Search results for " selection"

showing 10 items of 1271 documents

[Pharmacogenomics of antiretrovirals].

2008

HIV infection is a serious but treatable disease, yet current treatment is limited by development of resistance and high rates of adverse drug reactions. Antiretroviral therapy is especially suitable for pharmacogenomic investigation as both drug exposure and treatment response can be reliably measured. Increasing knowledge about genes implicated in pharmacokinetics, mode of action, efficacy, and toxicity of drugs has already provided relevant results for clinical practice, for example: The strong association of the abacavir hypersensitivity reaction with HLA-B*5701 permits testing patients for the allele, and if present avoiding the drug and therefore preventing the reaction. Persons with …

CyclopropanesDrugEfavirenzPyridinesmedia_common.quotation_subjectAtazanavir SulfateDiseaseBioinformaticsDrug HypersensitivityPatents as Topicchemistry.chemical_compoundPharmacokineticsCentral Nervous System DiseasesHLA AntigensAbacavirDrug Resistance ViralDrug DiscoveryMedicineHumansGenetic Predisposition to DiseasePharmacology (medical)Genetic TestingNevirapineGlucuronosyltransferaseDyslipidemiasHyperbilirubinemiamedia_commonRitonavirbusiness.industryPatient SelectionArea under the curveOxidoreductases N-DemethylatingGeneral MedicineDideoxynucleosidesBenzoxazinesHypersensitivity reactionCytochrome P-450 CYP2B6Infectious DiseaseschemistryAnti-Retroviral AgentsPharmacogeneticsAlkynesPharmacogenomicsAryl Hydrocarbon HydroxylasesbusinessOligopeptidesmedicine.drugMedicina clinica
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DBSCAN Algorithm for Document Clustering

2019

Abstract Document clustering is a problem of automatically grouping similar document into categories based on some similarity metrics. Almost all available data, usually on the web, are unclassified so we need powerful clustering algorithms that work with these types of data. All common search engines return a list of pages relevant to the user query. This list needs to be generated fast and as correct as possible. For this type of problems, because the web pages are unclassified, we need powerful clustering algorithms. In this paper we present a clustering algorithm called DBSCAN – Density-Based Spatial Clustering of Applications with Noise – and its limitations on documents (or web pages)…

DBSCANInformation retrievalSimilarity (network science)Computer scienceWeb pageFeature selectionDocument clusteringCluster analysisData typeWord (computer architecture)International Journal of Advanced Statistics and IT&C for Economics and Life Sciences
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Codominance of Lactobacillus plantarum and obligate heterofermentative lactic acid bacteria during sourdough fermentation

2015

Fifteen sourdoughs produced in western Sicily (southern Italy) were analysed by classical methods for their chemico-physical characteristics and the levels of lactic acid bacteria (LAB). pH and total titratable acidity (TTA) were mostly in the range commonly reported for similar products produced in Italy, but the fermentation quotient (FQ) of the majority of samples was above 4.0, due to the low concentration of acetic acid estimated by high performance liquid chromatography (HPLC). Specific counts of LAB showed levels higher than 10(8) CFU g(-1) for many samples. The colonies representing various morphologies were isolated and, after the differentiation based on phenotypic characteristics…

DNA BacterialBacterial codominanceStarter selectionTitratable acidPolymerase Chain ReactionMicrobiologyMicrobiologychemistry.chemical_compoundAcetic acidStarterBacteriocinsRNA Ribosomal 16SLactic acid bacteriaLactic AcidAcetic Acidbiologyfood and beveragesBreadSettore AGR/15 - Scienze E Tecnologie Alimentaribiology.organism_classificationLactic acidRAPDRandom Amplified Polymorphic DNA TechniqueLactobacillusBacterial codominance; Lactic acid bacteria; Lactobacillus plantarum; Sourdough; Starter selection; Food Science; MicrobiologyPhenotypechemistryItalySourdoughFermentationFood MicrobiologyMicrobial InteractionsFermentationGenetic FitnessLactobacillus plantarumBacteriaLactobacillus plantarumFood ScienceSettore AGR/16 - Microbiologia Agraria
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UVPAR: fast detection of functional shifts in duplicate genes.

