Evidence map›Paper›PMID 22141422›Full record

ArticleAMB Express2011

Modeling formalisms in Systems Biology.

Daniel Machado, Rafael S Costa, Miguel Rocha, Eugénio C Ferreira, Bruce Tidor, Isabel Rocha

Abstract read
In one paragraph

Article in AMB Express, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.

0numbers the graph read from it
0cells of the map it votes in
72citing 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

72 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Personalizing computational models to construct medical digital twins.Journal of the Royal Society, Interface · 2025
    Article
  8. Personalizing computational models to construct medical digital twins.bioRxiv : the preprint server for biology · 2024
    Article
  9. Towards a comprehensive assessment of QSP models: what would it take?Journal of pharmacokinetics and pharmacodynamics · 2024
    Review
  10. Article
  11. Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024
    Review
  12. Review
  13. Article
  14. Review
  15. Article
  16. Joint Realizability of Monotone Boolean Functions.Theoretical computer science · 2022
    Article
  17. Review
  18. Article
  19. Article
  20. Article

12 more citing papers are in PubMed but not listed here.

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

6 authors.

Daniel MachadoIBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt.
Rafael S Costa
Miguel Rocha
Eugénio C Ferreira
Bruce Tidor
Isabel Rocha

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systems Biology has taken advantage of computational tools and high-throughput experimental data to model several biological processes. These include signaling, gene regulatory, and metabolic networks. However, most of these models are specific to each kind of network. Their interconnection demands a whole-cell modeling framework for a complete understanding of cellular systems. We describe the features required by an integrated framework for modeling, analyzing and simulating biological processes, and review several modeling formalisms that have been used in Systems Biology including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, differential equations, rule-based models, interacting state machines, cellular automata, and agent-based models. We compare the features provided by different formalisms, and discuss recent approaches in the integration of these formalisms, as well as possible directions for the future.

Identifiers

PMID22141422
PMCPMC3285092

What OpenQuestion holds

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LicenceCC BY
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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.