Conditional mutual inclusive information enables accurate quantification of associations in gene regulatory networks

• Main Authors: Zhang, Xiajun, Zhao, Juan, Hao, Jin-Kao, Zhao, Xing-Ming, Chen, Luonan
• Other Authors: School of Chemical and Biomedical Engineering
• Format: Article
• Language: English
• Published: 2015
• Subjects: Chemical and Biomedical Engineering
• Online Access: https://hdl.handle.net/10356/81063; http://hdl.handle.net/10220/39094
• Institution: Nanyang Technological University

Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mu...