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- W3215020121 endingPage "102101" @default.
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- W3215020121 abstract "With advances in high-throughput sequencing technologies, quantitative genetics approaches have provided insights into genetic basis of many complex diseases. Emerging in-depth multi-omics profiling technologies have created exciting opportunities for systematically investigating intricate interaction networks with different layers of biological molecules underlying disease etiology. Herein, we summarized two main categories of biological networks: evidence-based and statistically inferred. These different types of molecular networks complement each other at both bulk and single-cell levels. We also review three main strategies to incorporate quantitative genetics results with multi-omics data by network analysis: (a) network propagation, (b) functional module-based methods, (c) comparative/dynamic networks. These strategies not only aid in elucidating molecular mechanisms of complex diseases but can guide the search for therapeutic targets." @default.
- W3215020121 created "2021-12-06" @default.
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- W3215020121 date "2022-02-01" @default.
- W3215020121 modified "2023-10-18" @default.
- W3215020121 title "Network biology bridges the gaps between quantitative genetics and multi-omics to map complex diseases" @default.
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- W3215020121 doi "https://doi.org/10.1016/j.cbpa.2021.102101" @default.
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