Inferring the Structure of Genetic Regulatory Networks Using Information Theoretic Tools Conference Paper

abstract

• By combining the mutual information and conditional mutual information, a practical metric is proposed to capture the inference confidence of direct connectivity between two genes. This metric helps to avoid the disadvantage of general schemes, i.e., the dichotomy of either being connected or disconnected. Based on data sets generated by synthetic networks, the performance of proposed algorithm is compared favorably with respect to other schemes in the literature. The proposed algorithm is also applied on realistic cutaneous melanoma data set to recover a genetic network containing 470 genes. © 2006 IEEE.

name of conference

• 2006 IEEE/NLM Life Science Systems and Applications Workshop

authors

• Dougherty, Edward
• Serpedin, Erchin

published proceedings

• 2006 IEEE/NLM Life Science Systems and Applications Workshop

author list (cited authors)

• Zhao, W., Serpedin, E., & Dougherty, E. R

citation count

• 1

complete list of authors

• Zhao, Wentao||Serpedin, Erchin||Dougherty, Edward R

publication date

• July 2006

publisher

• IEEE  Publisher

keywords

• Genetics

Digital Object Identifier (DOI)

• 10.1109/lssa.2006.250379

International Standard Book Number (ISBN) 10

• 1424402786

International Standard Book Number (ISBN) 13

• 9781424402786

start page

• 1

end page

• 2