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A review on gene regulatory network reconstruction algorithms based on single cell RNA sequencing.

Hyeonkyu KimHwisoo ChoiDaewon LeeJunil Kim
Published in: Genes & genomics (2023)
GRN reconstructors can be classified based on their requirement for cellular trajectory, which represents a dynamical cellular process including differentiation, aging, or disease progression. Benchmarking studies support the superiority of GRN reconstructors that do not require trajectory analysis in identifying regulator-target relationships. However, methods equipped with trajectory analysis demonstrate better performance in identifying key regulatory factors. In conclusion, researchers should select a suitable GRN reconstructor based on their specific research objectives.
Keyphrases
  • single cell
  • machine learning
  • rna seq
  • transcription factor
  • high throughput
  • deep learning
  • molecular dynamics