Biosensor Arrays for Estimating Molecular Concentration in Fluid Flows

TL;DR

This paper develops dynamical models and estimation algorithms for determining molecular concentrations in fluid flows using innovative biosensor arrays, combining PDEs, chemical reactions, and statistical analysis.

Contribution

It introduces a new modeling and estimation framework for biosensor arrays that accounts for advection-diffusion and surface reactions, with proven consistency and normality.

Findings

Estimator is strongly consistent

Asymptotic normality of the estimator

Explicit asymptotic variance expression

Abstract

This paper constructs dynamical models and estimation algorithms for the concentration of target molecules in a fluid flow using an array of novel biosensors. Each biosensor is constructed out of protein molecules embedded in a synthetic cell membrane. The concentration evolves according to an advection-diffusion partial differential equation which is coupled with chemical reaction equations on the biosensor surface. By using averaging theory methods and the divergence theorem, an approximate model is constructed that describes the asymptotic behaviour of the concentration as a system of ordinary differential equations. The estimate of target molecules is then obtained by solving a nonlinear least squares problem. It is shown that the estimator is strongly consistent and asymptotically normal. An explicit expression is obtained for the asymptotic variance of the estimation error. As an example, the results are illustrated for a novel biosensor built out of protein molecules.