finderdrug discoveryMolecular descriptors03 medical and health sciencesMolecular descriptorSettore BIO/10 - BiochimicaWeb applicationComputer SimulationPolypharmacologyMolecular Biology030304 developmental biologySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInternet0303 health sciencesbusiness.industrySmall moleculeSettore CHIM/08 - Chimica Farmaceutica0104 chemical sciencesComputer Science Applications010404 medicinal & biomolecular chemistryComputational MathematicsComputational Theory and MathematicsBiological targetThe InternetArtificial intelligencebusinesscomputerSoftware
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A tabu search algorithm for assigning teachers to courses

2002

In this paper we deal with the problem of assigning teachers to courses in a secondary school. The problem appears when a timetable is to be built and the teaching assignments are not fixed. We have developed a tabu search algorithm to solve the problem. The parameters involved in the algorithm have been estimated by using multiple regression techniques. The computational results, obtained on a set of Spanish secondary schools, show that the solutions obtained by this automatic procedure can be favourably compared with the solutions proposed by the experts.

Statistics and ProbabilitySet (abstract data type)Mathematical optimizationInformation Systems and ManagementModeling and SimulationComputingMilieux_COMPUTERSANDEDUCATIONDiscrete Mathematics and CombinatoricsGuided Local SearchManagement Science and Operations ResearchHeuristicsAlgorithmTabu searchMathematicsTop
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A quantum particle in a box with moving walls

2013

We analyze the non-relativistic problem of a quantum particle that bounces back and forth between two moving walls. We recast this problem into the equivalent one of a quantum particle in a fixed box whose dynamics is governed by an appropriate time-dependent Schroedinger operator.

Statistics and ProbabilitySettore FIS/02 - Fisica Teorica Modelli E Metodi MatematiciDifferential equationFOS: Physical sciencesGeneral Physics and AstronomySettore FIS/03 - Fisica Della MateriaSchrödinger equationsymbols.namesakeBoundary ConditionMathematical PhysicsQuantum Mechanics; Boundary Conditions; Quantum Zeno effect; Time-dependent HamiltoniansPhysicsQuantum PhysicsQuantum particlePartial differential equationOperator (physics)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)Quantum MechanicWave equationClassical mechanicsModeling and SimulationsymbolsQuantum Zeno effectQuantum Physics (quant-ph)Time-dependent HamiltoniansSchrödinger's cat
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Antibacterial Activity of Flavonoids Against Methicillin-resistant Staphylococcus aureus strains

2000

An experimental and theoretical study was performed on the anti-staphylococcal activity of 18 natural and synthetic flavonoids against methicillin-resistant Staphylococcus aureus strains. The analysed flavonoids belong to three well-differentiated structural patterns: chalcones, flavanones and flavones. The quantitative analysis of the anti-staphylococcal activity of the compounds was carried out by determining their percent inhibition degree. The hierarchical cluster analysis method was used to analyse the anti-MRSA activity of the compounds. With this methodology, the flavonoids were classified into four groups according to their anti-staphylococcal activity (high, sufficient, intermediat…

Statistics and ProbabilityStaphylococcus aureusChalconeStereochemistryFlavonoidMicrobial Sensitivity Testsmedicine.disease_causeFlavonesGeneral Biochemistry Genetics and Molecular BiologyStructure-Activity Relationshipchemistry.chemical_compoundChalconemedicineAnimalsCluster AnalysisHumansStructure–activity relationshipFlavonoidschemistry.chemical_classificationGeneral Immunology and MicrobiologyApplied MathematicsGeneral MedicineStaphylococcal InfectionsMethicillin-resistant Staphylococcus aureusAnti-Bacterial AgentschemistryBiochemistryStaphylococcus aureusModeling and SimulationMethicillin ResistanceGeneral Agricultural and Biological SciencesAntibacterial activityQuantitative analysis (chemistry)Journal of Theoretical Biology
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The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression.

2020

This paper focuses on hypothesis testing in lasso regression, when one is interested in judging statistical significance for the regression coefficients in the regression equation involving a lot of covariates. To get reliable p-values, we propose a new lasso-type estimator relying on the idea of induced smoothing which allows to obtain appropriate covariance matrix and Wald statistic relatively easily. Some simulation experiments reveal that our approach exhibits good performance when contrasted with the recent inferential tools in the lasso framework. Two real data analyses are presented to illustrate the proposed framework in practice.

Statistics and ProbabilityStatistics::TheoryInduced smoothingEpidemiologyComputer scienceFeature selectionWald test01 natural sciencesasthma researchStatistics::Machine Learning010104 statistics & probability03 medical and health sciencesHealth Information ManagementLasso (statistics)Linear regressionsparse modelsStatistics::MethodologyComputer Simulation0101 mathematicssandwich formula030304 developmental biologyStatistical hypothesis testing0303 health sciencesCovariance matrixlung functionRegression analysisStatistics::Computationsparse modelResearch DesignAlgorithmSmoothingvariable selectionStatistical methods in medical research
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Nonlinear parametric quantile models

2020

Quantile regression is widely used to estimate conditional quantiles of an outcome variable of interest given covariates. This method can estimate one quantile at a time without imposing any constraints on the quantile process other than the linear combination of covariates and parameters specified by the regression model. While this is a flexible modeling tool, it generally yields erratic estimates of conditional quantiles and regression coefficients. Recently, parametric models for the regression coefficients have been proposed that can help balance bias and sampling variability. So far, however, only models that are linear in the parameters and covariates have been explored. This paper …

