Evidence map›Paper›PMID 32513086›Full record

ReviewAnnual review of chemical and biomolecular engineering2020

How Do Cells Adapt? Stories Told in Landscapes.

Luca Agozzino, Gábor Balázsi, Jin Wang, Ken A Dill

Open access · hybridAbstract readReview
In one paragraph

Review in Annual review of chemical and biomolecular engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
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

22 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. The challenge of distinguishing living from non-living entities.Theory in biosciences = Theorie in den Biowissenschaften · 2026
    Review
  3. Environmental Regulation and Gene-by-Environment Interaction InfluencebioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Adaptive DNA amplification of synthetic gene circuit opens a way to overcome cancer chemoresistance.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  10. Is cancer an intelligent species?Cancer metastasis reviews · 2023
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Journal of biosciences · 2022
    Review
  18. Article
  19. The Protein Folding Problem: The Role of Theory.Journal of molecular biology · 2021
    Review
  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

4 authors at 1 institution in 1 country.

Luca AgozzinoThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; email: dill@laufercenter.org.
Gábor BalázsiThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; email: dill@laufercenter.org.
Jin WangThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; email: dill@laufercenter.org.
Ken A DillThe Louis and Beatrice Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York 11794, USA; email: dill@laufercenter.org.
Stony Brook University · US

Funding

Dynamics and evolution of synthetic and natural gene regulatory networksR35GM122561 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI BALAZSI, GABOR · 2017 to 2025
$4.2M
Theoretical and experimental investigation of multi-domain protein folding and conformational dynamicsR01GM124177 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI WANG, JIN · 2018 to 2021
$1.8M
MELD: accelerating MD modeling of proteins using Bayesian inferenceR01GM125813 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI DILL, KEN A · 2018 to 2021
$1.3M
NIGMS NIH HHS R01 GM124177NIGMS NIH HHS R01 GM125813NIGMS NIH HHS R35 GM122561
6 · The paper itself

Abstract

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

Indexed as

Models, BiologicalAdaptation, PhysiologicalAnimalsEnergy MetabolismEvolution, MolecularHumansMutationProtein FoldingProteinsRNA, MessengerProteinsRNA, Messengeradaptationevolutionfitnesshomeostasislandscape

Identifiers

PMID32513086
PMCPMC7291840
OpenAlexW3033782339

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.