Control of Singleton Attractors in Boolean Networks
Author Information
Author(s): Hayashida Morihiro, Tamura Takeyuki, Akutsu Tatsuya, Zhang Shu-Qin, Ching Wai-Ki
Primary Institution: Bioinformatics Center, Institute for Chemical Research, Kyoto University
Hypothesis
The study proposes algorithms for controlling singleton attractors in Boolean networks and analyzes their average-case time complexities.
Conclusion
The proposed algorithms demonstrate that gene ordering significantly affects computational time, with internal nodes yielding better performance when prioritized.
Supporting Evidence
- The algorithms developed are faster than previous methods when the maximum indegree is bounded.
- Most algorithms proposed show significant improvements in computational time.
- The study confirms the importance of gene ordering in computational efficiency.
Takeaway
This study is about finding ways to control how genes behave in a simple model of genetic networks, showing that the order in which we look at genes can make a big difference in how quickly we can solve problems.
Methodology
The study develops several algorithms for controlling singleton attractors in Boolean networks and analyzes their time complexities through theoretical and empirical methods.
Limitations
The algorithms are primarily tested on small networks, and their applicability to larger networks remains uncertain.
Digital Object Identifier (DOI)
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