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Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis

Author

Listed:
  • Kristin C. Gunsalus

    (New York University)

  • Hui Ge

    (Harvard Medical School)

  • Aaron J. Schetter

    (New York University)

  • Debra S. Goldberg

    (Harvard Medical School)

  • Jing-Dong J. Han

    (Harvard Medical School)

  • Tong Hao

    (Harvard Medical School)

  • Gabriel F. Berriz

    (Harvard Medical School)

  • Nicolas Bertin

    (Harvard Medical School)

  • Jerry Huang

    (New York University)

  • Ling-Shiang Chuang

    (New York University)

  • Ning Li

    (Harvard Medical School)

  • Ramamurthy Mani

    (Harvard Medical School)

  • Anthony A. Hyman

    (Max Planck Institute of Molecular Cell Biology and Genetics)

  • Birte Sönnichsen

    (Cenix BioScience GmbH)

  • Christophe J. Echeverri

    (Cenix BioScience GmbH)

  • Frederick P. Roth

    (Harvard Medical School)

  • Marc Vidal

    (Harvard Medical School)

  • Fabio Piano

    (New York University)

Abstract

Beating the system The early stages of embryogenesis in the nematode Caenorhabditis elegans are an ideal system in which to test the potential of ‘system-level’ approaches to understanding biological processes, as opposed to the conventional reductionist approach that focuses on individual enzymes. By integrating information on how proteins interact with each other, how genes are expressed and the effect of ‘knocking-down’ hundreds of genes, Gunsalus et al. have generated a string of models of molecular machines involved in driving early embryogenesis, and are able to propose functional links between these machines. Ten previously uncharacterized proteins were identified as significant in these pathways, showing how the systems can feed information back into single-reaction experiments.

Suggested Citation

  • Kristin C. Gunsalus & Hui Ge & Aaron J. Schetter & Debra S. Goldberg & Jing-Dong J. Han & Tong Hao & Gabriel F. Berriz & Nicolas Bertin & Jerry Huang & Ling-Shiang Chuang & Ning Li & Ramamurthy Mani &, 2005. "Predictive models of molecular machines involved in Caenorhabditis elegans early embryogenesis," Nature, Nature, vol. 436(7052), pages 861-865, August.
    • Handle: RePEc:nat:nature:v:436:y:2005:i:7052:d:10.1038_nature03876
    DOI: 10.1038/nature03876
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    Cited by:

    1. Hirofumi Nakaoka & Tailin Cui & Atsushi Tajima & Akira Oka & Shigeki Mitsunaga & Koichi Kashiwase & Yasuhiko Homma & Shinji Sato & Yasuo Suzuki & Hidetoshi Inoko & Ituro Inoue, 2011. "A Systems Genetics Approach Provides a Bridge from Discovered Genetic Variants to Biological Pathways in Rheumatoid Arthritis," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-16, September.
    2. Han Yan & Kavitha Venkatesan & John E Beaver & Niels Klitgord & Muhammed A Yildirim & Tong Hao & David E Hill & Michael E Cusick & Norbert Perrimon & Frederick P Roth & Marc Vidal, 2010. "A Genome-Wide Gene Function Prediction Resource for Drosophila melanogaster," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-11, August.
    3. Recep Colak & Flavia Moser & Jeffrey Shih-Chieh Chu & Alexander Schönhuth & Nansheng Chen & Martin Ester, 2010. "Module Discovery by Exhaustive Search for Densely Connected, Co-Expressed Regions in Biomolecular Interaction Networks," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-15, October.
    4. Craig, Adam & Yücel, Mesut & Muchnik, Lev & Hershberg, Uri, 2022. "Impact of finite size effect on applicability of generalized fractal and spectral dimensions to biological networks," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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