- Dynamic Modeling 111
between the components of biological systems. Although the analysis
of transcriptomics data for constructing the gene regulatory network is
taken as the example, other high-throughput data such as quantitative
proteomics and phosphoproteomics data can also be analyzed with the
similar procedure. The analysis of high-throughput data with dynamic
modeling procedure results in the mathematical expression of the biological
systems, which will be valuable for computational simulation of the systems.
In addition, the biological networks under specific experimental conditions
can be constructed based on the modeling procedure. These networks can be
further analyzed for understanding the biological mechanisms. For example,
the network motifs among the biological networks can be identified for
providing the insights into the network’s functions.^11 Network modules can
also be determined to predict unknown gene function, prioritize disease
genes, and classify cancer subtypes, etc.^12 Furthermore, biological networks
under different experimental conditions can be compared to become the
differential networks, which can yield insight into the biological basis of
variations of different phenotypes or diseases.^13 In summary, the dynamic
modeling procedure introduced in this chapter provides a useful tool for
high-throughput data analyses in systems biology.
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