Search results for "Discriminant Analysis"

showing 10 items of 229 documents

Application of molecular topology to the prediction of antifungal activity for a set of dication-substituted carbazoles, furans and benzimidazoles

2003

In this paper, the endpoint is the application of molecular topology to the search of QSAR relations into a group of dicationsubstituted carbazoles, furans and benzimidazoles, all showing antifungal activity against C. albicans. Mathematical and statistical methods such as linear regression and discriminant analysis, are used to goal. The obtained results clearly show a high efficiency of the formalism on the prediction and classification of antifungal activity. 83% of the compounds showing MIC , 10 mg/ml (active group) are correctly classified, whilst 100% overall accuracy is achieved for those compounds showing MIC . 100 mg/ml (inactive group). q 2003 Elsevier Science B.V. All rights rese…

AntifungalQuantitative structure–activity relationshipmedicine.drug_classStereochemistryChemistryCondensed Matter PhysicsLinear discriminant analysisBiochemistryDicationFormalism (philosophy of mathematics)Linear regressionmedicinePhysical and Theoretical ChemistryMolecular topologyActive groupJournal of Molecular Structure: THEOCHEM
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Comparative study to predict toxic modes of action of phenols from molecular structures.

2013

Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…

Antiprotozoal AgentsQuantitative Structure-Activity RelationshipBioengineeringMachine learningcomputer.software_genreConstant false alarm ratePhenolsArtificial IntelligenceDrug DiscoveryTraining setModels StatisticalArtificial neural networkCiliated protozoanMolecular StructureChemistrybusiness.industryTetrahymena pyriformisGeneral MedicineLinear discriminant analysisSupport vector machineTest setTetrahymena pyriformisMolecular MedicineArtificial intelligenceNeural Networks ComputerBiological systembusinesscomputerSAR and QSAR in environmental research
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Biological mineral content in Iberian skeletal cremains for control of diagenetic factors employing multivariate statistics

2013

Abstract The aim of this study was to define a strategy for a correct selection of bone samples by employing inductively coupled plasma optical emission spectroscopy (ICP-OES) for reconstructing the biological mineral content in bones through the determination of major elements, trace elements and Rare Earth Elements (REE, lanthanides) in skeletal cremains of ancient Iberians (III–II B.C), discovered in the Necropolis of Corral de Saus (Moixent, Valencia) between 1972 and 1979. The biological mineral content was determined taking into account diagenetic factors. A control method for a better reading of results was applied. To explore large geochemical datasets and to reduce the number of va…

ArcheologyMultivariate statisticsSoil testInductively coupled plasma atomic emission spectroscopyPrincipal component analysisPartial least squares regressionDendrogramMineralogyLinear discriminant analysisGeologyDiagenesisJournal of Archaeological Science
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Artificial Neural Networks and Linear Discriminant Analysis:  A Valuable Combination in the Selection of New Antibacterial Compounds

2004

A set of topological descriptors has been used to discriminate between antibacterial and nonantibacterial drugs. Topological descriptors are simple integers calculated from the molecular structure represented in SMILES format. The methods used for antibacterial activity discrimination were linear discriminant analysis (LDA) and artificial neural networks of a multilayer perceptron (MLP) type. The following plot frequency distribution diagrams were used: a function of the number of drugs within a value interval of the discriminant function and the output value of the neural network versus these values. Pharmacological distribution diagrams (PDD) were used as a visualizing technique for the i…

Artificial neural networkChemistrybusiness.industryComputer Science::Neural and Evolutionary ComputationDiscriminant AnalysisPattern recognitionGeneral MedicineMicrobial Sensitivity TestsGeneral ChemistryFunction (mathematics)Interval (mathematics)Linear discriminant analysisPlot (graphics)Anti-Bacterial AgentsQuantitative Biology::Cell BehaviorComputer Science ApplicationsComputational Theory and MathematicsDiscriminative modelDiscriminant function analysisMultilayer perceptronNeural Networks ComputerArtificial intelligencebusinessInformation SystemsMathematicsJournal of Chemical Information and Computer Sciences
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Classification of Satellite Images with Regularized AdaBoosting of RBF Neural Networks

2008

Artificial neural networkbusiness.industryPattern recognitionMachine learningcomputer.software_genreLinear discriminant analysisAdaboost algorithmSupport vector machineGeographySatelliteRadial basis functionArtificial intelligenceAdaBoostbusinesscomputer
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Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.

