Evidence map›Paper›PMID 34272246›Full record

ArticleScience advances2021

Parity and time reversal elucidate both decision-making in empirical models and attractor scaling in critical Boolean networks.

Jordan C Rozum, Jorge Gómez Tejeda Zañudo, Xiao Gan, Dávid Deritei, Réka Albert

Abstract read
In one paragraph

Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Article
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  5. Generative prediction of causal gene sets responsible for complex traits.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  17. Dauer fate in aPeerJ · 2023
    Article
  18. Article
  19. Leveraging network structure in nonlinear control.NPJ systems biology and applications · 2022
    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

5 authors.

Jordan C RozumDepartment of Physics, The Pennsylvania State University, University Park, PA 16802, USA. jcr52@psu.edu rza1@psu.edu.ORCID http://orcid.org/0000-0002-4356-9809
Jorge Gómez Tejeda ZañudoEli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.ORCID http://orcid.org/0000-0002-1092-0068
Xiao GanNetwork Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA.
Dávid DeriteiDepartment of Molecular Biology, Semmelweis University, Budapest, Hungary.
Réka AlbertDepartment of Physics, The Pennsylvania State University, University Park, PA 16802, USA. jcr52@psu.edu rza1@psu.edu.ORCID http://orcid.org/0000-0002-9485-0828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present new applications of parity inversion and time reversal to the emergence of complex behavior from simple dynamical rules in stochastic discrete models. Our parity-based encoding of causal relationships and time-reversal construction efficiently reveal discrete analogs of stable and unstable manifolds. We demonstrate their predictive power by studying decision-making in systems biology and statistical physics models. These applications underpin a novel attractor identification algorithm implemented for Boolean networks under stochastic dynamics. Its speed enables resolving a long-standing open question of how attractor count in critical random Boolean networks scales with network size and whether the scaling matches biological observations. Via 80-fold improvement in probed network size (

Identifiers

PMID34272246
PMCPMC8284893

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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.