Search results for "Databases"

showing 10 items of 937 documents

Validation of the SOS/umu test using test results of 486 chemicals and comparison with the Ames test and carcinogenicity data

1996

The present study gives a comprehensive update of all umu genotoxicity assay results published so far. The available data of 486 chemicals investigated with the umu test are compared with the Ames test (274 compounds) as well as rodent carcinogenicity data (179 compounds). On the whole, there is good agreement between the umu test and the Ames test results, with a concordance of about 90%. The umu test was able to detect 86% of the Ames mutagens, while the Ames test (using at least 5 strains) detected 97% of the umu positive compounds. The elimination of TA102 from the set of Ames tester strains reduced the percentage of detectable umu genotoxins from 97 to 86%. The agreement between carcin…

Databases FactualCarcinogenicity TestsRodentiaDNA-Directed DNA PolymeraseToxicologymedicine.disease_causeRodent carcinogenicityAmes testToxicologychemistry.chemical_compoundBacterial ProteinsOperonGeneticsCarcinogenicity testingmedicineAnimalsDegree of certaintySOS Response GeneticsCarcinogenMutagenicity TestsChemistryEscherichia coli ProteinsReproducibility of ResultsGene Expression Regulation BacterialMolecular biologyFurylfuramideMutagenesisGenotoxicityMutation Research/Genetic Toxicology
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PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources.

2019

Background Biological databases and repositories are incrementing in diversity and complexity over the years. This rapid expansion of current and new sources of biological knowledge raises serious problems of data accessibility and integration. To handle the growing necessity of unification, CellBase was created as an integrative solution. CellBase provides a centralized NoSQL database containing biological information from different and heterogeneous sources. Access to this information is done through a RESTful web service API, which provides an efficient interface to the data. Results In this work we present PyCellBase, a Python package that provides programmatic access to the rich RESTfu…

Databases FactualComputer scienceAnnotationBiological databaseRESTfulcomputer.software_genreNoSQLlcsh:Computer applications to medicine. Medical informaticsBiochemistryDatabase03 medical and health sciencesAnnotationUser-Computer Interface0302 clinical medicineInstallationStructural BiologyVariantMolecular Biologylcsh:QH301-705.5030304 developmental biologycomputer.programming_language0303 health sciencesBiological dataDatabaseApplied MathematicsRepositoryComputational BiologyPython (programming language)CellBaseComputer Science Applicationslcsh:Biology (General)Scripting language030220 oncology & carcinogenesislcsh:R858-859.7Web servicecomputerSoftwarePython
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Analysis of Lipid Experiments (ALEX): A Software Framework for Analysis of High-Resolution Shotgun Lipidomics Data

2013

Global lipidomics analysis across large sample sizes produces high-content datasets that require dedicated software tools supporting lipid identification and quantification, efficient data management and lipidome visualization. Here we present a novel software-based platform for streamlined data processing, management and visualization of shotgun lipidomics data acquired using high-resolution Orbitrap mass spectrometry. The platform features the ALEX framework designed for automated identification and export of lipid species intensity directly from proprietary mass spectral data files, and an auxiliary workflow using database exploration tools for integration of sample information, computat…

Databases FactualComputer scienceData managementlcsh:MedicineBioinformaticscomputer.software_genreMass spectrometryMiceUser-Computer InterfaceData visualizationLipidomicsAnimalslcsh:ScienceInternetMultidisciplinarybusiness.industrylcsh:RBrainLipid-phosphate phosphataseShotgun lipidomicsLipidomeLipidsVisualizationSoftware frameworkKnockout mouselcsh:QData miningbusinesscomputerSoftwareResearch ArticlePLoS ONE
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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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FABC: Retinal Vessel Segmentation Using AdaBoost

2010

This paper presents a method for automated vessel segmentation in retinal images. For each pixel in the field of view of the image, a 41-D feature vector is constructed, encoding information on the local intensity structure, spatial properties, and geometry at multiple scales. An AdaBoost classifier is trained on 789 914 gold standard examples of vessel and nonvessel pixels, then used for classifying previously unseen images. The algorithm was tested on the public digital retinal images for vessel extraction (DRIVE) set, frequently used in the literature and consisting of 40 manually labeled images with gold standard. Results were compared experimentally with those of eight algorithms as we…

Databases FactualComputer scienceFeature vectorFeature extractionNormal DistributionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingModels BiologicalEdge detectionArtificial IntelligenceImage Processing Computer-AssistedHumansSegmentationComputer visionAdaBoostFluorescein AngiographyElectrical and Electronic EngineeringTraining setPixelContextual image classificationSettore INF/01 - Informaticabusiness.industryReproducibility of ResultsRetinal VesselsWavelet transformBayes TheoremPattern recognitionGeneral MedicineImage segmentationComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONROC CurveTest setAdaBoost classifier retinal images vessel segmentationArtificial intelligencebusinessAlgorithmsBiotechnology
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Convolutional Neural Network With Shape Prior Applied to Cardiac MRI Segmentation.

