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The statistical information of datasets is shown in Table 2.
Table 2 Statistical information of datasets Dataset #Nodes #Edges Avg.
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To use full information of dataset and avoid complicated computation of posterior, the Markov Chain Monte Carlo (MCMC) method was introduced to overcome the difficulty of the complicated high-dimension integral of the posterior in ABC.
The detailed information of dataset is shown in Table 1.
The other five datasets D6 - D10 are generated with DNA t = 2. Detailed information of the datasets is shown in Table 2.
Table 4 summarizes basic information of the datasets we used.
The usage of iBFE does not require any prior information of the datasets and patients.
A brief information of these datasets is presented in Table 1.
The brief information of four datasets is listed in Table 1.
All the information of the datasets are summarized in Table 3 and Additional file 5: Table S3.
The file may contain additional fields as needed (e.g. additional information of the datasets included in the analyses) and fields can be renamed to be accommodated to other programming practices.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com