Arshdeep Sekhon

The paper introduces DeepVHPPI, a deep learning framework for predicting virus-host protein interactions for novel virus sequences, showing significant improvements over existing methods for SARS-CoV-2, H1N1, and Ebola.

This paper introduces KDiffNet, a method for estimating sparse differential Gaussian Graphical Models that integrates extra knowledge, achieving competitive performance and scalability.

AttentiveChrome combines hierarchical Long Short-Term Memory networks with two-level attention to predict human gene expression from chromatin marks across 56 cell types while identifying important marks and genomic positions.

GaKCo improves the speed of gapped k-mer string kernels by using cumulative counting, achieving faster performance on DNA, protein, and text classification tasks.