Bayesian methods for elucidating genetic regulatory networks
Publication
, Journal Article
Hartemink, AJ; Gifford, DK; Jaakkola, TS; Young, RA
Published in: IEEE Intelligent Systems and Their Applications
March 1, 2002
The ability to observe and measure how cells respond to diverse treatments will profoundly affect the understanding of cell biology, the diagnosis and treatment of disease, and the efficacy of designing and delivering targeted therapeutics. Bayesian network methods are useful for elucidating genetic regulatory networks because they can represent more than pair-wise relationships between variables, are resistant to overfitting, and remain robust in the face of noisy data. This paper discusses the advantages and limitations of the approach and demonstrate its application in the context of the galactose system in yeast.
Duke Scholars
Published In
IEEE Intelligent Systems and Their Applications
DOI
ISSN
1094-7167
Publication Date
March 1, 2002
Volume
17
Issue
2
Start / End Page
37 / 43
Related Subject Headings
- Artificial Intelligence & Image Processing
- 0906 Electrical and Electronic Engineering
- 0806 Information Systems
- 0801 Artificial Intelligence and Image Processing
Citation
APA
Chicago
ICMJE
MLA
NLM
Hartemink, A. J., Gifford, D. K., Jaakkola, T. S., & Young, R. A. (2002). Bayesian methods for elucidating genetic regulatory networks. IEEE Intelligent Systems and Their Applications, 17(2), 37–43. https://doi.org/10.1109/5254.999218
Hartemink, A. J., D. K. Gifford, T. S. Jaakkola, and R. A. Young. “Bayesian methods for elucidating genetic regulatory networks.” IEEE Intelligent Systems and Their Applications 17, no. 2 (March 1, 2002): 37–43. https://doi.org/10.1109/5254.999218.
Hartemink AJ, Gifford DK, Jaakkola TS, Young RA. Bayesian methods for elucidating genetic regulatory networks. IEEE Intelligent Systems and Their Applications. 2002 Mar 1;17(2):37–43.
Hartemink, A. J., et al. “Bayesian methods for elucidating genetic regulatory networks.” IEEE Intelligent Systems and Their Applications, vol. 17, no. 2, Mar. 2002, pp. 37–43. Scopus, doi:10.1109/5254.999218.
Hartemink AJ, Gifford DK, Jaakkola TS, Young RA. Bayesian methods for elucidating genetic regulatory networks. IEEE Intelligent Systems and Their Applications. 2002 Mar 1;17(2):37–43.
Published In
IEEE Intelligent Systems and Their Applications
DOI
ISSN
1094-7167
Publication Date
March 1, 2002
Volume
17
Issue
2
Start / End Page
37 / 43
Related Subject Headings
- Artificial Intelligence & Image Processing
- 0906 Electrical and Electronic Engineering
- 0806 Information Systems
- 0801 Artificial Intelligence and Image Processing