Modification of proteins by reactive electrophiles such as the 4-hydroxy-2-nonenal (HNE) plays a critical role in oxidant-associated human diseases. However, little is known about protein adduction and the mechanism by which protein damage elicits adaptive effects and toxicity. We developed a systems approach for relating protein adduction to gene expression changes through the integration of protein adduction, gene expression, protein-DNA interaction, and protein-protein interaction data. Using a random walk strategy, we expanded a list of responsive transcription factors inferred from gene expression studies to upstream signaling networks, which in turn allowed overlaying protein adduction data on the network for the prediction of stress sensors and their associated regulatory mechanisms. We demonstrated the general applicability of transcription factor-based signaling network inference using 103 known pathways. Applying our workflow on gene expression and protein adduction data from HNE-treatment not only rediscovered known mechanisms of electrophile stress but also generated novel hypotheses regarding protein damage sensors. Although developed for analyzing protein adduction data, the framework can be easily adapted for phosphoproteomics and other types of protein modification data.