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Systematically manipulating T-cell signaling dynamics via multiple model informed open-loop controller design | IEEE Conference Publication | IEEE Xplore

Systematically manipulating T-cell signaling dynamics via multiple model informed open-loop controller design


Abstract:

A multiple-model approach to open-loop control of T-cell signaling pathways is presented. Mathematical models of the T-cell signaling pathway are used to inform the contr...Show More

Abstract:

A multiple-model approach to open-loop control of T-cell signaling pathways is presented. Mathematical models of the T-cell signaling pathway are used to inform the controller design. The proposed framework employs a model predictive control strategy to reduce the computational complexity of the open loop control problem. Predictions from each model are weighted using adaptive Akaike weights that are iteratively computed for each controller update step based upon the most relevant training data subsets. This process accounts for the fact that models differ in their ability to accurately reflect the system dynamics under different experimental conditions. The algorithm is evaluated in silico and simulations demonstrate how the model weighting strategy more effectively manages the inaccuracies of any single model. Furthermore, the multiple-model control strategy is evaluated in vitro to direct T-cell signaling. The controller-derived input sequence successfully drives the relative concentration of phosphorylated Erk along the desired trajectory when implemented in the laboratory.
Date of Conference: 10-13 December 2012
Date Added to IEEE Xplore: 04 February 2013
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Conference Location: Maui, HI, USA

I. Introduction

T lymphocytes (T cells) are an integral part of the human body's natural defense against the threats of invading pathogens and cancerous cells. Engagement of T cell receptors (TCRs) immediately initiates intracellular signal transduction pathways resulting in the activation of transcription factors that ultimately direct the cell's action. During this process, manipulations to the early signaling events within the transduction pathways can alter the cell's response through changes to the active transcription factor profile. Traditional biochemical assays can monitor only a limited number of signaling molecules and do not support real-time observations. As a result, open-loop control provides a suitable tool for designing systematic manipulations to obtain desired signaling responses.

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