Kushal K. Dey

The paper improves deep learning SNP annotations for complex diseases by integrating them with SNP-to-gene linking strategies and gradient boosting, showing increased informativeness for autoimmune diseases.

The paper uses the ABC Model to map enhancer-gene regulation across 131 cell types and tissues, linking GWAS variants to disease genes, particularly in IBD.

The paper develops a method to quantify cell cycle progression in scRNA-seq data using a small number of genes, showing it can predict cell cycle phase within 14% accuracy.

This paper introduces Robocov, a convex optimization framework for estimating gene-level tissue networks with missing data, showing it improves correlation and causal structure estimation and identifies disease-related genes.

This study uses ancient DNA to trace Sardinia's population history from the Neolithic to the present, finding genetic continuity and limited Bronze Age Steppe ancestry.

The paper introduces a new sequence logo plot, EDLogo, that visualizes both enrichment and depletion of characters in biological sequences and provides an R package for its implementation.

This paper introduces a grade of membership model to infer and visualize DNA damage patterns in ancient DNA, distinguishing ancient from modern samples and contamination.

CorShrink is an Empirical Bayes method for estimating correlations with missing data, showing competitive performance on gene expression and word vector similarity tasks.

The paper applies grade of membership models to RNA-seq data to identify and summarize biological structure and heterogeneity in both bulk and single-cell datasets.