Statistical significance of combinatorial regulations

  title={Statistical significance of combinatorial regulations},
  author={A. Terada and M. Okada-Hatakeyama and K. Tsuda and J. Sese},
  journal={Proceedings of the National Academy of Sciences},
  pages={12996 - 13001}
  • A. Terada, M. Okada-Hatakeyama, +1 author J. Sese
  • Published 2013
  • Medicine, Biology
  • Proceedings of the National Academy of Sciences
  • More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing… CONTINUE READING

    Figures, Tables, and Topics from this paper.

    Probing sequence-level instructions for gene expression
    • 1
    • PDF
    MitoFates: Improved Prediction of Mitochondrial Targeting Sequences and Their Cleavage Sites*
    • 214
    • Highly Influenced
    • PDF
    LAMPLINK: detection of statistically significant SNP combinations from GWAS data
    • 10
    • PDF
    Identifying statistically significant combinatorial markers for survival analysis
    • 4


    Publications referenced by this paper.
    Architecture of the human regulatory network derived from ENCODE data
    • 1,235
    • PDF
    An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man
    • 551
    • Highly Influential
    • PDF