The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Input-State Approach to Boolean Networks
Abstract
This paper investigates the structure of Boolean networks via input-state structure. Using the algebraic form proposed by the author, the logic-based input-state dynamics of Boolean networks, called the Boolean control networks, is converted into an algebraic discrete-time dynamic system. Then the structure of cycles of Boolean control systems is obtained as compounded cycles. Using the obtained input-state description, the structure of Boolean networks is investigated, and their attractors are revealed as nested compounded cycles, called rolling gears. This structure explains why small cycles mainly decide the behaviors of cellular networks. Some illustrative examples are presented.
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Citations
Cites
A N EW A PPROACH TO D ECODING L IFE : Systems Biology
Ideker, T., Galitski, T., & Hood, L. (2001) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.2.1.343 · Cited by 1,664
Cited by
Controllability and observability of Boolean control networks
Cheng, D., & Qi, H. (2009) · Automatica · doi:10.1016/j.automatica.2009.03.006 · Cited by 770
Self-citationA Linear Representation of Dynamics of Boolean Networks
Cheng, D., & Qi, H. (2010) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2010.2043294 · Cited by 697
Self-citation
Metadata
- Authors
- Cheng, D.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 2009-03
- Volume
- 20
- Issue
- 3
- Pages
- 512-521
- ISSN
- 1045-9227 (ISSN-L)
- 1941-0093
- OpenAlex
- W2132980130
- Cited by
- 169
- References
- 1
- FWCI
- 6.36
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cheng, D. (2009). Input-State Approach to Boolean Networks. IEEE Transactions on Neural Networks. https://doi.org/10.1109/tnn.2008.2011359
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
