A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle

This study integrates experimental data into a Boolean discrete model to explain the regulatory logic of the Arabidopsis thaliana cell cycle. We proposed a network that converges into a single robust limit cycle attractor, mimicking the patterns of molecular components observed during the cell cycle phases. The model was validated using loss- and gain-of-function mutants and was further supported by a continuous approximation, ensuring that the results were an emergent consequence of the regulatory logic rather than an artifact of the discrete formalisms. This work provides a theoretical framework to address cell cycle regulation and propose novel predictions in plants and other eukaryotes[cite: 620].

Recommended citation: Ortiz-Gutiérrez, E., García-Cruz, K., Azpeitia, E., Castillo, A., Sánchez, M. D. L. P., & Álvarez-Buylla, E. R. (2015). A dynamic gene regulatory network model that recovers the cyclic behavior of Arabidopsis thaliana cell cycle. PLoS computational biology, 11(9), e1004486.
Download Paper