Evidence map›Paper›PMID 33495364›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

Estimating computational limits on theoretical descriptions of biological cells.

Roland R Netz, William A Eaton

Open access · hybridAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Biology and medicine in the landscape of quantum advantages.Journal of the Royal Society, Interface · 2022
    Review
  6. Review
  7. Review
  8. Life in silico: Are we close yet?Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 2 countries.

Roland R NetzFachbereich Physik, Freie Universität Berlin, 14195 Berlin, Germany; rnetz@physik.fu-berlin.de eaton@nih.gov.ORCID 0000-0003-0147-0162
William A EatonLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD 20892 rnetz@physik.fu-berlin.de eaton@nih.gov.ORCID 0000-0002-9244-5407
Freie Universität Berlin · DENational Institute of Diabetes and Digestive and Kidney Diseases · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There has been much success recently in theoretically simulating parts of complex biological systems on the molecular level, with the goal of first-principles modeling of whole cells. However, there is the question of whether such simulations can be performed because of the enormous complexity of cells. We establish approximate equations to estimate computation times required to simulate highly simplified models of cells by either molecular dynamics calculations or by solving molecular kinetic equations. Our equations place limits on the complexity of cells that can be theoretically understood with these two methods and provide a first step in developing what can be considered biological uncertainty relations for molecular models of cells. While a molecular kinetics description of the genetically simplest bacterial cell may indeed soon be possible, neither theoretical description for a multicellular system, such as the human brain, will be possible for many decades and may never be possible even with quantum computing.

Indexed as

Computing MethodologiesKineticsQuantum TheoryHumansModels, BiologicalMolecular Dynamics Simulationbiological complexitybiological uncertainty principlecomputational limits

Identifiers

PMID33495364
PMCPMC8017709
OpenAlexW3121282391

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.