Before revision: Cooperative binding processes in living cells represent a primary and highly general mechanism for achieving the collective behaviour that emerges at the systems-level properties of macromolecules, pathways, cells URLanisms. Recent progress in robotics and automated techniques for sampling and analyzing complex biological data can reduce statistical uncertainties (or errors) in measuring cooperativity. An identification of the systematic uncertainties that arise from inaccuracy in the measurement processes, however, has been often non-empirical. Here we propose a comprehensive method to quantitatively evaluate the systematic variances computed not only from a computer simulation of live-cell imaging systems, but also image processing and pattern recognition algorithms for biological images .
After revision: We propose a computational method to quantitatively evaluate the systematic variances computed not only from a computer simulation of live-cell imaging systems, but also image processing and pattern recognition algorithms for biological images .