Search results for " data"

showing 10 items of 7516 documents

Making sense of big data in health research: {T}owards an {EU} action plan

2016

Genome medicine 8(1), 71 (2016). doi:10.1186/s13073-016-0323-y

0301 basic medicineBiomedical ResearchDatabases FactualPREDICTIONComputer scienceBig data: Santé publique services médicaux & soins de santé [D22] [Sciences de la santé humaine]XXBioinformaticsBases de dadesSYSTEMS MEDICINE0302 clinical medicineINFORMATICSCultural diversityHealth careGenetics(clinical)030212 general & internal medicineGenetics (clinical)media_commonGenetics & HeredityExabyteCHALLENGESMacrodadesCANCER3. Good healthAction planMolecular MedicineErratumLife Sciences & BiomedicineMedical GeneticsOpinion: Public health health care sciences & services [D22] [Human health sciences]MedicinaInformation DisseminationMECHANISMS03 medical and health sciencesFUTUREJournal ArticleGeneticsmedia_common.cataloged_instanceHumansKNOWLEDGEEuropean UnionEuropean unionMolecular BiologyMedicinsk genetik0604 GeneticsScience & Technologybusiness.industryInformation DisseminationHealth Plan Implementation1103 Clinical SciencesCAREData scienceData sharing030104 developmental biologyUNDIAGNOSED DISEASES NETWORKbusiness
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Dry selection and wet evaluation for the rational discovery of new anthelmintics

2017

Helminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmin…

0301 basic medicineBiophysicsNon-stochastic and stochastic atom-based bilinear indicesBilinear interpolationLDA-based QSAR modelQuBiLs-MAS module01 natural sciencesSet (abstract data type)03 medical and health sciencesMolecular descriptorStatisticsPhysical and Theoretical ChemistryMolecular BiologySelection (genetic algorithm)MathematicsFree and open source softwareTraining setTOMOCOMD-CARDD softwareExternal validationAnthelmintic activityAtom (order theory)Computational creeningCondensed Matter PhysicsLinear discriminant analysis0104 chemical sciencesIndazole010404 medicinal & biomolecular chemistry030104 developmental biologyLead generationMolecular Physics
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Direct and Inverse Comorbidities Between Complex Disorders

2016

Comorbidity and multimorbidity, defined as the presence of more than one disease in individuals, have emerged as a major challenge in the last decade (Valderas et al., 2009). Indeed, researchers, health professionals, healthcare managers and policy makers, and patients and citizens are lagging behind considering the comorbidity scenario, as illustrated by the paucity of documentation concerning interventions in people with multiple conditions (Smith et al., 2012). There is a clear need to better understand disease-disease relationships, in order to better organize and provide care, but also to develop appropriate research models. We can first characterize direct multimorbidity (higher-than-…

0301 basic medicineBiopsychosocial modelNosologymedicine.medical_specialtymedicinemultimorbidityPhysiologymalaltiesContext (language use)Disease03 medical and health sciencesPhysiology (medical)MultimorbidityMedicinecomplex diseasesPsychiatryOMICS dataComputingMilieux_MISCELLANEOUSbusiness.industrymedicine.diseaseComorbidity[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]3. Good healthcomorbidityEditorial030104 developmental biologyAge of onsetbusinessNeurocognitive
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Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC-MS Metabolomics

2020

One of the most widely used strategies for metabolite annotation in untargeted LCMS is based on the analysis of MSn spectra acquired using data-dependent acquisition (DDA), where precursor ions are sequentially selected from MS scans based on user-selected criteria. However, the number of MSn spectra that can be acquired during a chromatogram is limited and a trade-off between analytical speed, sensitivity and coverage must be ensured. In this research, we compare four different strategies for automated MS2 DDA, which can be easily implemented in the frame of standard QA/QC workflows for untargeted LC&ndash

0301 basic medicineBioquímicaBiologiaComputer scienceEndocrinology Diabetes and Metabolismlcsh:QR1-50201 natural sciencesBiochemistryliquid chromatography–mass spectrometryArticlelcsh:Microbiology03 medical and health sciencesAnnotationMetabolomicsLiquid chromatography–mass spectrometrypeak annotationMolecular BiologyData dependentliquid chromatography-mass spectrometrydata dependent acquisitionbusiness.industry010401 analytical chemistryhuman milkPattern recognition0104 chemical sciencesWorking range030104 developmental biologyFeature (computer vision)Reference databaseArtificial intelligencebusinessMETABOLIC FEATURES
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Familial hypercholesterolemia: The Italian Atherosclerosis Society Network (LIPIGEN)

