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Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory | Abstract Reconstruction of time-varying gene regulatory networks underlying a time-series gene expression data is a fundamental challenge in the computational systems biology. The challenge increases multi-fold if the target networks need to be constructed for hundreds to thousands of genes. There have been constant efforts to design an algorithm that can perform the reconstruction task correctly as well as can scale efficiently (with respect to both time and memory) to such a large number of genes. However, the existing algorithms either do not offer time-efficiency, or they offer it at other costs memory-inefficiency or imposition of a constraint, known as the ‘smoothly time-varying assumption’