Inference of Gene Regulatory Networks Using Genetic Programming and Kalman Filter Conference Paper

abstract

• In this paper, gene regulatory networks are infered through evolutionary modeling and time-series microarray measurements. A nonlinear differential equation model is adopted and an iterative algorithm is proposed to identify the model, where genetic programming is applied to identify the structure of the model and Kalman filtering is employed to estimate the parameters in each iteration. Simulation results using synthetic data and microarray measurements show the effectiveness of the proposed scheme. 2006 IEEE.

name of conference

• 2006 IEEE International Workshop on Genomic Signal Processing and Statistics

authors

• Dougherty, Edward

published proceedings

• 2006 IEEE International Workshop on Genomic Signal Processing and Statistics

author list (cited authors)

• Wang, H., Qian, L., & Dougherty, E.

citation count

• 9

complete list of authors

• Wang, Haixin||Qian, Lijun||Dougherty, Edward

publication date

• May 2006

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Bioengineering
• Genetics

Digital Object Identifier (DOI)

• 10.1109/gensips.2006.353139

International Standard Book Number (ISBN) 10

• 1424403855

International Standard Book Number (ISBN) 13

• 9781424403851

start page

• 27

end page

• 28

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Fgensips.2006.353139