{
  "annotation_id": "6406d15c-72f5-470e-8e7e-d1d749bb17c7",
  "date_created": "2026-03-02T18:01:32.243000Z",
  "date_modified": "2026-03-02T18:01:32.243000Z",
  "file_hash": "46d55fe1dc6cd5437bd81f29033bd6c136f9d0b0885178191af69c0be6abbbdd",
  "private": false,
  "record": {
    "abstract": "Markov chain Monte Carlo algorithms play a key role in the Bayesian approach\nto phylogenetic inference. In this paper, we present the first theoretical work\nanalyzing the rate of convergence of several Markov chains widely used in\nphylogenetic inference. We analyze simple, realistic examples where these\nMarkov chains fail to converge quickly. In particular, the data studied are\ngenerated from a pair of trees, under a standard evolutionary model. We prove\nthat many of the popular Markov chains take exponentially long to reach their\nstationary distribution. Our construction is pertinent since it is well known\nthat phylogenetic trees for genes may differ within a single organism. Our\nresults shed a cautionary light on phylogenetic analysis using Bayesian\ninference and highlight future directions for potential theoretical work.",
    "arxiv_id": "q-bio/0505002",
    "authors": [
      "Elchanan Mossel",
      "Eric Vigoda"
    ],
    "categories": [
      "q-bio.PE",
      "q-bio.GN"
    ],
    "doi": "10.1214/105051600000000538",
    "journal_ref": "Annals of Applied Probability 2006, Vol. 16, No. 4, 2215-2234",
    "title": "Limitations of Markov chain Monte Carlo algorithms for Bayesian   Inference of phylogeny",
    "url": "https://arxiv.org/abs/q-bio/0505002"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "d4be443c-3107-42f2-801c-21cf5a3ace6a",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}