grant
Interpretable Bayesian Non-linear statistical learning models for multi-omics data integration
Organization UNIVERSITY OF MINNESOTALocation MINNEAPOLIS, UNITED STATESPosted 20 Sept 2023Deadline 31 Jul 2028
NIHUS FederalResearch GrantFY2025Bayesian MethodBayesian MethodologyBayesian Statistical MethodBayesian approachesBayesian classification methodBayesian classification procedureBayesian posterior distributionBiologicalBiological MarkersBody TissuesCancersCardiovascular DiseasesChargeClinicalComplexDataData SetDegenerative Neurologic DisordersDiagnosisDiseaseDisorderGenomicsGenotypeHeterogeneityJointsMalignant NeoplasmsMalignant TumorMedicineMethodsModelingMolecularMolecular DiseaseMultiomic DataNervous System Degenerative DiseasesNeural Degenerative DiseasesNeural degenerative DisordersNeurodegenerative DiseasesNeurodegenerative DisordersNeurologic Degenerative ConditionsPathway interactionsProductionPrognostic MarkerProteomicsTCGATechnologyThe Cancer Genome AtlasTimeTissuesbio-markersbiologicbiologic markerbiomarkercardiovascular disorderdata integrationdatabase of Genotypes and PhenotypesdbGaPdegenerative diseases of motor and sensory neuronsdegenerative neurological diseasesdisease subgroupsdisease subtypedisorder subtypeepigenomicsimprovedlearning activitylearning methodlearning strategieslearning strategymalignancymultiomicsmultiple omic datamultiple omicsneoplasm/cancerneurodegenerative illnessnovelpanomicspathwaypersonalization of treatmentpersonalized medicinepersonalized therapypersonalized treatmentpredict clinical outcomepredictive biological markerpredictive biomarkerspredictive markerpredictive molecular biomarkerprognostic biomarkerprognostic indicatorstatistical learningtranscriptomicstreatment strategyuser friendly computer softwareuser friendly software
Description preview
Project Summary
Recent technological advances have enabled the production of vast amounts of diverse multi-omics data types (e.g.,
genomics, epigenomics, proteomics, transcriptomics) of complex diseases such as cancer, cardiovascular diseases
and neurodegenerative disorders. The integration of multi-omics data from those heterogeneous diseases can…
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