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- W2801822128 abstract "Gene regulatory networks (GRNs) play a key role in various cellular processes and pathways. Recent advances in high-throughput biological data collection have provided novel platforms for understanding of GRNs, thus creating an enormous interest in mathematically modeling of biological networks. A good GRN inference algorithm can identify correct regulatory relationships among genes, which would hugely facilitate unveiling the fundamentals of how a cell operates and functions, thus allowing novel and better understanding of diseases initiation and progression. In this paper, we generalized the gene-regulated patterns first, and then reviewed the topology inference models/methods of GRNs from high-throughput omics data. Advantages, drawbacks, and application of each method were then analyzed and discussed. The consistency assessment and the validation of GRN-inferred are illustrated. Finally, we looked ahead to the challenge of GRN construction in multiomic integration and application trends of GRNs in a clinical context." @default.
- W2801822128 created "2018-05-17" @default.
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- W2801822128 date "2019-01-01" @default.
- W2801822128 modified "2023-09-26" @default.
- W2801822128 title "Gene Regulatory Network Review" @default.
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- W2801822128 doi "https://doi.org/10.1016/b978-0-12-809633-8.20218-5" @default.
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