Rohit K. Tripathy

The paper introduces a graph neural network framework that integrates multi-omics data with biological priors to identify biomarkers in Alzheimer's disease.

The paper benchmarks neuronal cell-type annotation in scATAC-seq data using marker genes and introduces a deep learning model to predict chromatin accessibility from DNA sequence.

This study investigates how architectural choices in convolution-based hybrid networks affect motif representations and the interpretability of their attention maps in genomics.