Evidence map›Paper›PMID 25143952›Full record

ReviewBioMed research international2014

Modeling biology spanning different scales: an open challenge.

Filippo Castiglione, Francesco Pappalardo, Carlo Bianca, Giulia Russo, Santo Motta

Abstract readReview
In one paragraph

Review in BioMed research international, 2014. 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
–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

22 citing papers in PubMed.

  1. Review
  2. Multiscale Modeling and Systems Biology in Microgravity Investigations.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Review
  5. Unveiling Forkhead-mediated regulation of yeast cell cycle and metabolic networks.Computational and structural biotechnology journal · 2022
    Article
  6. Cellular and molecular bioengineering · 2021
    Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Artificial cell mimics as simplified models for the study of cell biology.Experimental biology and medicine (Maywood, N.J.) · 2017
    Review
  17. Review
  18. Article
  19. Article
  20. Review
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.

Filippo CastiglioneInstitute for Applied Mathematics, National Research Council of Italy, Rome, Italy.ORCID 0000-0002-1442-3552
Francesco PappalardoDepartment of Pharmaceutical Sciences, University of Catania, Catania, Italy.ORCID 0000-0003-1668-3320
Carlo BiancaTheoretical Physics of Condensed Matter, Sorbonne Universities, UPMC Univ Paris 6, 75252 Paris Cedex 05, France ; UMR 7600 LPTMC, CNRS, 75252 Paris Cedex 05, France.ORCID 0000-0003-1122-7510
Giulia RussoDepartment of Pharmaceutical Sciences, University of Catania, Catania, Italy.ORCID 0000-0001-6616-7856
Santo MottaDepartment of Mathematics and Computer Science, University of Catania, 95125 Catania, Italy.ORCID 0000-0003-3533-2972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.

Indexed as

Models, BiologicalSystems BiologyComputational Biology

Identifiers

PMID25143952
PMCPMC4124842

What OpenQuestion holds

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Registered trials

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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.