Duc Tran

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.

The paper analyzes age-related changes in clonal haematopoiesis (CH) using whole exome data from 420,000 UK Biobank participants, finding a deceleration of clonal expansion with age.

This paper develops Ribo-ITP to measure ribosome occupancy in single cells during early mouse development, revealing differential translation efficiency and allele-specific ribosome engagement.

The paper identifies genomic associations with ex vivo DNA damage responses to ionizing radiation in mice, highlighting pathway differences across radiation types and timing.

The paper organizes a DREAM challenge to benchmark predictive models of single-cell signaling using mass cytometry data from breast cancer cell lines.

This paper introduces a hierarchical autoencoder for scRNA-seq analysis, showing improved performance in cell segregation, visualization, classification, and pseudo-time inference compared to existing methods.

The paper predicts cellular positions in the Drosophila embryo using scRNA-seq data by benchmarking methods against spatially annotated genes.