grant
Advanced machine learning models to integrate multi-modal biomedical datasets for gene regulation and precision medicine
Organization UNIVERSITY OF NORTH TEXASLocation DENTON, UNITED STATESPosted 1 Aug 2019Deadline 30 Jun 2030
NIHUS FederalResearch GrantFY2025AddressArchitectureBiologyBiomedical TechnologyComputational toolkitComputing MethodologiesDataData SetDependenceDevelopmentDiseaseDisorderDrugsElectronic Health RecordEngineering / ArchitectureGene Action RegulationGene Expression RegulationGene RegulationGene Regulation ProcessGenesGenomicsGraphIndividualInterpretable MLInterpretable machine learningLearningMachine LearningMedicationMedicineMethodsModelingOrganismPharmaceutical PreparationsResearchSightVisioncomputational methodologycomputational methodscomputational toolboxcomputational toolscomputational toolsetcomputer based methodcomputer based predictioncomputer methodscomputerized toolscomputing methoddata modalitiesdeep learningdeep learning methoddeep learning strategydesigndesigningdevelopmentaldrug/agentelectronic health care recordelectronic health medical recordelectronic health plan recordelectronic health registryelectronic medical health recordepigenomicsexplainable MLexplainable machine learninghigh dimensionalityhigh throughput technologyliving systemmachine based learningmachine learning based modelmachine learning modelmulti-modal datamulti-modal datasetsmulti-modalitymultimodal datamultimodal datasetsmultimodalitymultiomicsmultiple omicsnovelopen sourcepanomicsprecision medicineprecision-based medicinepredict clinical outcomepredictive modelingprogramstranscriptomicsvisual function
Description preview
Vast amounts of multi-modal biomedical datasets have become available due to advances in high-throughput biomedical technologies. Each of these distinct data modalities such as genomics, epigenomics, and transcriptomics (collectively called as “multi-omics”) offers complementary information about the underlying biology of living systems.…
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