Gordon Broderick

This paper uses knowledge-driven regulatory network modeling to explain ASFV pathogenesis from sparse data, identifying key regulatory proteins and pathways involved in disease progression.

This study identifies a combination treatment with etanercept and mifepristone that reduces neuroinflammation in a mouse model of Gulf War Illness through computational modeling and in vivo testing.

The paper infers regulatory relationships in protein-protein interaction networks from proteomic data to identify oxidative stress pathways linked to infectious vulnerability in COPD.

The paper identifies differentially expressed proteins in COPD patients' bronchoalveolar lavage fluid and uses network analysis to find potential drug targets and repurposable therapies.

The paper constructs a regulatory network model of 44 immune and neurotransmission mediators to show that inflammation is linked to chronic pain, depression, and opioid addiction through increased NF-kB and inflammatory signaling proteins.

The paper introduces attractor landscapes as a model selection criterion for data-poor environments, reducing 18 immune response models to 7 with statistical significance.