2017

Background and aims: Primary dyslipidemias are a heterogeneous group of disorders characterized by abnormal levels of circulating lipoproteins. Among them, familial hypercholesterolemia is the most common lipid disorder that predisposes for premature cardiovascular disease. We set up an Italian nationwide network aimed at facilitating the clinical and genetic diagnosis of genetic dyslipidemias named LIPIGEN (LIpid TransPort Disorders Italian GEnetic Network). Methods: Observational, multicenter, retrospective and prospective study involving about 40 Italian clinical centers. Genetic testing of the appropriate candidate genes at one of six molecular diagnostic laboratories serving as nationw…

0301 basic medicineCandidate geneGenetic testingSettore MED/09 - Medicina InternaDatabases FactualDNA Mutational AnalysisDiseaseFamilial hypercholesterolemia030204 cardiovascular system & hematology0302 clinical medicineDyslipidemias; Genetic testing; National network; Internal Medicine; Cardiology and Cardiovascular MedicineRisk FactorsProspective StudiesProgram DevelopmentProspective cohort studymedicine.diagnostic_testGeneral MedicinePrognosisCholesterolPhenotypeItalyCardiology and Cardiovascular MedicineGenetic Markersmedicine.medical_specialtyNational networkDyslipidemias; Genetic testing; National networkMEDLINEHyperlipoproteinemia Type II03 medical and health sciencesDatabasesInternal medicinemedicineInternal MedicineHumansGenetic Predisposition to DiseaseFactualGenetic testingRetrospective StudiesDyslipidemiasbusiness.industrySettore MED/13 - ENDOCRINOLOGIARetrospective cohort studymedicine.diseaseAtherosclerosisDyslipidemias; Genetic testing; National network; Atherosclerosis; Cholesterol; DNA Mutational Analysis; Databases Factual; Genetic Markers; Genetic Predisposition to Disease; Humans; Hyperlipoproteinemia Type II; Italy; Phenotype; Prognosis; Program Development; Prospective Studies; Retrospective Studies; Risk Factors; Mutation; Internal Medicine; Cardiology and Cardiovascular Medicine030104 developmental biologyEndocrinologyDyslipidemiaGenetic markerMutationbusiness
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OFIP/KIAA0753 forms a complex with OFD1 and FOR20 at pericentriolar satellites and centrosomes and is mutated in one individual with oral-facial-digi…

2016

Item does not contain fulltext Oral-facial-digital (OFD) syndromes are rare heterogeneous disorders characterized by the association of abnormalities of the face, the oral cavity and the extremities, some due to mutations in proteins of the transition zone of the primary cilia or the closely associated distal end of centrioles. These two structures are essential for the formation of functional cilia, and for signaling events during development. We report here causal compound heterozygous mutations of KIAA0753/OFIP in a patient with an OFD VI syndrome. We show that the KIAA0753/OFIP protein, whose sequence is conserved in ciliated species, associates with centrosome/centriole and pericentrio…

0301 basic medicineCentriolecell-cycle progressionGene Expressionmedicine.disease_causeCiliopathieshuman-disease genemolecular characterizationbbs proteinsGenetics (clinical)Conserved SequenceCentriolesGeneticsMutationCiliumCiliary transition zoneMetabolic Disorders Radboud Institute for Molecular Life Sciences [Radboudumc 6]General MedicineOrofaciodigital Syndromes3. Good healthcentriolar satellitesmultiple sequence alignmentbasal body dockingFemaleMicrotubule-Associated ProteinsProtein BindingHeterozygoteMolecular Sequence DataBiology03 medical and health sciencesIntraflagellar transportCiliogenesis[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyGeneticsmedicineHumansAmino Acid SequenceCiliaMolecular BiologyCentrosomeintraflagellar transportBase SequenceInfant NewbornProteins030104 developmental biologyCentrosomeMutationciliary transition zoneSequence Alignment[SDV.MHEP]Life Sciences [q-bio]/Human health and pathologyciliogenesis
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The Importance of Cerebellar Connectivity on Simulated Brain Dynamics

2020

The brain shows a complex multiscale organization that prevents a direct understanding of how structure, function and dynamics are correlated. To date, advances in neural modeling offer a unique opportunity for simulating global brain dynamics by embedding empirical data on different scales in a mathematical framework. The Virtual Brain (TVB) is an advanced data-driven model allowing to simulate brain dynamics starting from individual subjects' structural and functional connectivity obtained, for example, from magnetic resonance imaging (MRI). The use of TVB has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting…

