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• W3088404762 abstract "Transcriptional regulatory networks control context-specific gene expression patterns and play important roles in normal and disease processes. Advances in genomics are rapidly increasing our ability to measure different components of the regulation machinery at the single-cell and bulk population level. An important challenge is to combine different types of regulatory genomic measurements to construct a more complete picture of gene regulatory networks across different disease, environmental, and developmental contexts. In this review, we focus on recent computational methods that integrate regulatory genomic datasets to infer context specificity and dynamics in regulatory networks." @default.
• W3088404762 created "2020-10-01" @default.
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• W3088404762 date "2020-10-01" @default.
• W3088404762 modified "2023-09-26" @default.
• W3088404762 title "Data integration for inferring context-specific gene regulatory networks" @default.
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• W3088404762 doi "https://doi.org/10.1016/j.coisb.2020.09.005" @default.
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