A system for analyzing proximity binding assay data, comprising: a thermal cycler instrument configured to perform a proximity binding assay on at least one test sample, at least one reference sample for which a target protein is of a known quantity, at least one non-protein control sample as a background sample, and at least one set of calibration samples generated from at least a pair of calibration samples for which a relative protein quantity is known and to generate at least one set of test sample data, at least one set of reference sample data, at least one background sample data set, and at least one set of calibration sample data; and a processor, in communication with the thermal cycler instrument, configured to: receive from the thermal cycler instrument the at least one set of test sample data, the at least one set of reference sample data, the at least one background sample data set, and the at least one set of calibration sample data; determine cycle threshold (Ct) values for the at least one set of test sample data and the at least one set of reference sample data; calculate background corrected Ct values for each value in the test sample data set and the reference sample data set using a corresponding value in the background sample data set; determine a linear range for the background corrected Ct values as a function of sample quantity; calculate a linear regression line for each linear range that is determined; estimate one or more parameter values of an exponential model formula describing a fold change from the one or more sets of calibration sample data; and calculate a target protein quantity and an associated confidence interval using the linear regression lines calculated for the test sample data and the reference sample data and the exponential model formula describing the fold change with the one or more parameter values estimated from the one or more sets of calibration sample data. a thermal cycler instrument configured to perform a proximity binding assay on at least one test sample, at least one reference sample for which a target protein is of a known quantity, at least one non-protein control sample as a background sample, and at least one set of calibration samples generated from at least a pair of calibration samples for which a relative protein quantity is known and to generate at least one set of test sample data, at least one set of reference sample data, at least one background sample data set, and at least one set of calibration sample data; and a processor, in communication with the thermal cycler instrument, configured to: receive from the thermal cycler instrument the at least one set of test sample data, the at least one set of reference sample data, the at least one background sample data set, and the at least one set of calibration sample data; determine cycle threshold (Ct) values for the at least one set of test sample data and the at least one set of reference sample data; calculate background corrected Ct values for each value in the test sample data set and the reference sample data set using a corresponding value in the background sample data set; determine a linear range for the background corrected Ct values as a function of sample quantity; calculate a linear regression line for each linear range that is determined; estimate one or more parameter values of an exponential model formula describing a fold change from the one or more sets of calibration sample data; and calculate a target protein quantity and an associated confidence interval using the linear regression lines calculated for the test sample data and the reference sample data and the exponential model formula describing the fold change with the one or more parameter values estimated from the one or more sets of calibration sample data. receive from the thermal cycler instrument the at least one set of test sample data, the at least one set of reference sample data, the at least one background sample data set, and the at least one set of calibration sample data; determine cycle threshold (Ct) values for the at least one set of test sample data and the at least one set of reference sample data; calculate background corrected Ct values for each value in the test sample data set and the reference sample data set using a corresponding value in the background sample data set; determine a linear range for the background corrected Ct values as a function of sample quantity; calculate a linear regression line for each linear range that is determined; estimate one or more parameter values of an exponential model formula describing a fold change from the one or more sets of calibration sample data; and calculate a target protein quantity and an associated confidence interval using the linear regression lines calculated for the test sample data and the reference sample data and the exponential model formula describing the fold change with the one or more parameter values estimated from the one or more sets of calibration sample data.