Developing a Theoretical Framework for Optofluidic Device Designing for System Identification in Systems Biology: the EGFR Study Case

TL;DR

This paper presents a theoretical framework for designing optofluidic experiments to identify the dynamics of the EGFR pathway in systems biology, leveraging system theory to optimize input stimuli for better data collection.

Contribution

It introduces a novel theoretical approach for input stimulus design in optofluidic systems based on spectral properties to enhance system identification in biology.

Findings

Designed an optofluidic system based on spectral analysis.

Proposed a framework for input stimulus optimization.

Enhanced data informativeness for EGFR pathway modeling.

Abstract

Identification of dynamics underlying biochemical pathways of interest in oncology is a primary goal in current systems biology. Understanding structures and interactions that govern the evolution of such systems is believed to be a cornerstone in this research. Systems theory and systems identification theory are primary resources for this task since they both provide a self consistent framework for modelling and manipulating models of dynamical systems that are best suited for the problem under investigation. We address herein the issue of obtaining an informative dataset ZN to be used as starting point for identification of EGFR pathway dynamics. In order to match experimental identifiability criteria we propose a theoretical framework for input stimulus design based on dynamical properties of the system under investigation. A feasible optofluidic design has been designed on the basis of the spectral properties of the driving inputs that maximize information content after the theoretical studies.