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Our reconstruction of network 5 (Fig. 8A) achieved an AUPR of 76%.
The reconstruction of network 1 (Fig. 10A) achieved a very high AUPR of 92%.
Our software records all data in real-time to a relational database for later reconstruction of network maps and diffusion pathways.
The reconstruction of network will be very time-consuming when there exists massive number of expression profiles (e.g., n > 20,000 and m > 1,000).
Our study focuses on the reconstruction of network of biochemical interactions taking place between the drug, its metabolites, and their cellular targets.
Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology.
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Furthermore, the method is generalized for reconstruction of networks with time-delayed coupling, including the reconstruction of unknown time delays.
The reconstruction of networks solely from metabolic mass spectrometry data is a very young field of research.
In this section, we will only cover the pure de novo reconstruction of networks from metabolite mass spectrometry data.
As a proof of concept, we demonstrated reconstruction of networks with two nodes.
Nevertheless, prior knowledge can be of a benefit in the reconstruction of networks from time series.
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CEO of Professional Science Editing for Scientists @ prosciediting.com