2013

Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single…

BioinformaticsHealth InformaticsMicroarray data analysisRobustness (computer science)Databases GeneticCluster AnalysisHumansManifoldsCluster analysisMathematicsOligonucleotide Array Sequence Analysisbusiness.industryDimensionality reductionGene Expression ProfilingComputational BiologyDiscriminant AnalysisPattern recognitionSparse approximationLinear discriminant analysisManifoldComputer Science ApplicationsFISICA APLICADAEmbeddingAutomatic classificationArtificial intelligencebusinessGlioblastomaMeningiomaTranscriptomeAlgorithmsCurse of dimensionalityComputers in biology and medicine
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The Application of Machine Learning Algorithms to the Analysis of Electromyographic Patterns From Arthritic Patients

2009

The main aim of our study was to investigate the possibility of applying machine learning techniques to the analysis of electromyographic patterns (EMG) collected from arthritic patients during gait. The EMG recordings were collected from the lower limbs of patients with arthritis and compared with those of healthy subjects (CO) with no musculoskeletal disorder. The study involved subjects suffering from two forms of arthritis, viz, rheumatoid arthritis (RA) and hip osteoarthritis (OA). The analysis of the data was plagued by two problems which frequently render the analysis of this type of data extremely difficult. One was the small number of human subjects that could be included in the in…

Biomedical EngineeringArthritisElectromyographyMachine learningcomputer.software_genreGait (human)Musculoskeletal disorderArtificial IntelligenceInternal MedicineHumansMedicineGaitArtificial neural networkmedicine.diagnostic_testElectromyographybusiness.industryArthritisData CollectionGeneral NeuroscienceRehabilitationReproducibility of ResultsSignal Processing Computer-AssistedLinear discriminant analysismedicine.diseaseBiomechanical PhenomenaKernel methodROC CurveMultilayer perceptronArtificial intelligencebusinesscomputerAlgorithmAlgorithmsIEEE Transactions on Neural Systems and Rehabilitation Engineering
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Varietal and geographic classification of french red wines in terms of elements, amino acids and aromatic alcohols

1988

Thirty-four French red wines from three regions already studied for their anthocyanin and flavonoid constituents have been further analysed for elements, amino acids and aromatic alcohols. An interpretation of the differences between wines related to their different geographic and varietal origins has been made from the results of statistical analyses: F statistic, principal component analysis (PCA) and stepwise discriminant analysis (SDA). Wine samples produced near Bordeaux were found to be characterised by higher rubidium and lower lithium and calcium concentrations. Differences between wine samples made from the same grape variety or produced in the same region are mainly related to dif…

Bordeaux wineFlavonoid01 natural scienceschemistry.chemical_compound0404 agricultural biotechnologyEthanolamine[SDV.IDA]Life Sciences [q-bio]/Food engineeringFood scienceChemical compositionComputingMilieux_MISCELLANEOUSWinechemistry.chemical_classificationNutrition and DieteticsChemistryStepwise discriminant analysisdigestive oral and skin physiology010401 analytical chemistryfood and beverages04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food science0104 chemical sciencesAmino acidAnthocyaninAgronomy and Crop ScienceFood ScienceBiotechnology
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Chemometrics as a Tool of Origin Determination of Polish Monofloral and Multifloral Honeys

2014

The aim of this study was to evaluate the application of chemometrics studies to determine the botanical origin of Polish monofloral honeys using NMR spectroscopy. Aqueous extracts of six kinds of honeys, namely, heather (Calluna vulgaris L.), buckwheat (Fagopyrum esculentum L), lime (Tilia L), rape (Brassica napus L. var. napus), acacia (Acacia Mill.), and multifloral ones, were analyzed. Multivariate chemometric data analysis was performed using principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Chemometric analysis supported by pollen analysis revealed the incorrect classification of acacia honeys by the producers. Characteristic moti…

CallunaMagnetic Resonance Spectroscopychemical profilefloral markersAcaciaFlowersmedicine.disease_causechemical fingerprintingChemometricsTiliaPollenBotanymedicine1H NMR spectroscopyorigin of honeyPrincipal Component AnalysisPCAbiologyChemistryDiscriminant AnalysisHoneyGeneral Chemistrychemometricsbiology.organism_classificationOPLS-DAPrincipal component analysisPolandGeneral Agricultural and Biological SciencesChemical fingerprintingFagopyrumJournal of Agricultural and Food Chemistry
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Sexing adult Cory's Shearwater by discriminant analysis of body measurements on Linosa Island (Sicilian Channel), Italy

2001

-Males and females of many avian species may show no plumage dimorphism, but often can be sexed by differences in body measurements. Sex determination of many Cory's Shearwaters Calonectris diomedea, was possible by multiplying bill length by bill depth. In this study, discriminant analysis of six measurements (bill length, bill depth, wing, tail, tarsus and mass) was performed on Cory's Shearwaters breeding on Linosa Island (Sicilian Channel), Italy and the efficiency of sex determination was compared with the univariate method. Results show the advantages of the discriminant functions. Bill depth is the best parameter (up to 92% correct classification), followed by mass (84% correct class…

Calonectris diomedeaDiscriminant analysiZoologySexingBiologyLinear discriminant analysisbiology.organism_classificationlanguage.human_languageSexual dimorphismPlumageCory's ShearwaterlanguageCalonectris diomedeaAnimal Science and ZoologyCory's shearwaterSicilianSicily
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