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- W258741279 abstract "Abstract This chapter describes biological backgrounds of regulatory relationships in living cells, high-throughput experimental technologies, and application of computational approaches in reverse engineering of microRNA (miRNA)-mediated and gene regulatory networks (GRNs). The most commonly used models for GRNs inference based on Boolean networks, Bayesian networks, dynamic Bayesian networks, association networks, novel two-stage model using integration of a priori biological knowledge, differential and difference equations models are detailed and their inference capabilities are compared. The regulatory role of miRNAs and transcription factors (TFs) in miRNAs-mediated regulatory networks is described as well. Additionally, commonly used methods for target prediction of miRNAs and TFs are described as well as most commonly used biological regulatory relationships databases and tools are listed. The mainly validation criteria used for assessment of inferred regulatory networks are explained. Finally, concluding remarks and further directions for miRNA-mediated and GRNs inference are given." @default.
- W258741279 created "2016-06-24" @default.
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- W258741279 date "2015-01-01" @default.
- W258741279 modified "2023-10-03" @default.
- W258741279 title "Overview of Computational Approaches for Inference of MicroRNA-Mediated and Gene Regulatory Networks" @default.
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- W258741279 doi "https://doi.org/10.1016/bs.adcom.2014.12.001" @default.
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