Author

Yazheng Di

ETH ZurichORCID 0000-0003-2483-1696Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:GWAS / association mapping· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1 Assay:electronic health records· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Na CaiiD· 2 shared Patrick StylliD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

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2 top collaborators · 1 mutual co-author link

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2 shared papersGenomics

Na CaiORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintNov 9, 2026

Uncertainty-Aware Personalised Gene Expression Prediction Improves Cell-Type-Specific Association Testing

Patrick Styll, Yazheng Di, Na Cai

ATTICUS improves gene expression prediction and association testing by incorporating uncertainty awareness and personalized training, enhancing accuracy and cell-type specificity in disease studies.

DOI 10.64898/2026.11.06.764604

humanbulk RNA-seq

𝕏 PostBluesky

Genetic & Genomic MedicinemedRxivPreprintFeb 22, 2026

Learning lifetime disease liability reveals and removes genetic confounding in electronic health records

Yazheng Di, Na Cai

This paper introduces EDGAR, a deep learning framework that removes genetic confounding in EHR-based GWAS by learning lifetime disease liability and isolating systemic biases in EHR codes.

DOI 10.64898/2026.02.15.26346336

electronic health recordsdeep learning

𝕏 PostBluesky