Search results for "quantitative"

showing 10 items of 2409 documents

Additional file 4 of Development and validation of prediction model to estimate 10-year risk of all-cause mortality using modern statistical learning…

2021

Additional file 4. Distributions of the variables at baseline before and after multiple imputations.

Statistics::ApplicationsStatistics::MethodologyQuantitative Biology::GenomicsComputer Science::Operating Systems
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Are there dynamical effects in enzyme catalysis? Some thoughts concerning the enzymatic chemical step.

2015

Highlights • The possible role of enzymatic reaction dynamical effects is examined. • Solution reactions usefully inform the issue of dynamical effects in enzymes. • Division into regions containing and away from the transition state is important. • Motions in passage to/from the transition state need not lead to dynamical effects. • Transition State Theory is usually a reasonable description of enzyme kinetics.

StereochemistryProtein ConformationBiophysicsBiochemistryModels BiologicalVibrationArticleEnzyme catalysisDiffusionTransition state theoryTransition State TheoryEscherichia coli[CHIM]Chemical SciencesStatistical physicsMolecular BiologyQuantumNuclear motionChemistryQuantitative Biology::Molecular Networksdigestive oral and skin physiologyEnzyme catalysisEnzymesEnzyme ActivationKineticsTetrahydrofolate DehydrogenaseDynamical effectsBiocatalysisQuantum TheoryTetrahydrofolate dehydrogenaseProtonsArchives of biochemistry and biophysics
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Investigation of Temperature-Induced Phase Transitions in DOPC and DPPC Phospholipid Bilayers Using Temperature-Controlled Scanning Force Microscopy

2004

Under physiological conditions, multicomponent biological membranes undergo structural changes which help define how the membrane functions. An understanding of biomembrane structure-function relations can be based on knowledge of the physical and chemical properties of pure phospholipid bilayers. Here, we have investigated phase transitions in dipalmitoylphosphatidylcholine (DPPC) and dioleoylphosphatidylcholine (DOPC) bilayers. We demonstrated the existence of several phase transitions in DPPC and DOPC mica-supported bilayers by both atomic force microscopy imaging and force measurements. Supported DPPC bilayers show a broad L(beta)-L(alpha) transition. In addition to the main transition …

Steric effectsPhase transition12-DipalmitoylphosphatidylcholineBiophysicsPhospholipid02 engineering and technologyMicroscopy Atomic Force010402 general chemistry01 natural sciencesPhase TransitionQuantitative Biology::Subcellular Processeschemistry.chemical_compoundTransition TemperaturePhospholipidsPhysics::Biological PhysicsMembranesBilayerTransition temperaturedigestive oral and skin physiologyBiological membrane021001 nanoscience & nanotechnology0104 chemical sciencesCondensed Matter::Soft Condensed MatterCrystallographyMembranechemistryChemical physicsDipalmitoylphosphatidylcholineAluminum Silicateslipids (amino acids peptides and proteins)0210 nano-technologyBiophysical Journal
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Polarization Force Fields for Peptides Implemented in ECEPP2 and MM2

2000

Abstract The empirical conformational energy program for peptides (ECEPP2) and molecular mechanics (MM2) have been used for the simulation of the For-Gly-NH2 backbone. I propose two different methods for the calculation of the polarization energy term: the polarization procedure by non-interacting induced dipoles (NID) which assumes scalar isotropic point polarizabilities and the polarization scheme by interacting induced dipoles (ID) which calculates tensor effective anisotropic point polarizabilities (method of Applequist). I present a comparative study of ECEPP2 and MM2 + polarization. I discuss molecular mechanics results including the total energy differences, partitional analyses of t…

Steric effectsQuantitative Biology::BiomoleculesChemistryGeneral Chemical EngineeringGeneral ChemistryDihedral angleCondensed Matter PhysicsPolarization (waves)Molecular physicsMaxima and minimaDipoleComputational chemistryPolarizabilityModeling and SimulationIntramolecular forceGeneral Materials ScienceAnisotropyInformation SystemsMolecular Simulation
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Role of hydrophobicity on the monoamine receptor binding affinities of central nervous system drugs: a quantitative retention-activity relationships …

2004

Abstract Biological action and activity reflect an aspect of the fundamental physicochemical properties of the bioactive compounds. As an alternative to classical QSAR studies, in this work different quantitative retention–activity relationships (QRAR) models are proposed, which are able to describe the role of hydrophobicity on the binding affinity to different brain monoamine receptors (H 1 -histamine, α 1 -noradrenergic and 5-HT 2 -serotonergic) of different families of psychotherapeutic drugs. The retention of compounds is measured in a biopartitioning micellar chromatography (BMC) system using Brij-35 mobile phases. The adequacy of the QRAR models developed is due to the fact that both…

Steric effectsQuantitative structure–activity relationshipStereochemistryClinical BiochemistryQuantitative Structure-Activity RelationshipSerotonergicBiochemistryAnalytical ChemistryReceptors Biogenic AmineReceptors Adrenergic alpha-1AnimalsReceptors Histamine H1ReceptorMicellesChromatographyChromatographyMolecular StructureChemistryCell MembraneBrainCell BiologyGeneral MedicineAffinitiesMonoamine neurotransmitterSerotonin 5-HT2 Receptor AntagonistsPharmacophoreReceptors Serotonin 5-HT2Quantitative analysis (chemistry)Central Nervous System AgentsJournal of chromatography. B, Analytical technologies in the biomedical and life sciences
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On the Adsorption Process in Polymer Brushes:  A Monte Carlo Study

1996

The adsorption process of the single polymer chain in a polymer brush of varying surface coverages is studied by means of Monte Carlo simulations of the bond-fluctuation lattice model. Only the end monomers can adsorb at the grafting surface, whereas inner monomers interact repulsively with it. The brush builds up a steric hindrance which forces the penetrating polymer to stretch strongly and which is responsible for small adsorption probabilities at surface coverages close to the overlap density. The final step of the adsorption process is determined by a fluctuation of the end monomer around its average position, which is comparable to the initial step of the desorption process.

