Modeling pathways of differentiation in genetic regulatory networks with Boolean networks
Publication
, Journal Article
Dealy, S; Kauffman, S; Socolar, J
Published in: Complexity
January 1, 2005
We have carried out the first examination of pathways of cell differentiation in model genetic networks in which cell types are assumed to be attractors of the nonlinear dynamics, and differentiation corresponds to a transition of the cell to a new basin of attraction, which may be induced by a signal or noise perturbation. The associated flow along a transient to a new attractor corresponds to a pathway of differentiation. We have measured a variety of features of such model pathways of differentiation, most of which should be observable using gene array techniques. © 2005 Wiley Periodicals, Inc.
Duke Scholars
Published In
Complexity
DOI
EISSN
1099-0526
ISSN
1076-2787
Publication Date
January 1, 2005
Volume
11
Issue
1
Start / End Page
52 / 60
Related Subject Headings
- Fluids & Plasmas
- 49 Mathematical sciences
- 46 Information and computing sciences
- 0802 Computation Theory and Mathematics
- 0103 Numerical and Computational Mathematics
- 0102 Applied Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Dealy, S., Kauffman, S., & Socolar, J. (2005). Modeling pathways of differentiation in genetic regulatory networks with Boolean networks. Complexity, 11(1), 52–60. https://doi.org/10.1002/cplx.20100
Dealy, S., S. Kauffman, and J. Socolar. “Modeling pathways of differentiation in genetic regulatory networks with Boolean networks.” Complexity 11, no. 1 (January 1, 2005): 52–60. https://doi.org/10.1002/cplx.20100.
Dealy S, Kauffman S, Socolar J. Modeling pathways of differentiation in genetic regulatory networks with Boolean networks. Complexity. 2005 Jan 1;11(1):52–60.
Dealy, S., et al. “Modeling pathways of differentiation in genetic regulatory networks with Boolean networks.” Complexity, vol. 11, no. 1, Jan. 2005, pp. 52–60. Scopus, doi:10.1002/cplx.20100.
Dealy S, Kauffman S, Socolar J. Modeling pathways of differentiation in genetic regulatory networks with Boolean networks. Complexity. 2005 Jan 1;11(1):52–60.
Published In
Complexity
DOI
EISSN
1099-0526
ISSN
1076-2787
Publication Date
January 1, 2005
Volume
11
Issue
1
Start / End Page
52 / 60
Related Subject Headings
- Fluids & Plasmas
- 49 Mathematical sciences
- 46 Information and computing sciences
- 0802 Computation Theory and Mathematics
- 0103 Numerical and Computational Mathematics
- 0102 Applied Mathematics