grant

Data Management and Analysis Core

Organization EMORY UNIVERSITYLocation ATLANTA, UNITED STATESPosted 15 May 2022Deadline 28 Feb 2027
NIHUS FederalResearch GrantFY2025Active Follow-upAddressAreaAsiaBayesian ModelingBayesian adaptive designsBayesian adaptive modelsBayesian belief networkBayesian belief updating modelBayesian frameworkBayesian hierarchical modelBayesian network modelBayesian nonparametric modelsBayesian spatial data modelBayesian spatial image modelsBayesian spatial modelsBayesian statistical modelsBayesian tracking algorithmsBioinformaticsBiological MarkersBiometricsBiometryBiostatisticsBloodBlood Reticuloendothelial SystemCVD preventionCardiovascular DiseasesCaringChronic DiseaseChronic IllnessClinicalCollaborationsCollectionCommunicationComplexComputational BiologyDataData AnalysesData AnalysisData AnalyticsData BasesData Management and Analysis CoreData Management and Statistical Analysis CoreData Management and Statistical CoreData ScienceData SetDatabasesDedicationsDetectionDevelopmentDocumentationEcological momentary assessmentEngineeringEnsureEnvironmentEnvironmental ExposureEpigeneticEpigenetic ChangeEpigenetic MechanismEpigenetic ProcessEquationEvaluationFundingGoalsHealthHuman ResourcesIndiaInfrastructureInstitutionInternationalInvestigatorsLeadLongitudinal SurveysMachine LearningManpowerMeasurementMethodologyMethodsModelingMonitorNHLBINational Heart, Lung, and Blood InstituteP01 MechanismP01 ProgramPathway interactionsPb elementPersonsPhenotypePlayPostdocPostdoctoral FellowProceduresProgram Project GrantProgram Research Project GrantsProtocolProtocols documentationPublic HealthR-Series Research ProjectsR01 MechanismR01 ProgramReproducibilityReproducibility of FindingsReproducibility of ResultsResearchResearch AssociateResearch DesignResearch GrantsResearch MethodologyResearch MethodsResearch PersonnelResearch Program ProjectsResearch Project GrantsResearch ProjectsResearch ResourcesResearchersResourcesRisk ReductionRoleSamplingSecureSourceSouth AsianStudy TypeTechniquesTechnologyTraining ProgramsUniversitiesUrineWorkactive followupanalytical methodanalytical toolanalyzing longitudinalbio-markersbiobankbiologic markerbiomarkerbiorepositorycardiac disease preventioncardiometabolic riskcardiovascular disease epidemiologycardiovascular disease preventioncardiovascular disease riskcardiovascular disordercardiovascular disorder epidemiologycardiovascular disorder preventioncardiovascular disorder riskcardiovascular epidemiologychronic disordercohortcomplex datacomputer based predictioncomputer biologydata analysis coredata analysis research coredata analytics coredata analytics research coredata basedata captured from wearablesdata cleaningdata cleansingdata collected from wearablesdata collected using wearablesdata complexitydata diversitydata driven platformdata gathered from wearabledata gathered through wearablesdata gathered via wearabledata heterogeneitydata interpretationdata managementdata platformdata set heterogeneitydata sharingdata streamsdata visualizationdata-driven modeldataset heterogeneitydevelopmentaldigitaldisease controldisease diagnosticdisease phenotypedisease preventiondisorder controldisorder preventiondiverse dataepidemiological modelepigeneticallyepigenomicsexperienceexposomefollow upfollow-upfollowed upfollowupgraduate studentheavy metal Pbheavy metal leadheterogeneous dataheterogeneous data setsheterogeneous datasetsheterogenous dataheterogenous data setsheterogenous datasetshigh dimensional datahigh dimensionalityindexinginnovateinnovationinnovativelearning activitylearning methodlearning strategieslearning strategylongitudinal analysismachine based learningmachine learning based methodmachine learning based prediction modelmachine learning based predictive modelmachine learning methodmachine learning methodologiesmachine learning predictionmachine learning prediction modelmachine statistical learningmetabolism measurementmetabolomicsmetabonomicsmodel developmentmodel developmentsmultidimensional datamultidimensional datasetsmultiomicsmultiple omicspanomicspathwaypersonnelpost-docpost-doctoralpost-doctoral traineepredictive modelingreduce riskreduce risksreduce that riskreduce the riskreduce these risksreduces riskreduces the riskreducing riskreducing the riskresearch and methodsresearch associatesrisk-reducingsensorservice programssocial rolespatial and temporalspatial temporalspatiotemporalstatistical and machine learningstructured datastudy designsynergismwearable datawearable device datawearable sensor data
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Full Description

PROJECT SUMMARY / ABSTRACT (Data Management and Analysis Core)
The Data Management and Analysis (DMA) Core will provide comprehensive data science support for the

Program Project Grant (PPG): Precision Cardiovascular Disease Phenotyping and Pathophysiological

Pathways in the CARRS cohort (Precision-CARRS). The overarching goal of the DMA Core is to maintain

high scientific rigor in the management and analysis of large and complex datasets. The DMA Core will be

based at Emory University and the Center for Chronic Disease Control (CCDC) in India. The DMA Core will

include 8 investigators with comprehensive data science expertise and a dedicated team of database engineer,

data managers and biostatisticians from both the US and India. The DMA Core will oversee data

management, data sharing, and the development of common analytic frameworks to promote integration and

synergy across the interconnected aims of the Precision-CARRS Projects. The DMA Core will work closely

with the Administrative and Field Coordination (AFC) Core and the CVD Phenotyping Core to ensure high

quality data capture and documentation, as well as to provide continuous infrastructure and management for

all research data from Precision-CARRS (Aim 1). By leveraging and expanding existing data platforms, we will

establish workflows and protocols for consistent data cleaning, harmonization, monitoring and documentation

for diverse datasets, including longitudinal surveys, subclinical and clinical phtenotypes, blood and urine

biomarker measurements, environmental exposures, and data from high-throughput omics technologies and

digital sensors. The DMA Core will also work closely with all Reseach Projects to provide centralized support

for data analysis using state-of-the-art biostatistics, bioinformatics and maching learning methods (Aim 2).

Specifically, the DMA Core will create synchronized analytic plans for both epidemiologic modeling and

predictive equation development across projects. To provide integrated and timely data science support

throughout the PPG, two DMA Core investigators (one from Emory and one from CCDC) will serve as liaisons

for each Core and Project. Finally, the DMA core will support the development of new and innovative analytic

methods motivated by the scientific goals of Precision-CARRS (Aim 3). The DMA Core is particularly poised to

contribute in the areas of machine learning for predictive health, latent variable models for handling multivariate

and structured data, high-dimensional methods for multi-omics, and integrative analysis of heterogeneous data

types. In summary, the DMA Core will be an integral component for Precision-CARRS by offering essential

data management and analysis support for PPG research aims, while enhancing the reliability, relevance and

reproducility of the PPG’s findings to utlimately sustain the long-term impact and collaborative potential of

Precision-CARRS.

Grant Number: 5P01HL154996-04
NIH Institute/Center: NIH

Principal Investigator: Howard Chang

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