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A Practical Guide to Phylogenetics for Nonexperts
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Explaining evolution via constrained persistent perfect phylogeny.

Paola Bonizzoni, Anna Paola Carrieri, Gianluca Della Vedova

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    Summary
    This summary is machine-generated.

    The Persistent Perfect Phylogeny (PPP) model explains genomic data evolution. A new Constrained PPP (CPPP) model handles violated assumptions, offering efficient solutions for complex evolutionary histories.

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    Area of Science:

    • Phylogenetics
    • Computational Biology
    • Evolutionary Biology

    Background:

    • The perfect phylogeny model efficiently represents binary character evolution under the infinite sites assumption.
    • Generalizations are needed to address violations of the infinite sites assumption, such as back mutations.
    • The Persistent Perfect Phylogeny (PPP) model allows characters to be gained and lost once, modeling phenomena like protein domain evolution.

    Purpose of the Study:

    • To investigate computational problems related to the Persistent Perfect Phylogeny (PPP) model.
    • To introduce and analyze a generalization of the PPP model with constraints on character persistence.
    • To develop efficient algorithms for reconstructing evolutionary histories under these constrained models.

    Main Methods:

    • Defined the Constrained Persistent Perfect Phylogeny (CPPP) problem, restricting character persistence for certain species.
    • Formulated the CPPP problem using a graph-based approach.
    • Developed a polynomial-time algorithm for CPPP when the conflict graph is edgeless and a parameterized algorithm based on the number of characters.

    Main Results:

    • A polynomial-time solution was found for the CPPP problem on matrices with edgeless conflict graphs.
    • A parameterized algorithm was developed for the general CPPP problem.
    • The CPPP model demonstrates improved ability to explain data compared to the classical perfect phylogeny model.

    Conclusions:

    • The constrained persistent perfect phylogeny model provides a more flexible framework for evolutionary data.
    • The developed algorithms offer efficient computational solutions for phylogenetic reconstruction under constraints.
    • Preliminary experiments confirm the utility of the CPPP model for data not fitting classical models.