Evidence map›Paper›PMID 37400577›Full record

ReviewNature reviews. Genetics2023

Steering and controlling evolution - from bioengineering to fighting pathogens.

Michael Lässig, Ville Mustonen, Armita Nourmohammad

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Design principles of the cytotoxic CD8Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026
    Article
  6. Design principles of the cytotoxic CD8bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. The design and engineering of synthetic genomes.Nature reviews. Genetics · 2025
    Review
  10. Article
  11. Concepts and Methods for Predicting Viral Evolution.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  12. Extending evolutionary forecasts across bacterial species.Proceedings. Biological sciences · 2024
    Article
  13. Concepts and methods for predicting viral evolution.bioRxiv : the preprint server for biology · 2024
    Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. 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

3 authors.

Michael Lässig *Institute for Biological Physics, University of Cologne, Cologne, Germany. mlaessig@uni-koeln.de.ORCID 0000-0002-3575-6719
Ville Mustonen *Organismal and Evolutionary Biology Research Programme, Department of Computer Science, Institute of Biotechnology, University of Helsinki, Helsinki, Finland. v.mustonen@helsinki.fi.ORCID 0000-0002-7270-1792
Armita Nourmohammad *Department of Physics, University of Washington, Seattle, WA, USA. armita@uw.edu.ORCID 0000-0002-6245-3553

Funding

Learning a molecular shape space for the adaptive immune systemR35GM142795 · NIGMS · UNIVERSITY OF WASHINGTON · PI NOURMOHAMMAD, ARMITA · 2021 to 2025
$1.8M
NIGMS NIH HHS R35 GM142795
6 · The paper itself

Abstract

Control interventions steer the evolution of molecules, viruses, microorganisms or other cells towards a desired outcome. Applications range from engineering biomolecules and synthetic organisms to drug, therapy and vaccine design against pathogens and cancer. In all these instances, a control system alters the eco-evolutionary trajectory of a target system, inducing new functions or suppressing escape evolution. Here, we synthesize the objectives, mechanisms and dynamics of eco-evolutionary control in different biological systems. We discuss how the control system learns and processes information about the target system by sensing or measuring, through adaptive evolution or computational prediction of future trajectories. This information flow distinguishes pre-emptive control strategies by humans from feedback control in biotic systems. We establish a cost-benefit calculus to gauge and optimize control protocols, highlighting the fundamental link between predictability of evolution and efficacy of pre-emptive control.

Indexed as

BioengineeringBiological EvolutionHumans

Identifiers

PMID37400577
PMCPMC11137064

What OpenQuestion holds

Textmetadata
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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.