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Related Experiment Video

Updated: Jun 1, 2026

Using Synthetic Biology to Engineer Living Cells That Interface with Programmable Materials

Using Synthetic Biology to Engineer Living Cells That Interface with Programmable Materials

Published on: March 9, 2017

How do control-based approaches enter into biology?

Philip R LeDuc¹, William C Messner, John P Wikswo

¹Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA. prleduc@cmu.edu

Annual Review of Biomedical Engineering

|May 24, 2011

Summary

This summary is machine-generated.

Biological control systems involve cells sensing and responding to stimuli. This study explores methods to understand and engineer cellular processes using control theory, aiding future research.

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Area of Science:

Systems biology
Control theory applications in cellular systems

Background:

Cells constantly sense and respond to internal and external stimuli.
Control-based approaches are vital for studying complex cellular systems.
Existing methods include chemical/genetic manipulation and feedback/feed-forward strategies.

Purpose of the Study:

To review control-based approaches in cellular systems.
To present methods for determining cellular states and reverse-engineering systems.
To discuss controlling cellular environments for probing and manipulation.

Main Methods:

Analysis of existing control-based methodologies in cell biology.
Proposal of techniques for real-time cellular state determination.
Discussion of engineering-based technologies for environmental control.

Main Results:

Identified gaps in understanding cellular behavior during non-interventional periods.
Outlined strategies for reverse-engineering cellular control mechanisms.
Highlighted potential of engineered environments to probe cellular responses.

Conclusions:

Further development of simplified control models is needed.
New technologies are required to advance the study and application of cellular processes.
Control theory offers a powerful framework for understanding and engineering biological systems.