Author

Stephen Sim

Icahn School of Medicine at Mount SinaiORCID 0000-0001-6322-2864Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Li SheniD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintJul 24, 2026

Deconvolution-derived cell-type expression targets for personal genome sequence-to-expression prediction

Stephen Sim, Li Shen

The paper uses deconvolution of bulk RNA-seq to generate cell-type-specific targets for predicting gene expression from personal genome sequences, finding that sequence-derived models outperform genotype-feature baselines.

DOI 10.64898/2026.07.20.739672

humanbulk RNA-seq

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