Search results for "Test set"

showing 10 items of 50 documents

The impact of ocean acidification and warming on the skeletal mechanical properties of the sea urchin Paracentrotus lividus from laboratory and field…

2016

Increased atmospheric CO2 concentration is leading to changes in the carbonate chemistry and the temperature of the ocean. The impact of these processes on marine organisms will depend on their ability to cope with those changes, particularly the maintenance of calcium carbonate structures. Both a laboratory experiment (long-term exposure to decreased pH and increased temperature) and collections of individuals from natural environments characterized by low pH levels (individuals from intertidal pools and around a CO2 seep) were here coupled to comprehensively study the impact of near-future conditions of pH and temperature on the mechanical properties of the skeleton of the euechinoid sea …

Ocean Acidification International Coordination Centre (OA-ICC)IdentificationSalinityTemperateinorganicAlkalinityAreaExperimentTemperature waterCarbon inorganic dissolvedCalculated using seacarb after Nisumaa et al 2010Aragonite saturation stateMesocosm or benthocosmAlkalinity totaltotalYoung s moduluspHNorth AtlanticTemperatureProportiondissolvedCarbonate ionLaboratory experimentPartial pressure of carbon dioxide (water) at sea surface temperature (wet air)Earth System ResearchField observationThicknessEchinodermataCalcite saturation stateLengthwaterYoung's modulusGrowth MorphologyBenthosReplicateDiameterHardnessOther studied parameter or processOcean Acidification International Coordination Centre OA ICCAnimaliaBicarbonate ionCalculated using seacarb after Nisumaa et al. (2010)ForceSpeciesHeightTest setCarbonate system computation flagFugacity of carbon dioxide (water) at sea surface temperature (wet air)CarbonTreatmentPartial pressure of carbon dioxide water at sea surface temperature wet airCarbon dioxideParacentrotus lividusGrowth/MorphologySingle speciesBenthic animalsFugacity of carbon dioxide water at sea surface temperature wet airCoast and continental shelfSecond moment of area
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A topological sub-structural approach for predicting human intestinal absorption of drugs.

2004

The human intestinal absorption (HIA) of drugs was studied using a topological sub-structural approach (TOPS-MODE). The drugs were divided into three classes according to reported cutoff values for HIA. "Poor" absorption was defined as HIAor =30%, "high" absorption as HIAor =80%, whereas "moderate" absorption was defined between these two values (30%HIA79%). Two linear discriminant analyses were carried out on a training set of 82 compounds. The percentages of correct classification, for both models, were 89.02%. The predictive power of the models were validated by three test: a leave-one-out cross validation procedure (88.9% and 87.9%), an external prediction set of 127 drugs (92.9% and 80…

PharmacologyQuantitative structure–activity relationshipChemistryOrganic ChemistryBiological AvailabilityQuantitative Structure-Activity RelationshipGeneral MedicineModels TheoreticalLinear discriminant analysisTopologyCross-validationIntestinal absorptionBioavailabilityIntestinal AbsorptionPharmaceutical PreparationsTest setDrug DiscoveryHuman intestinal absorptionCutoffHumansIntestinal MucosaEuropean journal of medicinal chemistry
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Prediction of Aquatic Toxicity of Benzene Derivatives to Tetrahymena pyriformis According to OECD Principles

2016

Background: Many QSAR studies have been developed to predict acute toxicity over several biomarkers like Pimephales promelas, Daphnia magna and Tetrahymena pyriformis. Regardless of the progress made in this field there are still some gaps to be resolved such as the prediction of aquatic toxicity over the protozoan T. pyriformis still lack a QSAR study focused in accomplish the OECD principles. Methods: Atom-based quadratic indices are used to obtain quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. Our models agree with the principles required by the OECD for QSAR models to regulatory purposes. The database employed consists of 392 substitut…

PharmacologyQuantitative structure–activity relationshipTetrahymena pyriformisAntiprotozoal AgentsQuantitative Structure-Activity Relationship010501 environmental sciencesBiology01 natural sciencesAcute toxicity0104 chemical sciencesAquatic toxicologyToxicology010404 medicinal & biomolecular chemistryParasitic Sensitivity TestsTest setDrug DiscoveryBenzene derivativesLinear regressionTetrahymena pyriformisBenzene DerivativesBiological systemMonte Carlo MethodAlgorithmsBootstrapping (statistics)0105 earth and related environmental sciencesCurrent Pharmaceutical Design
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The Prediction of Human Intestinal Absorption Based on the Molecular Structure

2014

Human Intestinal Absorption (HIA) has been modeled many times by using classification models. However, regression models are scarce. Here, Artificial Neural Networks (ANNs) are implemented for this purpose. A dataset of structurally diverse chemicals with their respective experimental HIA were used to design robust, true predictive and widespread applicable ANN models. An input variables pool was made up of structural invariants calculated by using either Dragon or our software Desmol 1. The selection of best variables was performed following three steps using the entire dataset of molecules. Firstly, variables poorly correlated with the experimental data were eliminated. Secondly, input va…

Pharmacologyeducation.field_of_studyMolecular StructureArtificial neural networkComputer sciencebusiness.industryClinical BiochemistryPopulationReproducibility of ResultsPattern recognitionFeature selectionRegression analysisModels TheoreticalBackpropagationIntestinal absorptionIntestinal AbsorptionPharmaceutical PreparationsResamplingTest setHumansNeural Networks ComputerArtificial intelligenceeducationbusinessCurrent Drug Metabolism
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Assessment of the accuracy of coupled cluster perturbation theory for open-shell systems. I. Triples expansions

