Inferring the Structure of Genetic Regulatory Networks Using Information Theoretic Tools
Conference Paper
-
- Overview
-
- Research
-
- Identity
-
- Additional Document Info
-
- View All
-
Overview
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
published proceedings
-
2006 IEEE/NLM Life Science Systems and Applications Workshop
author list (cited authors)
-
Zhao, W., Serpedin, E., & Dougherty, E. R
citation count
complete list of authors
-
Zhao, Wentao||Serpedin, Erchin||Dougherty, Edward R
publication date
publisher
Research
Identity
Digital Object Identifier (DOI)
International Standard Book Number (ISBN) 10
International Standard Book Number (ISBN) 13
Additional Document Info