Evidence map›Paper›PMID 25444121›Full record

ReviewCurrent opinion in microbiology2014

What can we learn from fitness landscapes?

Daniel L Hartl

Abstract readReview
In one paragraph

Review in Current opinion in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Deconstructing empirical fitness seascapes across scales of granularity.bioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025
    Review
  7. Article
  8. Article
  9. Experimental andACS infectious diseases · 2022
    Article
  10. Article
  11. Article
  12. Relevance of Higher-Order Epistasis in Drug Resistance.Molecular biology and evolution · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. On the deformability of an empirical fitness landscape by microbial evolution.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  18. Article
  19. Article
  20. 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

1 author.

Daniel L HartlDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. Electronic address: dhartl@oeb.harvard.edu.

Funding

Evolutionary medicine in the development of antimalaria drugsR01AI106734 · NIAID · HARVARD UNIVERSITY · PI HARTL, DANIEL L · 2014 to 2017
$1.6M
NIAID NIH HHS AI106734NIAID NIH HHS R01 AI106734
6 · The paper itself

Abstract

A combinatorially complete data set consists of studies of all possible combinations of a set of mutant sites in a gene or mutant alleles in a genome. Among the most robust conclusions from these studies is that epistasis between beneficial mutations often shows a pattern of diminishing returns, in which favorable mutations are less fit when combined than would be expected. Another robust inference is that the number of adaptive evolutionary paths is often limited to a relatively small fraction of the theoretical possibilities, owing largely to sign epistasis requiring evolutionary steps that would entail a decrease in fitness. Here we summarize these and other results while also examining issues that remain unresolved and future directions that seem promising.

Indexed as

Evolution, MolecularMutationAdaptation, BiologicalAllelesBacteriaEpistasis, GeneticGenotypeModels, Genetic

Identifiers

PMID25444121
PMCPMC4254422

What OpenQuestion holds

Textmetadata
LicenceTDM
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.