2006

Abstract Background The imprint of natural selection on gene sequences is often difficult to detect. A plethora of methods have been devised to detect genetic changes due to selective processes. However, many of those methods depend heavily on underlying assumptions regarding the mode of change of DNA sequences and often require sophisticated mathematical treatments that made them computationally slow. The development of fast and effective methods to detect modifications in the selective constraints of genes is therefore of great interest. Results We describe UVPAR, a program designed to quickly test for changes in the functional constraints of duplicate genes. Starting with alignments of t…

DanioComputational biologyBiologylcsh:Computer applications to medicine. Medical informaticsBiochemistryDNA sequencingEvolution MolecularGenes DuplicateSequence Analysis ProteinStructural BiologySelection GeneticHox geneMolecular BiologyGenelcsh:QH301-705.5Selection (genetic algorithm)GeneticsNatural selectionApplied MathematicsProteinsSequence Analysis DNAbiology.organism_classificationComputer Science Applicationslcsh:Biology (General)lcsh:R858-859.7DNA microarraySequence AlignmentSoftwareAlgorithmsGenètica
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Context matters-consensus molecular subtypes of colorectal cancer as biomarkers for clinical trials

2019

Abstract The Colorectal Cancer Subtyping Consortium identified four gene expression consensus molecular subtypes, CMS1 (immune), CMS2 (canonical), CMS3 (metabolic), and CMS4 (mesenchymal), using multiple microarray or RNA-sequencing datasets of primary tumor samples mainly from early stage colon cancer patients. Consequently, rectal tumors and stage IV tumors (possibly reflective of more aggressive disease) were underrepresented, and no chemo- and/or radiotherapy pretreated samples or metastatic lesions were included. In view of their possible effect on gene expression and consequently subtype classification, sample source and treatments received by the patients before collection must be ca…

Data Analysis0301 basic medicineOncologymedicine.medical_specialtyMicroarrayconsensus molecular subtypesColorectal cancermedicine.medical_treatmentDatasets as TopicReviews03 medical and health sciencesstratification0302 clinical medicineBiasCàncer colorectalInternal medicineBiomarkers TumormedicineHumansRNA-SeqOligonucleotide Array Sequence AnalysisClinical Trials as Topicclinical trialsbusiness.industryPatient SelectionBiochemical markersbiomarkersChemoradiotherapypersonalized medicineHematologyPrognosismedicine.diseaseChemotherapy regimenPrimary tumorColorectal cancerSubtypingRadiation therapyClinical trialTreatment Outcome030104 developmental biologyOncology030220 oncology & carcinogenesisMutationgene expressionPersonalized medicineNeoplasm Recurrence LocalColorectal NeoplasmsbusinessMarcadors biomquímics
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Parameter Rating by Diffusion Gradient

2014

Anomaly detection is a central task in high-dimensional data analysis. It can be performed by using dimensionality reduction methods to obtain a low-dimensional representation of the data, which reveals the geometry and the patterns that exist and govern it. Usually, anomaly detection methods classify high-dimensional vectors that represent data points as either normal or abnormal. Revealing the parameters (i.e., features) that cause detected abnormal behaviors is critical in many applications. However, this problem is not addressed by recent anomaly-detection methods and, specifically, by nonparametric methods, which are based on feature-free analysis of the data. In this chapter, we provi…

Data pointbusiness.industryComputer scienceDimensionality reductionNonparametric statisticsDiffusion mapAnomaly detectionFeature selectionPattern recognitionArtificial intelligenceAbnormalityRepresentation (mathematics)business
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Context-related data processing in artificial neural networks for higher reliability of telerehabilitation systems

