2021
Calibrating predictive model estimates in a distributed network of patient data
Huang Y, Jiang X, Gabriel R, Ohno-Machado L. Calibrating predictive model estimates in a distributed network of patient data. Journal Of Biomedical Informatics 2021, 117: 103758. PMID: 33811986, DOI: 10.1016/j.jbi.2021.103758.Peer-Reviewed Original ResearchConceptsData privacyRecalibration modelHigh-performance predictive modelsIntegration of dataPatient dataPredictive model estimatesDistributed networkExpected calibration errorMaximum calibration errorPrivacyClinical informaticsCalibration errorsComputational efficiencyPredictive analysisAlgorithmBuilding modelsModel buildingImportant issuePerformance measuresPredictive modelMultiple health systemsLarge numberIsotonic regressionInformaticsSystem
2014
Extending the NIF DISCO framework to automate complex workflow: coordinating the harvest and integration of data from diverse neuroscience information resources
Marenco LN, Wang R, Bandrowski AE, Grethe JS, Shepherd GM, Miller PL. Extending the NIF DISCO framework to automate complex workflow: coordinating the harvest and integration of data from diverse neuroscience information resources. Frontiers In Neuroinformatics 2014, 8: 58. PMID: 25018728, PMCID: PMC4071641, DOI: 10.3389/fninf.2014.00058.Peer-Reviewed Original ResearchNeuroscience Information FrameworkData integration capabilitiesComplex workflowsInformation resourcesNeuroscience dataIntegration of dataData aggregatorInformation frameworkSearchable databaseCurrent capabilitiesIntegration capabilityWorkflowWealth of dataResourcesFrameworkInternetCapabilityIntegrationAggregatorDISCOIntegratingFunctionalityFuture directionsDataDatabase
2008
Bringing Web 2.0 to bioinformatics
Zhang Z, Cheung KH, Townsend JP. Bringing Web 2.0 to bioinformatics. Briefings In Bioinformatics 2008, 10: 1-10. PMID: 18842678, PMCID: PMC2638627, DOI: 10.1093/bib/bbn041.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsData exchangeWeb 2.0Data integrationHeterogeneous data sourcesHarness collective intelligenceSharing of dataWeb 2.0 technologiesIntegration of dataMajor bioinformatics challengeWeb servicesData warehousingData creationData sharingCollaborative platformCollective intelligenceAutomatic analysisCommunication modelInformation technologyBioinformatics researchUsersData sourcesSharingMultiple sourcesBioinformatics challengesPlatform
2007
Using contextual and lexical features to restructure and validate the classification of biomedical concepts
Fan J, Xu H, Friedman C. Using contextual and lexical features to restructure and validate the classification of biomedical concepts. BMC Bioinformatics 2007, 8: 264. PMID: 17650333, PMCID: PMC2014782, DOI: 10.1186/1471-2105-8-264.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemString-based approachesMean reciprocal rankReciprocal rankNatural language processingError rateContextual featuresLexical featuresIntegration of dataLow error rateReasoning systemAutomatic approachComplementary classifiersLanguage processingClassification approachBiomedical terminologiesClassification errorOntological conceptsBiomedical conceptsOntological termsSyntactic approachLanguage systemClassifierSyntactic featuresOntology
2006
MitoP2: the mitochondrial proteome database—now including mouse data
Prokisch H, Andreoli C, Ahting U, Heiss K, Ruepp A, Scharfe C, Meitinger T. MitoP2: the mitochondrial proteome database—now including mouse data. Nucleic Acids Research 2006, 34: d705-d711. PMID: 16381964, PMCID: PMC1347489, DOI: 10.1093/nar/gkj127.Peer-Reviewed Original ResearchConceptsMitochondrial proteinsSystematic genome-wide studiesMitochondrial proteome databaseNovel mitochondrial proteinGenome-wide studiesSystems biology approachOrthologous proteinsMolecular functionsBiology approachProteome databaseRare mitochondrial diseaseMitochondrial diseasePhenotype screeningMitochondrial dysfunctionReference proteinProteinMitochondriaMouse dataMitoP2ProteomicsIntegration of dataYeastGenesSpeciesPathway
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