Statistics and ProbabilityStatistics::Theoryquantile regressionEpidemiologyparametric010501 environmental sciences01 natural sciencesquantile regression coefficients models010104 statistics & probabilityOutcome variableHealth Information ManagementCovariateEconometricsHumansStatistics::MethodologyComputer Simulation0101 mathematicsChild0105 earth and related environmental sciencesParametric statisticsMathematicsModels StatisticalForced oscillation technique integrated loss function parametric quantile regression quantile regression coefficients models Child Computer Simulation Humans Regression Analysis Models Statistical Nonlinear DynamicsStatistics::ComputationQuantile regressionNonlinear systemNonlinear Dynamicsintegrated loss functionRegression AnalysisQuantileStatistical Methods in Medical Research
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A hypothetical model of the influence of inorganic phosphate on the kinetics of pyruvate kinase

2000

This paper presents a simple solution to the problem of approximating the calculated curve of reaction progress to the measured curve which is usually disturbed by initial oscillation of auxiliary lactate dehydrogenase (LDH) reaction. The experiments leading to the determination of the apparent Km for phosphoenolpyruvate (PEP) and Vm were performed. For precise estimation of kinetic parameters (Km and Vm) of the M1 isozyme of pyruvate kinase (PK), measured by coupling it to LDH reaction, the sequence of Michaelis‐Menten for pyruvate kinase and second-order kinetics for lactate dehydrogenase reaction as well as a non-zero initial concentration of lactate was assumed. The functions of apparen…

Statistics and ProbabilityStereochemistryPyruvate KinaseIn Vitro TechniquesModels BiologicalGeneral Biochemistry Genetics and Molecular BiologyPhosphatesPhosphoenolpyruvatechemistry.chemical_compoundAdenosine TriphosphateLactate dehydrogenaseAnimalsEnzyme kineticsEnzyme InhibitorsL-Lactate DehydrogenaseKinaseApplied MathematicsGeneral MedicineNADPhosphateAdenosine DiphosphateDissociation constantKineticsBiochemistrychemistryModeling and SimulationCattleUncompetitive inhibitorPhosphoenolpyruvate carboxykinasePyruvate kinaseBiosystems
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On the stability and ergodicity of adaptive scaling Metropolis algorithms

2011

The stability and ergodicity properties of two adaptive random walk Metropolis algorithms are considered. The both algorithms adjust the scaling of the proposal distribution continuously based on the observed acceptance probability. Unlike the previously proposed forms of the algorithms, the adapted scaling parameter is not constrained within a predefined compact interval. The first algorithm is based on scale adaptation only, while the second one incorporates also covariance adaptation. A strong law of large numbers is shown to hold assuming that the target density is smooth enough and has either compact support or super-exponentially decaying tails.

Statistics and ProbabilityStochastic approximationMathematics - Statistics TheoryStatistics Theory (math.ST)Law of large numbersMultiple-try Metropolis01 natural sciencesStability (probability)010104 statistics & probabilityModelling and Simulation65C40 60J27 93E15 93E35Adaptive Markov chain Monte CarloFOS: Mathematics0101 mathematicsScalingMetropolis algorithmMathematicsta112Applied Mathematics010102 general mathematicsRejection samplingErgodicityProbability (math.PR)ta111CovarianceRandom walkMetropolis–Hastings algorithmModeling and SimulationAlgorithmStabilityMathematics - ProbabilityStochastic Processes and their Applications
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Spatial moving average risk smoothing

2013

This paper introduces spatial moving average risk smoothing (SMARS) as a new way of carrying out disease mapping. This proposal applies the moving average ideas of time series theory to the spatial domain, making use of a spatial moving average process of unknown order to define dependence on the risk of a disease occurring. Correlation of the risks for different locations will be a function of m values (m being unknown), providing a rich class of correlation functions that may be reproduced by SMARS. Moreover, the distance (in terms of neighborhoods) that should be covered for two units to be found to make the correlation of their risks 0 is a quantity to be fitted by the model. This way, …

Statistics and ProbabilityStructure (mathematical logic)RiskModels StatisticalSeries (mathematics)EpidemiologyBayes TheoremFunction (mathematics)BiostatisticsMoving-average modelCorrelationMoving averageSpainEconometricsRange (statistics)HumansComputer SimulationDiseaseMortalitySmoothingMathematics
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Misinterpretation risks of global stochastic optimisation of kinetic models revealed by multiple optimisation runs

2016

Abstract One of use cases for metabolic network optimisation of biotechnologically applied microorganisms is the in silico design of new strains with an improved distribution of metabolic fluxes. Global stochastic optimisation methods (genetic algorithms, evolutionary programing, particle swarm and others) can optimise complicated nonlinear kinetic models and are friendly for unexperienced user: they can return optimisation results with default method settings (population size, number of generations and others) and without adaptation of the model. Drawbacks of these methods (stochastic behaviour, undefined duration of optimisation, possible stagnation and no guaranty of reaching optima) cau…

Statistics and ProbabilitySucroseMathematical optimizationComputer scienceSystems biology0206 medical engineeringMetabolic network02 engineering and technologyModels BiologicalGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciencesYeastsConvergence (routing)HomeostasisUse caseLimit (mathematics)030304 developmental biologyStochastic Processes0303 health sciencesGeneral Immunology and MicrobiologyApplied MathematicsParticle swarm optimizationGeneral MedicineEnzymesSaccharumConstraint (information theory)Nonlinear systemModeling and SimulationGeneral Agricultural and Biological SciencesMetabolic Networks and Pathways020602 bioinformaticsMathematical Biosciences
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