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Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
Golden rice is a genetically modified...

In vitro Mutagenesis

In vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

In-vitro Mutagenesis

In-vitro Mutagenesis

To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.

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Updated: May 11, 2026

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

Published on: October 6, 2019

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

Taek Kang¹, Jacob T White, Zhen Xie

¹Bioengineering Department, Center for Systems Biology, University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080, United States.

ACS Synthetic Biology

|May 10, 2013

Summary

This summary is machine-generated.

Researchers developed a new experimental platform to validate biological network reverse engineering methods. This system uses a synthetic gene network in human cells to reliably reconstruct causal relationships, advancing biomolecular network analysis.

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Area of Science:

Systems Biology
Synthetic Biology
Molecular Biology

Background:

Biological network understanding is limited by unreliable reverse engineering methods.
Diverse methodologies hinder validation and comparison of predictive capabilities.
Automated, validated methods for biomolecular network analysis are crucial.

Purpose of the Study:

To introduce a novel experimental platform for developing and verifying reverse engineering algorithms.
To establish a benchmark for validating network characterization methodologies in mammalian cells.
To address the challenge of unraveling complex biomolecular networks.

Main Methods:

Stable integration of an orthogonal synthetic gene network in human kidney cells.
Performing successive perturbations on modular components of the synthetic network.
Quantifying reconstruction performance using protein and RNA measurements.

Main Results:

The synthetic network serves as a reliable benchmark for validating reverse engineering algorithms.
Demonstrated the ability to quantify reconstruction performance of regulatory interactions.
Identified conditions for reliably reconstructing causal relationships in the integrated network.

Conclusions:

The developed platform facilitates the creation and validation of robust reverse engineering tools.
Enables rigorous comparison and independent validation of network inference algorithms.
Advances the field of biomolecular network characterization in human cells.