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PhyloGFN uses generative flow networks for evolutionary relationship inference

By PulseAugur Editorial · [1 sources] ·

Researchers have developed PhyloGFN, a novel method for phylogenetic inference that utilizes generative flow networks (GFlowNets). This approach is designed to address the computational challenges in reconstructing evolutionary relationships from sequence data. PhyloGFN aims to improve the exploration and sampling of complex combinatorial structures, such as tree topologies and evolutionary distances, and has demonstrated competitive performance in marginal likelihood estimation and fitting target distributions compared to existing methods. AI

IMPACT Introduces a novel AI-driven method for complex biological evolutionary analysis, potentially improving scientific discovery in phylogenetics.

RANK_REASON The cluster contains a research paper detailing a new method for phylogenetic inference. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

PhyloGFN uses generative flow networks for evolutionary relationship inference

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The cluster contains a research paper detailing a new method for phylogenetic inference. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mingyang Zhou, Zichao Yan, Elliot Layne, Esmeralda S. Whitammer, Dinghuai Zhang, Moksh Jain, Mathieu Blanchette, Yoshua Bengio ·

    PhyloGFN: Phylogenetic inference with generative flow networks

    arXiv:2310.08774v3 Announce Type: replace-cross Abstract: Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history and numerous applications notwithstanding, inference of phylogenetic trees from seq…

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