Nature Communications (Oct 2020)

Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors

  • Xiaoyu Tu,
  • María Katherine Mejía-Guerra,
  • Jose A. Valdes Franco,
  • David Tzeng,
  • Po-Yu Chu,
  • Wei Shen,
  • Yingying Wei,
  • Xiuru Dai,
  • Pinghua Li,
  • Edward S. Buckler,
  • Silin Zhong

DOI
https://doi.org/10.1038/s41467-020-18832-8
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 13

Abstract

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Transcriptional factors (TFs) bind in a combinatorial fashion to specify the on-and-off states of genes in a complex and redundant regulatory network. Here, the authors construct the transcription regulatory network in maize leaf using 104 TFs ChIP-seq data and train machine learning models to predict TF binding and colocalization.