Daniel Marri

The paper develops a multiscale model of the mammalian liver circadian clock to show that intercellular communication is necessary for sustained circadian oscillations with a near 24-hour period.

This paper introduces scVIDR, a variational autoencoder for predicting dose-dependent gene expression in single cells across different cell types and tissues, showing improved performance over existing methods.

The paper develops tissue-specific models to predict CLOCK-BMAL1 binding to E-box motifs using DNA sequence, shape, and histone modification features in mouse liver, heart, and kidney.

The paper develops predictive models to identify tissue-specific AhR binding determinants using machine learning on genomic features.