Denis Đermadi

The paper develops a framework to impute histone modification abundances and infer directional associations between them using neural processes, identifying novel interactions and changes post-vaccination.

The paper develops a 6-mRNA classifier using non-COVID-19 viral infection data to predict COVID-19 severity, achieving high accuracy in independent cohorts.

The paper uses single-cell exome sequencing to study how replication errors, H3K36me3, and MMR shape the mutational landscape in mouse thymocytes.

This paper uses single-cell transcriptomics to map the transcriptional organization of lymphatic endothelial cells in mouse and human lymph nodes, identifying distinct subsets and their functional roles.

The paper introduces tSpace, a computational method for analyzing developmental pathways in single-cell data, and shows it reconstructs known developmental sequences and reveals new insights into B cell development and intestinal epithelial differentiation.