Probabilistic State Models

Probabilistic State Models is a computational modeling framework in cell fate analysis that represents cellular states as discrete entities and transitions between them as stochastic processes governed by probabilistic rules, thereby capturing the inherent variability and uncertainty in cell fate decisions.

168

Publications

8.9K

Citations

480

Authors

215

Institutions

Publications per year

2017–2026

31

Authors

480

  1. WB
    Wolfram Burgard

    University of Freiburg, Germany

    4 publications · 106 citations

    4

    h-index

  2. MB
    Michael Beetz

    Technical University of Munich, Germany

    3 publications · 179 citations

    3

    h-index

  3. RH
    Robert Hanek

    Technical University of Munich, Germany

    2 publications · 139 citations

    2

    h-index

  4. SB
    Sebastian Buck

    University of Tübingen, Germany

    2 publications · 139 citations

    2

    h-index

  5. BL
    Beth L. Hill

    Stanford University, United States

    2 publications · 44 citations

    2

    h-index

1–5 of 480

Venues

  1. 3

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  2. arXiv (Cornell University)

    Repository · 3 publications · 176 citations

    3

    h-index

  3. Theoretical Computer Science

    2 publications · 91 citations

    2

    h-index

  4. 2

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  5. IEEE Transactions on Smart Grid

    2 publications · 135 citations

    2

    h-index

1–5