0301 basic medicineCerebellumEmpirical dataComputer scienceThe Virtual Brainlcsh:RC321-57103 medical and health sciencesFunctional brainCellular and Molecular Neuroscience0302 clinical medicinemultiscale approachbrain dynamicsmedicineFunctional connectomestructural connectivitylcsh:Neurosciences. Biological psychiatry. NeuropsychiatryComputingMilieux_MISCELLANEOUSOriginal ResearchSignal processingFunctional connectivity[SCCO.NEUR]Cognitive science/Neurosciencefunctional connectivity030104 developmental biologyBrain statemedicine.anatomical_structureDynamics (music)Neuroscience030217 neurology & neurosurgeryNeurosciencecerebro-cerebellar loopFrontiers in Cellular Neuroscience
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Reanalysis of Chinese Treponema pallidum samples: all Chinese samples cluster with SS14-like group of syphilis-causing treponemes

2018

[Objective]: Treponema pallidum subsp. pallidum (TPA) is the causative agent of syphilis. Genetic analyses of TPA reference strains and human clinical isolates have revealed two genetically distinct groups of syphilis-causing treponemes, called Nichols-like and SS14-like groups. So far, no genetic intermediates, i.e. strains containing a mixed pattern of Nichols-like and SS14-like genomic sequences, have been identifed. Recently, Sun et al. (Oncotarget 2016. https://doi. org/10.18632/oncotarget.10154) described a new “phylogenetic group” (called Lineage 2) among Chinese TPA strains. This lineage exhibited a “mosaic genomic structure” of Nichols-like and SS14-like lineages.

0301 basic medicineChinaLineage (genetic)Sequencing datalcsh:MedicineGenome sequencingPolymorphism Single NucleotideGeneral Biochemistry Genetics and Molecular BiologyDNA sequencing03 medical and health sciencesmedicineHumansTreponema pallidumSyphilislcsh:Science (General)lcsh:QH301-705.5GenePhylogenyGeneticsTreponemaPhylogenetic analysisbiologyPhylogenetic treeintegumentary systemlcsh:RGeneral MedicineSequence Analysis DNAbiology.organism_classificationmedicine.disease3. Good healthSingle nucleotide variantResearch Note030104 developmental biologylcsh:Biology (General)SyphilisMixed patternGenome Bacteriallcsh:Q1-390BMC Research Notes
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Quantum clustering in non-spherical data distributions: Finding a suitable number of clusters

2017

Quantum Clustering (QC) provides an alternative approach to clustering algorithms, several of which are based on geometric relationships between data points. Instead, QC makes use of quantum mechanics concepts to find structures (clusters) in data sets by finding the minima of a quantum potential. The starting point of QC is a Parzen estimator with a fixed length scale, which significantly affects the final cluster allocation. This dependence on an adjustable parameter is common to other methods. We propose a framework to find suitable values of the length parameter σ by optimising twin measures of cluster separation and consistency for a given cluster number. This is an extension of the Se…

0301 basic medicineClustering high-dimensional dataMathematical optimizationCognitive NeuroscienceSingle-linkage clusteringCorrelation clustering02 engineering and technologyComputer Science ApplicationsHierarchical clusteringDetermining the number of clusters in a data set03 medical and health sciences030104 developmental biologyArtificial Intelligence0202 electrical engineering electronic engineering information engineeringCluster (physics)020201 artificial intelligence & image processingQACluster analysisAlgorithmk-medians clusteringMathematicsNeurocomputing
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High fat diets for weight loss among subjects with elevated fasting glucose levels: The PREDIMED study

2020

Abstract Aim We studied fasting plasma glucose (FPG) as a determinant of weight change on high-fat diets in the PREDIMED trial. Methods A total of 3,622 participants were randomized to receive one of two Mediterranean diets (n = 2,616) or a control diet (n = 1,006) for 5 years and had complete data for baseline FPG and body-weight development. Weight change by pre-treatment FPG categories ( Results The two Mediterranean diets contained 41.5 E% fat, 16.5 E% protein, and 40 E% carbohydrate whereas the control diet contained 37.8 E% fat, 16.8 E% protein and 43.2 E% carbohydrate. In the Mediterranean diet groups, participants with FPG≥115 lost 1.04 kg (95% CI 0.68; 1.41, n = 1115) whereas parti…

0301 basic medicineComplete data030109 nutrition & dieteticsendocrine system diseasesMediterranean dietbusiness.industryEndocrinology Diabetes and MetabolismWeight changePublic Health Environmental and Occupational Healthnutritional and metabolic diseases030209 endocrinology & metabolismHigh fat dietCarbohydratePredimedFasting glucose03 medical and health sciences0302 clinical medicineAnimal scienceWeight lossInternal Medicinemedicinemedicine.symptombusinessObesity Medicine
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