Gradient Decoding

Gradient Decoding is a computational method in developmental biology and systems neuroscience that infers positional identity within a tissue or network by interpreting concentration gradients of morphogens or signaling molecules through spatial decoding mechanisms.

5

Publications

206

Citations

22

Authors

10

Institutions

Publications per year

2017–2026

1

Authors

22

  1. MJ
    Michael Jahr

    Stanford University, United States

    1 publications · 52 citations

    1

    h-index

  2. SV
    Sergey V. Dvinskikh

    KTH Royal Institute of Technology, Sweden

    1 publications · 72 citations

    1

    h-index

  3. JE
    Juan E. Arco

    Universidad de Granada, Spain

    1 publications · 12 citations

    1

    h-index

  4. SS
    Sung Sik Lee

    ETH Zurich, Switzerland

    1 publications · 56 citations

    1

    h-index

  5. JR
    Javier Ramı́rez

    Universidad de Granada, Spain

    1 publications · 12 citations

    1

    h-index

1–5 of 22

Venues

  1. Developmental Cell

    1 publications · 56 citations

    1

    h-index

  2. Journal of Biological Physics

    1 publications · 14 citations

    1

    h-index

  3. Applied Soft Computing

    1 publications · 12 citations

    1

    h-index

  4. Magnetic Resonance in Chemistry

    MRC · 1 publications · 72 citations

    1

    h-index

  5. Artificial Intelligence

    1 publications · 52 citations

    1

    h-index

1–5