Eric Yao-Yu Chuang

This study examines how variations in ACE2 and TMPRSS2 genes influence COVID-19 infection and disease progression through multi-omics analysis of SNPs, structural variations, and gene expression patterns.

The paper uses deep convolutional neural networks on pathological images from the TCGA-BRCA dataset to predict breast cancer molecular subtypes with 78% validation accuracy.

RNASeqR provides an automated RNA-Seq analysis workflow in R, enabling six-step processing and visualization for comparative transcriptomic studies.