Timothy L. Downing

This study shows XIST modulates the adhesome network and cell stemness by altering adhesion pathways and gene expression in ovarian cancer cells and across tissues.

The paper investigates how enzymatic activity thresholds control DNA methylation patterns, finding an ultrasensitive switch mechanism influenced by enzyme interactions.

This paper develops a computational pipeline to infer kinetic parameters from single-cell RNA sequencing data and assesses parameter identifiability using the stochastic telegraph model.

The paper uses polymer mechanics and nucleosome positioning to explain genomic contacts, finding that nucleosomes explain 71% of close contacts within 500 kb.

This paper introduces MPATH, a method to temporally order epigenetic modifications using long-read sequencing, revealing sub-cell-cycle dynamics of methylation states and nucleosome occupancy.

This paper introduces a stochastic dynamical systems model to predict gene expression from methylation data using a gene regulatory network, and provides software for implementation.

The paper uses statistical and stochastic modeling to analyze Repli-BS data from human embryonic stem cells, revealing kinetic heterogeneity in post-replication DNA methylation.