Probabilistic Reconciliation

Probabilistic Reconciliation is a computational framework within tree reconciliation that models evolutionary discordance between hierarchically related biological entities by assigning probabilities to alternative evolutionary scenarios, distinguishing itself from deterministic methods through its explicit quantification of uncertainty in inferred events.

15

Publications

1.2K

Citations

30

Authors

27

Institutions

Publications per year

2017–2026

3

Authors

30

  1. BS
    Bengt Sennblad

    Karolinska Institutet, Sweden

    5 publications · 452 citations

    5

    h-index

  2. JL
    Jens Lagergren

    KTH Royal Institute of Technology, Sweden

    5 publications · 452 citations

    5

    h-index

  3. LA
    Lars Arvestad

    KTH Royal Institute of Technology, Sweden

    3 publications · 391 citations

    3

    h-index

  4. GJ
    Gergely J. Szöllősi

    Eötvös Loránd University, Hungary

    2 publications · 287 citations

    2

    h-index

  5. VD
    Vincent Daubin

    Centre National de la Recherche Scientifique, France

    2 publications · 287 citations

    2

    h-index

1–5 of 30

Venues

  1. Systematic Biology

    2 publications · 303 citations

    2

    h-index

  2. European Journal of Operational Research

    1 publications · 54 citations

    1

    h-index

  3. BMC Bioinformatics

    1 publications · 18 citations

    1

    h-index

  4. Computers & Chemical Engineering

    1 publications · 13 citations

    1

    h-index

  5. Solar Energy

    1 publications · 33 citations

    1

    h-index

1–5