Steric effectschemistry.chemical_classificationQuantitative Biology::BiomoleculesLattice model (finance)Polymers and PlasticsChemistryOrganic ChemistryMonte Carlo methodPolymerPolymer brushCondensed Matter::Soft Condensed MatterInorganic Chemistrychemistry.chemical_compoundAdsorptionMonomerChemical physicsDesorptionMaterials ChemistryPhysical chemistryMacromolecules
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A Neurocomputational Approach to Trained and Transitive Relations in Equivalence Classes

2017

A stimulus class can be composed of perceptually different but functionally equivalent stimuli. The relations between the stimuli that are grouped in a class can be learned or derived from other stimulus relations. If stimulus A is equivalent to B, and B is equivalent to C, then the equivalence between A and C can be derived without explicit training. In this work we propose, with a neurocomputational model, a basic learning mechanism for the formation of equivalence. We also describe how the relatedness between the members of an equivalence class is developed for both trained and derived stimulus relations. Three classic studies on stimulus equivalence are simulated covering typical and at…

Stimulus equivalencePure mathematicslcsh:BF1-990Stimulus (physiology)Machine learningcomputer.software_genre03 medical and health sciencesBasic learning0302 clinical medicinePsychology0501 psychology and cognitive sciences050102 behavioral science & comparative psychologyNodal distanceEquivalence classGeneral PsychologyOriginal ResearchTransitive relationQuantitative Biology::Neurons and Cognitionbusiness.industryneurocomputational modelequivalence classes05 social sciencestransitive relationscategorizationlcsh:PsychologyHebbian theoryCategorizationArtificial intelligenceHebbian learningbusinessPsychologycomputer030217 neurology & neurosurgeryFrontiers in Psychology
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Bond-based 3D-chiral linear indices: Theory and QSAR applications to central chirality codification

2008

The recently introduced non-stochastic and stochastic bond-based linear indices are been generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. These improved modified descriptors are applied to several well-known data sets to validate each one of them. Particularly, Cramer's steroid data set has become a benchmark for the assessment of novel quantitative structure activity relationship methods. This data set has been used by several researchers using 3D-QSAR approaches such as Comparative Molecular Field Analysis, Molecular Quantum Similarity Measures, Comparative Molecular Moment Analysis, E-state, Mapping Prope…

Stochastic ProcessesQuantitative structure–activity relationshipIndolesProperty (programming)ChemistryComparabilityQuantitative Structure-Activity RelationshipAngiotensin-Converting Enzyme InhibitorsStereoisomerismGeneral ChemistrySet (abstract data type)Data setComputational MathematicsModels ChemicalPiperidinesComputational chemistryDrug DesignBenchmark (computing)Molecular symmetryCombinatorial Chemistry TechniquesReceptors sigmaThermodynamicsTrigonometryAlgorithmJournal of Computational Chemistry
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A stochastic interspecific competition model to predict the behaviour of Listeria monocytogenes in the fermentation process of a traditional Sicilian…

2008

The present paper discusses the use of modified Lotka-Volterra equations in order to stochastically simulate the behaviour of Listeria monocytogenes and Lactic Acid Bacteria (LAB) during the fermentation period (168 h) of a typical Sicilian salami. For this purpose, the differential equation system is set considering T, pH and aw as stochastic variables. Each of them is governed by dynamics that involve a deterministic linear decrease as a function of the time t and an "additive noise" term which instantaneously mimics the fluctuations of T, pH and aw. The choice of a suitable parameter accounting for the interaction of LAB on L. monocytogenes as well as the introduction of appropriate nois…

Stochastic approachWater activityDifferential equationStochastic modellingBiologymedicine.disease_causeBiochemistryNoise (electronics)Industrial and Manufacturing EngineeringQuantitative Biology::Cell BehaviorInterspecific competition modelListeria monocytogenesLactic acid bacteriamedicineQuantitative Biology - Populations and EvolutionListeria monocytogenePredictive microbiologybusiness.industryPopulations and Evolution (q-bio.PE)Environmental noiseGeneral ChemistryFunction (mathematics)Listeria monocytogenesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)BiotechnologyPredictive microbiology; Interspecific competition model; Stochastic approach; Environmental noise; Listeria monocytogenes; Lactic acid bacteriaFOS: Biological sciencesProbability distributionFermentationBiological systembusinessFood ScienceBiotechnologyEuropean Food Research and Technology
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Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics

2013

In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…

Stochastic modellingFOS: Physical sciencesStructural basinBiologyRandom processe01 natural sciencesIntraspecific competitionMediterranean sea0103 physical sciencesPhytoplanktonMarine ecosystemSpatial ecologyMarine ecosystem14. Life underwaterQuantitative Biology - Populations and Evolution010306 general physicsPhytoplankton dynamic010301 acousticsEcology Evolution Behavior and SystematicsDeep chlorophyll maximumEcologyEcological ModelingPopulations and Evolution (q-bio.PE)Spatial ecology; Marine ecosystems; Phytoplankton dynamics; Deep chlorophyll maximum; Random processes; Stochastic differential equationsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Oceanography13. Climate actionPhysics - Data Analysis Statistics and ProbabilityFOS: Biological sciencesSpatial ecologyStochastic differential equationsDeep chlorophyll maximumData Analysis Statistics and Probability (physics.data-an)
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