H. Steven Wiley

This study quantifies how dose-response relationships in signaling systems affect information transmission under various noise distributions and identifies design principles for improved signaling fidelity.

ProteoMeter integrates multi-PTM and limited proteolysis data to map proteomic changes to residue level, demonstrating its use in analyzing HCoV-229E infection.

The paper investigates how biochemical reaction networks perform signal integration and integral feedback control, finding that these capabilities overlap but are not always mutually exclusive.

The paper generates a deep phosphoproteomics dataset of the EGFR-MAPK pathway in MCF10A cells and integrates it with protein databases to study kinase signaling.

The paper develops a method to generate synthetic signaling networks that mimic real biological networks in topology and dynamics, enabling testing of network inference algorithms.

This paper infers reaction networks from perturbation data using an evolutionary strategy that evolves network topologies and parameters to match experimental data.

The paper introduces BSF, a fast pairwise similarity algorithm that filters unproductive comparisons to enable efficient data mining.