1. Computational and Systems Biology

Emergence of power-law distributions in protein-protein interaction networks through study bias

  1. David B Blumenthal  Is a corresponding author
  2. Marta Lucchetta
  3. Linda Kleist
  4. Sándor P Fekete
  5. Markus List  Is a corresponding author
  6. Martin H Schaefer  Is a corresponding author
  1. University of Erlangen-Nuremberg, Germany
  2. European Institute of Oncology, Italy
  3. Technische Universität Braunschweig, Germany
  4. Technical University of Munich, Germany
https://doi.org/10.7554/eLife.99951
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  1. David B Blumenthal
  2. Marta Lucchetta
  3. Linda Kleist
  4. Sándor P Fekete
  5. Markus List
  6. Martin H Schaefer
(2024)
Emergence of power-law distributions in protein-protein interaction networks through study bias
eLife 13:e99951.
https://doi.org/10.7554/eLife.99951
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Abstract

Degree distributions in protein-protein interaction (PPI) networks are believed to follow a power law (PL). However, technical and study bias affect the experimental procedures for detecting PPIs. For instance, cancer-associated proteins have received disproportional attention. Moreover, bait proteins in large-scale experiments tend to have many false-positive interaction partners. Studying the degree distributions of thousands of PPI networks of controlled provenance, we address the question if PL distributions in observed PPI networks could be explained by these biases alone. Our findings are supported by mathematical models and extensive simulations and indicate that study bias and technical bias suffice to produce the observed PL distribution. It is, hence, problematic to derive hypotheses about the topology of the true biological interactome from the PL distributions in observed PPI networks. Our study casts doubt on the use of the PL property of biological networks as a modeling assumption or quality criterion in network biology.

Data availability

We analyzed only previously published data for this work. To facilitate reproducibility, we deposited the used datasets at https://zenodo.org/record/8288898.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. David B Blumenthal

    Department Artificial Intelligence in Biomedical Engineering, University of Erlangen-Nuremberg, Erlangen, Germany
    For correspondence
    david.b.blumenthal@fau.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8651-750X

  2. Marta Lucchetta

    Department of Experimental Oncology, European Institute of Oncology, Milan, Italy
    Competing interests
    The authors declare that no competing interests exist.

  3. Linda Kleist

    Department of Computer Science, Technische Universität Braunschweig, Braunschweig, Germany
    Competing interests
    The authors declare that no competing interests exist.

  4. Sándor P Fekete

    Department of Computer Science, Technische Universität Braunschweig, Braunschweig, Germany
    Competing interests
    The authors declare that no competing interests exist.

  5. Markus List

    Data Science in Systems Biology, Technical University of Munich, Freising, Germany
    For correspondence
    markus.list@tum.de
    Competing interests
    The authors declare that no competing interests exist.

  6. Martin H Schaefer

    Department of Experimental Oncology, European Institute of Oncology, Milan, Italy
    For correspondence
    martin.schaefer@ieo.it
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7503-6364

Funding

Bundesministerium für Bildung und Forschung (031L0309A)

  • David B Blumenthal

Klaus Tschira Stiftung (00.003.2024)

  • David B Blumenthal
  • Markus List
  • Martin H Schaefer

Fondazione AIRC per la ricerca sul cancro ETS (MFAG 21791)

  • Martin H Schaefer

Fondazione AIRC per la ricerca sul cancro ETS (Bridge Grant n. 29162)

  • Martin H Schaefer

Ministero della Salute (Ricerca Corrente)

  • Martin H Schaefer

Ministero della Salute (5x1000 funds)

  • Martin H Schaefer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2024, Blumenthal et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. David B Blumenthal
  2. Marta Lucchetta
  3. Linda Kleist
  4. Sándor P Fekete
  5. Markus List
  6. Martin H Schaefer
(2024)
Emergence of power-law distributions in protein-protein interaction networks through study bias
eLife 13:e99951.
https://doi.org/10.7554/eLife.99951

Share this article

https://doi.org/10.7554/eLife.99951

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