Regulon Inference

Regulon Inference is a computational method in regulatory network inference that identifies a regulon—a set of co-regulated genes controlled by a common transcription factor—by integrating gene expression data with regulatory prior knowledge to distinguish direct regulatory interactions from indirect associations.

41

Publications

4.4K

Citations

233

Authors

127

Institutions

Publications per year

2017–2026

15

Authors

233

  1. DA
    Dmitry A. Rodionov

    Sanford Burnham Prebys Medical Discovery Institute, United States

    5 publications · 967 citations

    5

    h-index

  2. ID
    Inna Dubchak

    Lawrence Berkeley National Laboratory, United States

    4 publications · 900 citations

    4

    h-index

  3. AP
    Adam P. Arkin

    Lawrence Berkeley National Laboratory, United States

    4 publications · 900 citations

    4

    h-index

  4. PS
    Pavel S. Novichkov

    Lawrence Berkeley National Laboratory, United States

    3 publications · 807 citations

    3

    h-index

  5. MS
    Mikhail S. Gelfand

    Institute for Information Transmission Problems, Russia

    3 publications · 406 citations

    3

    h-index

1–5 of 233

Venues

  1. BMC Bioinformatics

    5 publications · 104 citations

    5

    h-index

  2. PLoS ONE

    5 publications · 131 citations

    5

    h-index

  3. Nucleic Acids Research

    5 publications · 732 citations

    5

    h-index

  4. Bioinformatics

    4 publications · 258 citations

    4

    h-index

  5. BMC Genomics

    2 publications · 587 citations

    2

    h-index

1–5