2016

The accuracy at which total energies of open-shell atoms and organic radicals may be calculated is assessed for selected coupled cluster perturbative triples expansions, all of which augment the coupled cluster singles and doubles (CCSD) energy by a non-iterative correction for the effect of triple excitations. Namely, the second- through sixth-order models of the recently proposed CCSD(T-n) triples series [J. Chem. Phys. 140, 064108 (2014)] are compared to the acclaimed CCSD(T) model for both unrestricted as well as restricted open-shell Hartree-Fock (UHF/ROHF) reference determinants. By comparing UHF- and ROHF-based statistical results for a test set of 18 modest-sized open-shell species …

PhysicsChemical Physics (physics.chem-ph)010304 chemical physicsSeries (mathematics)General Physics and AstronomyFOS: Physical sciences010402 general chemistry01 natural sciences0104 chemical sciencesCoupled clusterRate of convergenceConsistency (statistics)Quantum mechanicsTest setPhysics - Chemical Physics0103 physical sciencesPhysics::Atomic and Molecular ClustersPerturbation theory (quantum mechanics)Physical and Theoretical ChemistryPhysics::Chemical PhysicsOpen shell
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The Use of Rule-Based and QSPR Approaches in ADME Profiling: A Case Study on Caco-2 Permeability.

2013

During the early ADME profiling the development of simple, interpretable and reliable in silico tools is very important. In this study, rule-based and QSPR approaches were investigated using a large Caco-2 permeability database. Three permeability classes were determined: high (H), moderate (M) and low (L). The main physicochemical properties related with permeability were ranked as follows: Polar Surface Area (PSA)>Lipophilicity (logP/logD)>Molecular Weight (MW)>number of Hydrogen Bond donors and acceptors>Ionization State>number of Rotatable Bonds>number of Rings. The best rule, based on the combination of PSA-MW-logD (3PRule), was able to identify the H, M and L classes with accuracy of …

Profiling (computer programming)Quantitative structure–activity relationshipChemistryOrganic ChemistryRule-based systemCombinatorial chemistryComputer Science ApplicationsPolar surface areaBinary classificationStructural BiologyTest setDrug DiscoveryLipophilicityMolecular MedicineBiological systemADMEMolecular informatics
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Automated quality control protocol for MR spectra of brain tumors.

2008

Item does not contain fulltext eTUMOUR (http://www.etumour.net/) is acquiring a large database of brain tumor (1)H MR spectra to develop automated pattern recognition methods and decision support system (DSS) for tumor diagnosis. Development of accurate pattern-recognition algorithms requires spectra undistorted by artifacts, low signal-to-noise, or broad lines. eTUMOUR currently uses panels of expert spectroscopists to subjectively grade spectra as being acceptable or unacceptable. Automated quality control (QC) would be more satisfactory for several reasons: 1) to provide a reproducible objective classification of spectrum quality; 2) for use within the future DSS to prevent misdiagnosis …

Quality ControlProtocol (science)Decision support systemMagnetic Resonance SpectroscopyBrain NeoplasmsComputer sciencemedia_common.quotation_subjectFeature extractioncomputer.software_genreIndependent component analysisDecision Support TechniquesPattern Recognition AutomatedTest setPattern recognition (psychology)Support vector machine classifierHumansRadiology Nuclear Medicine and imagingQuality (business)Functional Imaging [UMCN 1.1]Data miningcomputermedia_commonMagnetic Resonance in Medicine
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A topological substructural approach for the prediction of P-glycoprotein substrates

2006

A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the predictio…

Quantitative structure–activity relationshipMolecular modelLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisTopologyModels BiologicalData setSet (abstract data type)Pharmaceutical PreparationsPredictive Value of TestsTest setLinear ModelsComputer SimulationATP Binding Cassette Transporter Subfamily B Member 1Sensitivity (control systems)FluoroquinolonesMathematicsJournal of Pharmaceutical Sciences
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Combined use of PCA and QSAR/QSPR to predict the drugs mechanism of action. An application to the NCI ACAM Database

2009

During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of …

Quantitative structure–activity relationshipMultivariate analysisDatabaseArtificial neural networkMechanism (biology)Computer scienceOrganic Chemistrycomputer.software_genreSettore CHIM/08 - Chimica FarmaceuticaComputer Science ApplicationsSet (abstract data type)Mechanism of actionTest setDrug DiscoveryPrincipal component analysisAnti-cancer Agent Mechanism database PCA QSAR/QSPR Mechanism of actionmedicineData miningmedicine.symptomcomputer
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Atom-Based Quadratic Indices to Predict Aquatic Toxicity of Benzene Derivatives to <i>Tetrahymena pyriformis</i>

2009

The non-stochastic and stochastic atom-based quadratic indices are applied to develop quantitative structure-activity relationship (QSAR) models for the prediction of aquatic toxicity. The used dataset, consisting of 392 benzene derivatives for which toxicity data to the ciliate Tetrahymena pyriformis were available, is divided into training and test sets. The obtained multiple linear regression models are statistically significant (R2 = 0.787 and s = 0.347, R2 = 0.806 and s = 0.329, for non-stochastic and stochastic quadratic indices, respectively) and show rather good stability in a cross-validation experiment (q2 = 0.769 and scv = 0.357, q2 = 0.791 and scv = 0.337, correspondingly). In a…

Quantitative structure–activity relationshipQuadratic equationTest setToxicityLinear regressionTetrahymena pyriformisBiological systemStability (probability)MathematicsAquatic toxicologyProceedings of The 13th International Electronic Conference on Synthetic Organic Chemistry
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