Graph-based Spatial Modeling

Graph-Based Spatial Modeling is a computational framework that represents biological entities and their spatial relationships as a graph, where nodes denote spatially resolved biological components and edges encode their spatial interactions or proximity, enabling the analysis of tissue architecture and cellular organization in a structured, topology-preserving manner.

15

Publications

858

Citations

61

Authors

32

Institutions

Publications per year

2017–2026

7

Authors

61

  1. MG
    Mark G. Kris

    Memorial Sloan Kettering Cancer Center, United States

    1 publications · 39 citations

    1

    h-index

  2. SM
    Sathya Muralidhar

    Institute of Cancer Research, United Kingdom

    1 publications · 78 citations

    1

    h-index

  3. AC
    Anna C. Schaar

    Helmholtz Zentrum München, Germany

    1 publications · 203 citations

    1

    h-index

  4. WZ
    Weixin Zheng

    Wuhan University of Technology, China

    1 publications · 50 citations

    1

    h-index

  5. HL
    Haobing Liu

    Shanghai Jiao Tong University, China

    1 publications · 70 citations

    1

    h-index

1–5 of 61

Venues

  1. Lecture notes in computer science

    LNCS · Book series · 2 publications · 31 citations

    2

    h-index

  2. Environment and Planning B Planning and Design

    2 publications · 134 citations

    2

    h-index

  3. eCAADe proceedings

    1 publications · 18 citations

    1

    h-index

  4. IEEE Transactions on Image Processing

    1 publications · 16 citations

    1

    h-index

  5. Cancer Research

    1 publications · 78 citations

    1

    h-index

1–5