Evidence map›Paper›PMID 32089118›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2020

Evolving complexity: how tinkering shapes cells, software and ecological networks.

Ricard Solé, Sergi Valverde

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Biological Systems as Physical Data Processors: Evolution as a Case of Embodied Computing.BioEssays : news and reviews in molecular, cellular and developmental biology · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Open problems in synthetic multicellularity.NPJ systems biology and applications · 2024
    Article
  8. Article
  9. The cultural transmission of tacit knowledge.Journal of the Royal Society, Interface · 2022
    Article
  10. Article
  11. Article
  12. Article
  13. Unifying the essential concepts of biological networks: biological insights and philosophical foundations.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    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

2 authors.

Ricard SoléICREA-Complex Systems Lab, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona 08003, Spain.
Sergi ValverdeEuropean Centre for Living Technology, S. Marco 2940, 30124 Venice, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A common trait of complex systems is that they can be represented by means of a network of interacting parts. It is, in fact, the network organization (more than the parts) that largely conditions most higher-level properties, which are not reducible to the properties of the individual parts. Can the topological organization of these webs provide some insight into their evolutionary origins? Both biological and artificial networks share some common architectural traits. They are often heterogeneous and sparse, and most exhibit different types of correlations, such as nestedness, modularity or hierarchical patterns. These properties have often been attributed to the selection of functionally meaningful traits. However, a proper formulation of generative network models suggests a rather different picture. Against the standard selection-optimization argument, some networks reveal the inevitable generation of complex patterns resulting from reuse and can be modelled using duplication-rewiring rules lacking functionality. These give rise to the observed heterogeneous, scale-free and modular architectures. Here, we examine the evidence for tinkering in cellular, technological and ecological webs and its impact in shaping their architecture. Our analysis suggests a serious consideration of the role played by selection as the origin of network topology. Instead, we suggest that the amplification processes associated with reuse might shape these graphs at the topological level. In biological systems, selection forces would take advantage of emergent patterns. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Indexed as

Cell BiologyEcologyModels, TheoreticalTechnologyEvolution, MolecularPhenotypecomplexityevolutionNetwork Scienceselectionspandrelstinkering

Identifiers

PMID32089118
PMCPMC7061959

What OpenQuestion holds

Textmetadata
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.