Integer Programming-Based Approach to Attractor Detection and Control of Boolean Networks

Author:

AKUTSU Tatsuya1,ZHAO Yang1,HAYASHIDA Morihiro1,TAMURA Takeyuki1

Affiliation:

1. Bioinformatics Center, Institute for Chemical Research, Kyoto University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference32 articles.

1. [1] T. Akutsu, S. Kuhara, O. Maruyama, and S. Miyano, “A system for identifying genetic networks from gene expression patterns produced by gene disruptions and overexpressions,” Genome Informatics, no.9, pp.151-160, 1998.

2. [2] T. Akutsu, M. Hayashida, W.-K. Ching, W.-K., and M.K. Ng, “Control of Boolean networks: hardness results and algorithms for tree-structured networks,” J. Theoretical Biology, vol.244, pp.670-679, 2007.

3. [3] T. Akutsu, M. Hayashida, and T. Tamura, “Integer programming-based methods for attractor detection and control of Boolean networks,” Proc. The combined 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, pp.5610-5617, 2009.

4. [4] T. Akutsu, A.A. Melkman, T. Tamura, and M. Yamamoto, “Determining a singleton attractor of a Boolean network with nested canalyzing functions,” J. Computational Biology, vol.18, pp.1275-1290, 2011.

5. [5] E. Balleza, E.R. Alvarez-Buylla, A. Chaos, S. Kauffman, I. Shmulevich, and M. Aldana. “Critical dynamics in genetic regulatory networks: examples from four kingdoms,” PLoS One, vol.3, e2456, 2008.

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