Windowed Granger causal inference strategy improves discovery of gene regulatory networks

• DOI: 10.1073/pnas.1710936115
• Publication Date: 2018-02-12T20:27:07Z
• Authors: Justin D. Finkle; Jia J. Wu; Neda Bagheri
• Keywords: Gene regulatory network; Identification

Significance Discovery of gene regulatory networks (GRNs) is crucial for gaining insights into biological processes involved in development or disease. Although time-resolved, high-throughput data are increasingly available, many algorithms do not account temporal delays underlying systems—such as protein synthesis and posttranslational modifications—leading to inaccurate network inference. To overcome this challenge, we introduce Sliding Window Inference Network Generation (SWING), which uniquely accounts information. We validate SWING both silico vitro experimental systems, highlighting improved performance identifying time-delayed edges illuminating structure. robust user-defined parameters, enabling identification mechanisms from time-series expression data.