Evidence map›Paper›PMID 31806491›Full record

ArticleNeuron2020

A Genetic Model of the Connectome.

Dániel L Barabási, Albert-László Barabási

Abstract read
In one paragraph

Article in Neuron, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. A data-driven framework linking the connectome to spatial gene expression gradients inspired by chemoaffinity theory.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. Article
  4. Building the connectome of a small brain with a simple stochastic developmental generative model.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Encoding innate ability through a genomic bottleneck.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Article
  13. Neuroscience Needs Network Science.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Bringing Anatomical Information into Neuronal Network Models.Advances in experimental medicine and biology · 2022
    Article
  19. Article
  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

2 authors.

Dániel L BarabásiBiophysics Program, Harvard University, Cambridge, MA 02138, USA.
Albert-László BarabásiNetwork Science Institute, Northeastern University, Boston, MA 02115, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Data and Network Science, Central European University, Budapest 1051, Hungary. Electronic address: a.barabasi@northeastern.edu.

Funding

MOLECULAR BIOPHYSICS TRAINING GRANTT32GM008313 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI MURTHY, VENKATESH N · 1989 to 2023
$14.6M
NIGMS NIH HHS T32 GM008313
6 · The paper itself

Abstract

The connectomes of organisms of the same species show remarkable architectural and often local wiring similarity, raising the question: where and how is neuronal connectivity encoded? Here, we start from the hypothesis that the genetic identity of neurons guides synapse and gap-junction formation and show that such genetically driven wiring predicts the existence of specific biclique motifs in the connectome. We identify a family of large, statistically significant biclique subgraphs in the connectomes of three species and show that within many of the observed bicliques the neurons share statistically significant expression patterns and morphological characteristics, supporting our expectation of common genetic factors that drive the synapse formation within these subgraphs. The proposed connectome model offers a self-consistent framework to link the genetics of an organism to the reproducible architecture of its connectome, offering experimentally falsifiable predictions on the genetic factors that drive the formation of individual neuronal circuits.

Indexed as

Models, GeneticAnimalsBrainCaenorhabditis elegansCiona intestinalisConnectomeDrosophilaNerve NetBrain NetworksC. elegansConnectomicsdevelopmentencodingGenerative ModelTheory

Identifiers

PMID31806491
PMCPMC7007360

What OpenQuestion holds

Textmetadata
LicenceTDM
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.