Evidence map›Paper›PMID 25887947›Full record

ReviewTrends in ecology & evolution2015

Measurably evolving pathogens in the genomic era.

Roman Biek, Oliver G Pybus, James O Lloyd-Smith, Xavier Didelot

Abstract readReview
In one paragraph

Review in Trends in ecology & evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 160 papers.

0numbers the graph read from it
0cells of the map it votes in
160citing 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

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.

3 · Its place in the literature

Who cites it

160 citing papers in PubMed.

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100 more citing papers are in PubMed but not listed here.

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

4 authors.

Roman BiekBoyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary, and Life Sciences, University of Glasgow, Glasgow, UK; Fogarty International Center, National Institutes of Health, Bethesda MD, USA. Electronic address: roman.biek@glasgow.ac.uk.
Oliver G PybusDepartment of Zoology, University of Oxford, Oxford, UK.
James O Lloyd-SmithFogarty International Center, National Institutes of Health, Bethesda MD, USA; Department of Ecology and Evolutionary Biology, University of California at Los Angeles, Los Angeles, CA 90095, USA.
Xavier DidelotDepartment of Infectious Disease Epidemiology, Imperial College, London, UK.

Funding

SPATIAL POPULATION DYNAMICS OF RABIESR01AI047498 · NIAID · EMORY UNIVERSITY · PI REAL, LESLIE A. · 1999 to 2014
$3.6M
Biotechnology and Biological Sciences Research Council BB/L010569/1Medical Research Council MR/K010174/1NIAID NIH HHS R01 AI047498
6 · The paper itself

Abstract

Current sequencing technologies have created unprecedented opportunities for studying microbial populations. For pathogens with comparatively low per-site mutation rates, such as DNA viruses and bacteria, whole-genome sequencing can reveal the accumulation of novel genetic variation between population samples taken at different times. The concept of 'measurably evolving populations' and related analytical approaches have provided powerful insights for fast-evolving RNA viruses, but their application to other pathogens is still in its infancy. We argue that previous distinctions between slow- and fast-evolving pathogens become blurred once evolution is assessed at a genome-wide scale, and we highlight important analytical challenges to be overcome to infer pathogen population dynamics from genomic data.

Indexed as

Evolution, MolecularGenome, BacterialGenome, ViralBacteriaMutation RatePopulation DynamicsRNA VirusesbacteriaDNA virusepidemiological modelsevolutionary rateinfectious diseasephylodynamics

Identifiers

PMID25887947
PMCPMC4457702

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.