Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
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 predi...
Päätekijät: | 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 |
---|---|
Aineistotyyppi: | Artikkeli |
Kieli: | English |
Julkaistu: |
Nature Portfolio
2020-10-01
|
Sarja: | Nature Communications |
Linkit: | https://doi.org/10.1038/s41467-020-18832-8 |
Samankaltaisia teoksia
-
Author Correction: Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors
Tekijä: Xiaoyu Tu, et al.
Julkaistu: (2023-03-01) -
Impact of artefact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data.
Tekijä: Thomas Samuel Carroll, et al.
Julkaistu: (2014-04-01) -
ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis
Tekijä: Karchenko Peter V, et al.
Julkaistu: (2011-02-01) -
ChIP-Seq in Candida albicans
Tekijä: Sadri Znaidi, et al.
Julkaistu: (2014-06-01) -
ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data
Tekijä: Pagès Hervé, et al.
Julkaistu: (2010-05-01)