ArticlePLoS computational biology2023
Fidelity of hyperbolic space for Bayesian phylogenetic inference.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- VINE: Variational inference for scalable Bayesian reconstruction of species and cell-lineage phylogenies.bioRxiv : the preprint server for biology · 2026Article
- Comparative Analysis of Evolutionary Distances Using the GenusInternational journal of molecular sciences · 2025Article
- Edit Distance Embedding with Genomic Large Language Model.bioRxiv : the preprint server for biology · 2025Article
- Article
- Common Methods for Phylogenetic Tree Construction and Their Implementation in R.Bioengineering (Basel, Switzerland) · 2024Review
- Differentiable phylogeneticsBioinformatics advances · 2024Article
- Towards explainable interaction prediction: Embedding biological hierarchies into hyperbolic interaction space.PloS one · 2024Article
- Leaping through Tree Space: Continuous Phylogenetic Inference for Rooted and Unrooted Trees.Genome biology and evolution · 2023Article
- Fidelity of hyperbolic space for Bayesian phylogenetic inference.PLoS computational biology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bayesian inference for phylogenetics is a gold standard for computing distributions of phylogenies. However, Bayesian phylogenetics faces the challenging computational problem of moving throughout the high-dimensional space of trees. Fortunately, hyperbolic space offers a low dimensional representation of tree-like data. In this paper, we embed genomic sequences as points in hyperbolic space and perform hyperbolic Markov Chain Monte Carlo for Bayesian inference in this space. The posterior probability of an embedding is computed by decoding a neighbour-joining tree from the embedding locations of the sequences. We empirically demonstrate the fidelity of this method on eight data sets. We systematically investigated the effect of embedding dimension and hyperbolic curvature on the performance in these data sets. The sampled posterior distribution recovers the splits and branch lengths to a high degree over a range of curvatures and dimensions. We systematically investigated the effects of the embedding space's curvature and dimension on the Markov Chain's performance, demonstrating the suitability of hyperbolic space for phylogenetic inference.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.