Transcriptomics-constrained Modeling

Transcriptomics-Constrained Modeling is a computational framework within genome-scale metabolic modeling that integrates transcriptomic data to constrain and refine metabolic flux predictions by differentially regulating reaction bounds based on gene expression levels.

18

Publications

1K

Citations

60

Authors

37

Institutions

Publications per year

2017–2026

11

Authors

60

  1. JL
    Jennifer L. Reed

    University of Wisconsin–Madison, United States

    2 publications · 84 citations

    2

    h-index

  2. AN
    Ali Navid

    Lawrence Livermore National Laboratory, United States

    1 publications · 76 citations

    1

    h-index

  3. EY
    Elisabeth Yaneske

    Teesside University, United Kingdom

    1 publications · 28 citations

    1

    h-index

  4. SB
    Siddharth Bhadra-Lobo

    Rutgers, The State University of New Jersey, United States

    1 publications · 13 citations

    1

    h-index

  5. ZW
    Zhuo Wang

    Shanghai Jiao Tong University, China

    1 publications · 19 citations

    1

    h-index

1–5 of 60

Venues

  1. BMC Systems Biology

    3 publications · 266 citations

    3

    h-index

  2. BMC Bioinformatics

    2 publications · 58 citations

    2

    h-index

  3. Bioinformatics

    2 publications · 84 citations

    2

    h-index

  4. BMC Genomics

    1 publications · 16 citations

    1

    h-index

  5. Molecular Omics

    1 publications · 15 citations

    1

    h-index

1–5