Evidence map›Paper›PMID 23275296›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Evolutionary inference via the Poisson Indel Process.

Alexandre Bouchard-Côté, Michael I Jordan

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Article
  2. Protein Structural Phylogenetics.Genome biology and evolution · 2025
    Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
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  11. Article
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  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Solving the master equation for Indels.BMC bioinformatics · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alexandre Bouchard-CôtéDepartment of Statistics, University of British Columbia, Vancouver, BC, Canada V6T 1Z4.
Michael I Jordan

Funding

COMPUTATIONAL STRUCTURAL AND FUNCTIONAL GENOMICSK22HG000056 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E · 2000 to 2003
$1.1M
NHGRI NIH HHS K22 HG000056NHGRI NIH HHS K22 HG00056
6 · The paper itself

Abstract

We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

Indexed as

Evolution, MolecularINDEL MutationModels, GeneticModels, StatisticalBayes TheoremBiostatisticsLikelihood FunctionsMarkov ChainsPhylogenyPoisson DistributionSequence Alignment

Identifiers

PMID23275296
PMCPMC3557041

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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.