Steve S. Ho

This paper uses domain-specific embeddings to uncover hidden genetic knowledge from scientific literature, predicting gene-disease associations and gene-gene interactions before they are published.

This paper introduces OGL, a deep learning method that integrates multi-omics data to predict gene expression and uncover regulatory interactions across cell lines and tissues.

This study provides haplotype-resolved genome characterization of a marmoset ESC line and demonstrates CRISPR/Cas9 targeting and neuronal differentiation capabilities.

The paper investigates the molecular effects of 16p11.2 CNVs on gene expression and DNA methylation using an iPSC-to-iN model and identifies potential contributing genes.

The paper provides a comprehensive whole-genome analysis of K562, identifying genomic structural features and their impact on functional genomics data.

This paper provides a haplotype-resolved genome analysis of the HepG2 cell line, identifying genomic features and allele-specific regulation to support functional genomics studies.

The paper generates deep re-sequencing datasets for the Venter/HuRef genome to develop and benchmark genome analysis tools using Illumina sequencing.

The paper compares low-coverage whole-genome sequencing strategies to array-based methods for detecting copy number variations, finding WGS more efficient and accurate.