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Related Concept Videos

Methods of Nuclear Reprogramming01:24

Methods of Nuclear Reprogramming

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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...
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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...
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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...
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Related Experiment Video

Updated: Sep 7, 2025

Application of RNAi and Heat-shock-induced Transcription Factor Expression to Reprogram Germ Cells to Neurons in C. elegans
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NETISCE: a network-based tool for cell fate reprogramming.

Lauren Marazzi1, Milan Shah1, Shreedula Balakrishnan1

  • 1Center for Quantitative Medicine, University of Connecticut School of Medicine, Farmington, CT, 06030, USA.

NPJ Systems Biology and Applications
|June 20, 2022
PubMed
Summary
This summary is machine-generated.

NETISCE is a new computational tool that identifies cell fate reprogramming targets in static biological networks. It aids regenerative medicine and cancer research by predicting therapeutic targets without extensive data.

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Area of Science:

  • Computational Biology
  • Systems Biology
  • Genomics

Background:

  • Cell fate reprogramming is crucial for regenerative medicine and cancer research.
  • Current methods for identifying reprogramming targets are limited, especially for systems lacking extensive data or dynamical characterization.

Purpose of the Study:

  • To introduce NETISCE, a novel computational tool for identifying cell fate reprogramming targets in static biological networks.
  • To enable the prediction of reprogramming targets in large-scale biological systems without requiring full model parameterization.

Main Methods:

  • NETISCE combines machine learning algorithms with signal flow analysis and feedback vertex set control.
  • It estimates the attractor landscape to predict reprogramming targets.

Main Results:

  • NETISCE successfully predicted known cell fate reprogramming targets in developmental, stem cell, and cancer biology studies.
  • The tool identified potentially novel combinations of reprogramming targets.

Conclusions:

  • NETISCE expands the applicability of cell fate reprogramming studies to larger biological networks.
  • It serves as a valuable tool for both experimental and computational biologists in identifying key regulatory elements for desired cellular transitions.