2015

Classification is a data processing technique of a great significance both for native eHealth systems and web telemedicine solutions. In this sense, artificial neural networks have been widely applied in telerehabilitation as powerful tools to process information and acquire a new medical knowledge. But effective analysis of multidimensional heterogeneous medical data, still poses considerable difficulties. It was shown that processing too many data features simultaneously is costly and has some adverse effects on the resulting models classification properties. Therefore, there is a strong need to develop new techniques for selecting features from the very large data sets that include many …

Data processingArtificial neural networkComputer sciencebusiness.industryReliability (computer networking)Feature selectionContext (language use)computer.software_genreMachine learningData acquisitionTelerehabilitationeHealthData miningArtificial intelligencebusinesscomputer2015 17th International Conference on E-health Networking, Application & Services (HealthCom)
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Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis

2006

Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…

Databases FactualComputer scienceFeature extractionInformation Storage and RetrievalFeature selectionMachine learningcomputer.software_genreModels BiologicalPattern Recognition AutomatedImmune systemArtificial IntelligenceDrug Resistance BacterialCluster AnalysisHumansComputer SimulationElectrical and Electronic EngineeringRepresentation (mathematics)Cluster analysisCross Infectionbusiness.industryDimensionality reductionSupervised learningGeneral MedicineAnti-Bacterial AgentsComputer Science ApplicationsData pre-processingData miningArtificial intelligenceMultidimensional systemsbusinesscomputerAlgorithmsBiotechnology
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Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex

2019

14 páginas, 6 figuras

Datasets as TopicGene ExpressionBacterial lineagesPopulation genomicsNegative selectionMUTATIONPathogenSensor kinaseResearch ArticlesHistory AncientPhylogenyRecombination Genetic0303 health sciencesMultidisciplinaryHYPOTHESIS1184 Genetics developmental biology physiologySciAdv r-articlesLINEAGE3. Good healthPast and presentPositive selectionMycobacterium tuberculosis complexHost-Pathogen InteractionsTwo component systemsResearch ArticleLineage (genetic)Genetic SpeciationVirulence FactorsVirulenceBiologyMicrobiologyHistory 21st CenturyRecombination eventsMycobacterium03 medical and health sciencesBacterial ProteinsGenetic algorithmGeneticsHumansTuberculosisSelection GeneticGene030304 developmental biologyGenetic locus030306 microbiologyMycobacterium tuberculosis complexesMycobacterium tuberculosisbiology.organism_classificationEVOLUTIONGenetic SpeciationGenetic LociEvolutionary biologyVIRULENCEAdaptationGenome BacterialRESISTANCE
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LANDFILL SITE SELECTION FOR MUNICIPAL SOLID WASTE BY USING AHP METHOD IN GIS ENVIRONMENT: WASTE MANAGEMENT DECISION-SUPPORT IN SICILY (ITALY)

2018

The goal of this work was to test a methodology, based on multi-criteria analysis and geographic information systems, aimed at identifying areas potentially suitable to host landfills for Municipal Solid Waste (MSW). Although the above-mentioned methodology was applied to three different areas (Western, South-western and Eastern) of Sicily, in this paper, we present the results of the western sector. The first step consisted of the division of the study area in excluded and potentially suitable sites, on the basis of the Italian current legislation. The suitable sites were subsequently re-evaluated based on additional criteria in order to choose the most suitable ones. This second step cons…

Decision support systemEnvironmental EngineeringMunicipal solid wasteGeographic information system010504 meteorology & atmospheric sciencesbusiness.industryScale (chemistry)Environmental resource managementSite selectionAnalytic hierarchy process010502 geochemistry & geophysics01 natural sciencesWeightinglcsh:Environmental engineeringRankinglcsh:Environmental pollutionlcsh:TD172-193.5Environmental ChemistryEnvironmental sciencelcsh:TA170-171businessWaste Management and DisposalMunicipal solid waste Landfill Analytical hierarchy process Geographic information system Sicily0105 earth and related environmental sciencesDetritus
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