Concepedia

Dynamic Adjacency Matrix Visualization

Dynamic Adjacency Matrix Visualization is a computational visualization framework that extends static adjacency matrix representations by incorporating time-varying or interactive structural changes in networks, enabling the systematic depiction of evolving graph topologies over time or under varying conditions.

2

Publications

35

Citations

6

Authors

2

Institutions

Publications per year

2017–2026

0

Parents

Publications

2

1–2 of 2

Authors

6

  1. JF
    Jean‐Daniel Fekete

    Institut national de recherche en sciences et technologies du numérique, France

    1 publications · 11 citations

    1

    h-index

  2. NJ
    Narendra Jussien

    Computer Algorithms for Medicine, Austria

    1 publications · 11 citations

    1

    h-index

  3. YC
    Yan Cui

    University of Tennessee Health Science Center, United States

    1 publications · 24 citations

    1

    h-index

  4. MG
    Mohammad Ghoniem

    Luxembourg Institute of Science and Technology, Luxembourg

    1 publications · 11 citations

    1

    h-index

  5. MZ
    Mi Zhou

    University of California, San Francisco, United States

    1 publications · 24 citations

    1

    h-index

1–5 of 6

Institutions

2

  1. Institut national de recherche en sciences et technologies du numérique

    Le Chesnay-Rocquencourt, France

    1 h-index

    1 publications

    11 citations

  2. University of Tennessee Health Science Center

    Memphis, United States

    1 h-index

    2 publications

    48 citations

1–2 of 2

Venues

  1. In Silico Biology

    ISB · 1 publications · 24 citations

    1

    h-index

1–1