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# Phylogenetic Inference

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  1. bioRxiv

    HERACLES skips the tree search: quartet likelihoods rebuild a 150,000-cell lineage in about four hours on one GPU

    CRISPR lineage recorders can trace the ancestry of hundreds of thousands of cells, but likelihood-based tree building searches over tree topologies and becomes impractical at that scale. HERACLES places each cell as a point in hyperbolic space, scores the CRISPR editing likelihood of sampled cell quartets, and optimizes those coordinates by gradient descent before a single neighbour-joining pass yields the full tree. On simulated benchmarks its reconstruction error is lower than LAML, Startle-NNI and distance-based methods, and it handles 150,000 cells in about four hours on one GPU.

  2. arXiv

    Phylogenetic posteriors get an iterative generative model: it matches IQ-Tree on simple data and beats it on complex evolution

    Posterior inference over phylogenetic trees has depended on likelihoods, which become intractable once real processes such as insertions, deletions or site selection are modeled. This family of conditional generative models builds a tree step by step, bottom-up, middle-out or top-down, and is trained with a discrete diffusion objective; on real and synthetic data it recovers MCMC posteriors more closely than the prior simulation-based method Phyloformer 2, matches IQ-Tree on simple data, and is reliably more accurate on more realistic complex models.

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