Divyansh Agarwal

This study evaluates dispersion metrics for estimating transcriptional variability in single-cell RNA sequencing data and finds the variance-to-mean ratio is scale-invariant and responsive to noise.

This study compares pathogenesis of ancestral and contemporary Zika viruses in human cerebral organoids, finding differential signaling responses and identifying ROS imbalance as a key driver, which is mitigated by Trolox.

This paper improves scRNA-seq data quality using transfer learning by combining a deep autoencoder with a Bayesian model to extract gene-gene relationships across diverse datasets.