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Updated: May 7, 2026
07:55
A Deep-sequencing-assisted, Spontaneous Suppressor Screen in the Fission Yeast Schizosaccharomyces pombe
Published on: March 7, 2019
Boolean network model predicts knockout mutant phenotypes of fission yeast
Maria I Davidich1, Stefan Bornholdt
1Institute for Theoretical Physics, University of Bremen, Bremen, Germany.
Plos One
|September 27, 2013
Summary
Boolean networks accurately predict gene regulatory network dynamics and yeast cell cycle mutant viability. This demonstrates their potential to complement detailed models in systems biology for understanding cellular regulation.
Area of Science:
- Systems Biology
- Computational Biology
- Biochemical Signaling Networks
Background:
- Boolean networks are simple mathematical models of biochemical signaling networks.
- These models can predict dynamical activation patterns of gene regulatory networks, including yeast cell cycle dynamics.
Purpose of the Study:
- To investigate if Boolean networks can predict complex cellular phenomena like cell cycle dynamics in yeast mutants.
- To assess the capability of Boolean networks in predicting mutant viability, a task previously reserved for more complex models.
Main Methods:
- Development and application of a Boolean network model for the cell cycle control network of yeast (S. pombe).
- Comparison of the Boolean network model's predictions with known viability data for various yeast mutants.
Main Results:
- The Boolean network model correctly predicted the viability of a significant number of known S. pombe mutants.
- This predictive capability was previously thought to be beyond the scope of simple Boolean network models.
Conclusions:
- Boolean networks can successfully predict complex cellular behaviors, such as mutant viability, in addition to wild-type dynamics.
- These findings support the utility of Boolean networks as a complementary tool in systems biology, particularly when focusing on overall regulatory blueprints rather than biochemical details.
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