Matthew Wheeler

The paper analyzes attractor coherence in Boolean gene regulatory networks, revealing that attractors representing mature cell types are less stable than their basins due to canalization.

This study investigates how auxiliary information improves RNA secondary structure prediction accuracy by analyzing suboptimal structures and using topological data analysis features.

This study shows hemopexin reduces fungal lung injury by limiting heme-mediated NETosis in aspergillosis.

The paper explores the relationship between structural and functional modularity in gene regulatory networks using Boolean models and simulations, showing that structural decomposition correlates with dynamic behavior.

This study develops a multiscale computational model of invasive aspergillosis to identify key factors determining infection outcome, finding that fungal growth, iron acquisition, and leukocyte activation are critical.