Jason E. Shoemaker

This paper develops a rule-based kinetic model of EEEV replication in mammalian cells, calibrated with experimental data, revealing ribosome density on viral RNA as critical for rapid replication and identifying transcription as a therapeutic target.

The paper develops a spatial multicellular model of RNA virus replication and interferon responses, showing how interferon concentrations and diffusion rates affect plaque growth dynamics.

The paper describes the development of a computational knowledge repository, the COVID-19 Disease Map, which curates SARS-CoV-2 virus-host interaction mechanisms and provides tools for their analysis and application.

DeltaNeTS+ infers direct gene targets of drugs and diseases from gene expression data, showing effectiveness in complex organisms and time-course profiles.

Open-source agent-based PhysiCell model of SARS-CoV-2 infection in lung epithelium; version 5 clears virus in about 6 days in simulation, and delayed T cell arrival increases epithelial loss.

The paper evaluates how network and gene expression data affect ProTINA's accuracy, finding that network data dominates and introduces TREAP, a new algorithm with higher accuracy.

This paper identifies 24 potential antiviral drug targets by analyzing the controllability of host and influenza virus-host protein interaction networks.

The paper identifies host factors critical for influenza virus replication by analyzing network positions of virus-host interactions and validates them through an siRNA screen.

This paper reviews mathematical models of influenza-induced host responses, finding that current models fail to capture complex interactions and suggest improvements in modeling virus-resistant cells.

ProTINA infers protein targets of drugs and influenza A virus by analyzing gene expression changes, revealing accurate targets and infection mechanisms.