KAIST Finds a Way to Redirect Cell Fate with Just a Single Stimulus (IMAGE)
Caption
[Fig. 3] Performance comparison of NUDGE
NUDGE mathematically derives, without omission, every minimal combination of control factors capable of achieving a target phenotype, and for large-scale networks, an approximation algorithm is introduced to address computational complexity. NUDGE's approximation algorithm identifies more control targets with higher accuracy than existing control methods. The team also found that biological networks contain far more pathways through self-reinforced motifs, the structural basis of temporary control, than random networks do.
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KAIST
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