Author

Elsa Bismuth

Stanford University

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Genomics· 1

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Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Approach:machine learning (classical)· 1

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Cheng ChangiD· 1 shared Manuel A. RivasiD· 1 shared Oscar AguilariD· 1 shared

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Cheng ChangORCID

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Recent·Most cited

Integrative machine learning approaches for predicting disease risk using multi-omics data from the UK Biobank

Oscar Aguilar, Cheng Chang, Elsa Bismuth, Manuel A. Rivas

The paper trains machine learning models on multi-omics UK Biobank data to predict disease risk, finding metabolomics provides limited improvement over standard features but can replace them when unavailable.

bioRxiv · Apr 16, 2024 · PreprintGenomics