MS-based techniques can yield quantitative information about the abundance of proteins phosphorylated at specific amino acid residues without reliance on availability of phosphosite-specific antibodies, and measurements can be made with fine time resolution, which is needed to decipher the order of phosphorylation events. Thus, MS-based proteomics has the potential to make unique contributions to systems biology modeling. However, modeling and proteomics have not yet become tightly integrated, in part because of the technical challenges of constructing and parameterizing a model with sufficient detail and scope to be used for analysis of proteomic data. Proteomic measurements give information about phosphorylation levels at specific amino acid residues ; thus, a compatible model requires similar site-specific resolution. For this task, traditional modeling approaches can be difficult or impossible to apply, which has catalyzed development of the specialized techniques of rule-based modeling. Rule-based Folinic acid calcium salt pentahydrate models make it possible to simulate site-specific biomolecular interactions in a manner consistent with physicochemical principles. Rule-based modeling has been used to study several immunoreceptor signaling systems, although in each case, the scope of the model has been restricted to a handful of signaling readouts. Development of models with sufficient scope to connect to proteomic data has faced additional challenges; large models can be costly to simulate and the complexity of the model can hinder communication of the model’s content. To overcome these obstacles, simulation techniques for large models and methods for model annotation and visualization have recently been developed. Although these modeling capabilities have been demonstrated to a limited extent, use of large models to decode high-content data, generate hypotheses, and drive the discovery of biological insights has thus far remained Atractylenolide-III uncharted territory. We have developed a new approach for characterizing signal initiation using a rule-based model to interpret temporal phosphoproteomic data. We have applied this approach to study initiation of T-cell receptor signaling, which is an essential process in the adaptive immune response. The TCR and related antigen recognition receptors transmit signals that are dependent on site-specific details. These receptors are characterized by immunoreceptor tyrosine-based activation motifs, which each contain two tyrosine residues that can be phosphorylated. It has been found that the specific phosphoform of an ITAM can determine whether activating or inhibitory signals are transmitted. Additionally, TCR signal initiation relies on the kinase LCK, which can be phosphorylated at a minimum of three sites: phosphorylation of two of these sites have opposing influences in regulating kinase activity, and phosphorylation of the third site regulates the affinity of the SH2 domain. These examples underscore the need to investigate the site-specific dynamics of immunoreceptor signaling. Our results 1) characterize early TCR signaling with finer time resolution than previous proteomic studies of this system, 2) reveal mechanisms primarily operative on short timescales immediately after stimulation, and 3) demonstrate how mechanistic modeling and high-content measurements can be combined to develop a predictive understanding of cellular information processing.