Mapper Construction

Mapper Construction is a computational method in topological data analysis that generalizes the construction of nerve complexes by combining a continuous map from a topological space to a Euclidean domain with a cover of that domain to produce a combinatorial summary of the data’s shape, distinguished by its use of clustering within preimage sets to capture overlapping topological features.

37

Publications

11.4K

Citations

112

Authors

64

Institutions

Publications per year

2017–2026

9

Authors

112

  1. YS
    Yoko Sato

    Yamaguchi University, Japan

    3 publications · 7K citations

    3

    h-index

  2. MK
    Minoru Kanehisa

    Kyoto University, Japan

    3 publications · 7K citations

    3

    h-index

  3. CG
    Chuang Gan

    IBM (United States), United States

    2 publications · 135 citations

    2

    h-index

  4. BC
    Billy Chan

    University of California, Berkeley, United States

    2 publications · 60 citations

    2

    h-index

  5. AM
    Alan Mishchenko

    University of California, Berkeley, United States

    2 publications · 60 citations

    2

    h-index

1–5 of 112

Venues

  1. Nucleic Acids Research

    4 publications · 5.3K citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 197 citations

    3

    h-index

  3. Protein Science

    PS · 2 publications · 2K citations

    2

    h-index

  4. Forensic Science International Genetics

    FSI · 1 publications · 11 citations

    1

    h-index

  5. Mobile DNA

    1 publications · 32 citations

    1

    h-index

1–5