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New AI model reconstructs extinct protein sequences using evolutionary trees

Researchers have developed a novel tree-conditioned edit-flow model for ancestral sequence reconstruction (ASR), aiming to infer extinct protein sequences. This model reconstructs ancestors by using paired bidirectional edit trajectories that converge on a common ancestral state, accommodating insertions, deletions, and substitutions. While it did not outperform classical methods on a benchmark with only context-independent substitutions, it showed strong performance on natural homologous sequences with complex evolutionary changes. AI

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IMPACT Introduces a new method for inferring protein evolution, potentially improving biological sequence analysis.

RANK_REASON This is a research paper published on arXiv detailing a new model for ancestral sequence reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

COVERAGE [1]

  1. arXiv cs.LG TIER_1 · Emil Sharafutdinov, Ingemar Andr\'e ·

    Tree-Conditioned Edit Flows for Ancestral Sequence Reconstruction

    arXiv:2605.04119v1 Announce Type: cross Abstract: Ancestral sequence reconstruction (ASR) aims to infer extinct protein sequences at internal nodes of a phylogenetic tree. Classical ASR methods are typically based on continuous-time Markov substitution models, but they treat site…