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Related Concept Videos

Methods of Nuclear Reprogramming01:24

Methods of Nuclear Reprogramming

Nuclear reprogramming is a process of transforming one cell type into an unrelated cell type by epigenetic changes that alter the cell’s original gene expression pattern. Such epigenetic changes force cells to express a different set of genes, which play a significant role in inducing transformation into other cell types. Nuclear reprogramming offers applications in reproductive cloning for livestock propagation and regenerative medicine — developing patient-specific cells for injury repair.
Somatic to iPS Cell Reprogramming01:29

Somatic to iPS Cell Reprogramming

Reprogramming alters the gene expression in somatic cells, transforming them into induced pluripotent stem (iPS) cells over several generations. Scientists can reprogram cells by introducing genes for four transcription factors—Oct4, Sox2, Klf4, and c-Myc (OSKM) by viral or non-viral methods. These factors are also known as Yamanaka factors after Shinya Yamanaka, who first generated iPS cells using mouse skin cells. Yamanaka was awarded the Nobel Prize in Physiology or Medicine in 2012 for this...
The Central Dogma01:20

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RNA is the Missing Link Between DNA and Proteins
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Introduction to Nuclear Reprogramming01:14

Introduction to Nuclear Reprogramming

Nuclear reprogramming is the process of switching gene expression of one cell type to that of another cell type, usually from a differentiated cell state to an undifferentiated cell state. Differentiation occurs during processes such as development and morphogenesis, tissue regeneration, and malignancy. Cells can also be artificially induced to reprogram their gene expression by techniques such as nuclear transfer, induced pluripotency, and cell fusion. Such techniques have many applications in...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
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What is Genetic Engineering?00:49

What is Genetic Engineering?

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Related Experiment Video

Updated: Jun 10, 2026

Rapid Characterization of Genetic Parts with Cell-Free Systems
05:00

Rapid Characterization of Genetic Parts with Cell-Free Systems

Published on: August 30, 2021

Programming cells: towards an automated 'Genetic Compiler'.

Kevin Clancy1, Christopher A Voigt

  • 1Life Technologies, 5791 Van Allen Way, Carlsbad, CA 90028, USA.

Current Opinion in Biotechnology
|August 13, 2010
PubMed
Summary
This summary is machine-generated.

Synthetic biology aims to program cells like computers, developing a genetic compiler for complex DNA programs. This approach abstracts design complexity, enabling automated DNA sequence generation and error checking for larger projects.

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Last Updated: Jun 10, 2026

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Area of Science:

  • Synthetic Biology
  • Computational Biology
  • Genetic Engineering

Background:

  • Programming cells offers a powerful paradigm in synthetic biology.
  • Managing large genetic programs at the nucleotide level is complex and error-prone.
  • Current methods necessitate advanced computer-aided design (CAD) software for scalability.

Purpose of the Study:

  • To develop a higher-level programming language for genetic programs.
  • To create a genetic compiler for automated DNA sequence synthesis.
  • To abstract design processes, simplifying the creation of complex cellular programs.

Main Methods:

  • Defining the semantics of a high-level genetic programming language.
  • Developing algorithms for automated part selection and assembly.
  • Integrating biophysical methods to correlate DNA sequence with cellular function.
  • Coupling design interfaces with simulation packages for prediction and optimization.

Main Results:

  • Establishment of a framework for high-level genetic programming.
  • Demonstration of automated DNA sequence generation from abstract specifications.
  • Improved methods for predicting cellular program dynamics and optimizing gene function.
  • Tools for error scanning in large genetic projects.

Conclusions:

  • A higher-level programming language and genetic compiler can significantly advance synthetic biology.
  • Abstraction in design simplifies the creation of complex, large-scale genetic programs.
  • Integrated CAD tools and simulation are crucial for efficient design, optimization, and error checking.