2019

In this paper, we present a novel convolutional neural network architecture to segment images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed model is an extension of the U-net that embeds a cardiac shape prior and involves a loss function tailored to the cardiac anatomy. Since the shape prior is computed offline only once, the execution of our model is not limited by its calculation. Our system takes as input raw magnetic resonance images, requires no manual preprocessing or image cropping and is trained to segment the endocardium and epicardium of the left ventricle, the endocardium of the right ventricle, as well as the center of the left ventricle. Wit…

Databases FactualComputer scienceHealth InformaticsImage processingConvolutional neural network030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineHealth Information ManagementSørensen–Dice coefficientImage Processing Computer-AssistedHumansElectrical and Electronic EngineeringArtificial neural networkbusiness.industryMedical image computingCenter (category theory)Pattern recognitionHeartImage segmentationMagnetic Resonance ImagingComputer Science ApplicationsCardiac Imaging TechniquesHausdorff distancecardiovascular systemArtificial intelligenceNeural Networks Computerbusiness030217 neurology & neurosurgeryIEEE journal of biomedical and health informatics
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Increase in norovirus activity reported in Europe.

2006

A large increase in norovirus outbreaks in Hungary and Germany was reported to European national health authorities via the Foodborne Viruses in Europe network

Databases FactualGenotypevirusesMESH : EuropeMESH : GermanyMESH : Health SurveysMESH : GenotypeMESH : Databases FactualMESH : Hungarymedicine.disease_cause[ SDV.MP.VIR ] Life Sciences [q-bio]/Microbiology and Parasitology/VirologyMESH : Information ServicesDisease OutbreaksEnvironmental healthGermanyMESH : Population SurveillancemedicineHumansMESH : Disease OutbreaksComputingMilieux_MISCELLANEOUSCaliciviridae Infections[SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/VirologyNational healthInformation ServicesHungaryMESH : SeasonsMESH : NorovirusIncidenceMESH : HumansNorovirusOutbreakVirologyHealth SurveysMESH : IncidenceGastroenteritisMESH : GastroenteritisEuropeGeographyPopulation SurveillanceNorovirusSeasonsMESH : Caliciviridae InfectionsEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
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A completely automated CAD system for mass detection in a large mammographic database.

2006

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Databases FactualInformation Storage and RetrievalReproducibility of ResultsBreast NeoplasmsSensitivity and SpecificityNeural networkPattern Recognition AutomatedRadiographic Image EnhancementBreast cancerTextural featuresRadiology Information SystemsImage processingComputer-aided detection (CAD)Artificial IntelligenceCluster AnalysisDatabase Management SystemsHumansRadiographic Image Interpretation Computer-AssistedFemaleBreast cancer; Computer-aided detection (CAD); Image processing; Mammographic mass detection; Neural network; Textural featuresMammographic mass detectionAlgorithmsMammographyMedical physics
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A brief history of the formation of DNA databases in forensic science within Europe.

2001

The introduction of DNA analysis to forensic science brought with it a number of choices for analysis, not all of which were compatible. As laboratories throughout Europe were eager to use the new technology different systems became routine in different laboratories and consequently, there was no basis for the exchange of results. A period of co-operation then started in which a nucleus of forensic scientists agreed on an uniform system. This collaboration spread to incorporate most of the established forensic science laboratories in Europe and continued through two major changes in the technology. At each step agreement was reached on which systems to use. From the beginning it was realise…

Databases FactualInternational CooperationLegislationMinisatellite RepeatsBiologycomputer.software_genrePolymerase Chain ReactionSensitivity and SpecificityPathology and Forensic MedicineDNA databaseCrime sceneHumansEthics MedicalDatabaseHistorical ArticleForensic MedicineHistory 20th CenturyDNA FingerprintingForensic scienceEuropeDNA profilingLawcomputerNational DNA databaseNucleic Acid Amplification TechniquesPolymorphism Restriction Fragment LengthCriminal justiceForensic science international
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The short-term efficacy and safety of artificial total disc replacement for selected patients with lumbar degenerative disc disease compared with ant…

2018

PurposeTo systematically compare the efficacy and safety of lumbar total disc replacement (TDR) with the efficacy and safety of anterior lumbar interbody fusion (ALIF) for the treatment of lumbar degenerative disc disease (LDDD).MethodsThe electronic databases PubMed, Web of Science and the Cochrane Library were searched for the period from the establishment of the databases to March 2018. The peer-reviewed articles that investigate the safety and efficacy of TDR and ALIF were retrieved under the given search terms. Quality assessment must be done independently by two authors according to each item of criterion. The statistical analyses were performed using RevMan (version 5.3) and Stata (v…

Databases FactualIntervertebral Disc DegenerationCochrane Librarylaw.inventionDatabase and Informatics MethodsMathematical and Statistical Techniques0302 clinical medicineRandomized controlled triallawMedicine and Health SciencesRange of Motion ArticularDatabase Searching030222 orthopedicsMultidisciplinaryQStatisticsRMetaanalysisResearch AssessmentHospitalsTreatment OutcomeResearch DesignMeta-analysisPhysical SciencesObservational StudiesMedicineRange of motionResearch ArticleTotal Disc Replacementmedicine.medical_specialtySystematic ReviewsClinical Research DesignScienceSurgical and Invasive Medical ProceduresResearch and Analysis MethodsDegenerative disc disease03 medical and health sciencesLumbarmedicineHumansStatistical Methodsbusiness.industryEvidence-based medicinemedicine.diseaseSurgeryHealth CareSpinal FusionHealth Care FacilitiesObservational studyAdverse EventsbusinessPublication BiasMathematics030217 neurology & neurosurgeryPLOS ONE
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