Limits of performance of real-time DNA microarrays

DNA microarrays rely on chemical attraction between the nucleic acid sequences of interest (mRNA and DNA sequences, referred to as targets) and their molecular complements which serve as biological sensing elements (probes). The attraction between the complementary sequences leads to binding, in which probes capture target molecules. Molecular binding is a stochastic process and hence the number of captured analytes at any time is a random variable. Today, majority of DNA microarrays acquire only a single measurement of the binding process, essentially taking one sample from the steady-state distribution of the binding process. Real-time DNA microarrays provide much more: they can take multiple temporal measurements which not only allow more precise characterization of the steady-state but also enable faster detection based on the early kinetics of the binding process. In this paper, we derive the Cramer-Rao lower bound on the mean-square error of estimating the target amounts in real-time DNA microarrays, and compare it to that of conventional microarrays. The results suggest that a few temporal samples collected in the early phase of the binding process are often sufficient to enable significant performance improvement of the real-time microarrays over the conventional ones.