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Fig 1.

Structure flowchart of the proposed two-stage procedure.

This flowchart shows the two-stage procedure in this study to detect the inverse transcriptional regulatory process of AD and BC. The first stage is to extract the feature genes of AD and BC datasets by FastICA, and the second stage is to deduce the regulatory activities and control strength of common TFs by NCA, then the TFs with inverse association will be selected for further study.

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Fig 1 Expand

Fig 2.

Dynamic transcriptional regulatory networks for the AD dataset.

(A) presents the transcriptional regulatory network for the control samples, and (B) shows the transcriptional regulatory network for AD samples. The diamonds in the middle denote TFs with different colors according to their activity values. The different colored circles display TG gene expression, and the different colored lines between the TFs and TGs show the control strength.

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Fig 2 Expand

Table 1.

KEGG pathway analysis of the shared TGs in AD and BC.

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Table 1 Expand

Fig 3.

Dynamic transcriptional regulatory networks for the BC dataset.

(A) presents the transcriptional regulatory network for the control samples, and (B) shows transcriptional regulatory network for the BC samples. The diamonds in the middle denote TFs, with different colors according to their activity values. The different colored circles display TG gene expression, and the different colored lines between the TFs and TGs show the control strength.

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Fig 3 Expand

Table 2.

Common TFs with their TGs in AD and BC.

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Table 2 Expand

Fig 4.

Flowchart of the experiments for different datasets of one disease (AD/BC).

(A) gives the flowchart of the two-stage procedure in comparing AD-HIP dataset with AD in 3 severities dataset; (B) gives the flowchart of the two-stage procedure in comparing BC with no metastasis dataset with BC in 3 grades dataset.

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Fig 4 Expand

Table 3.

Regulatory activities comparison of the shared TFs in two different AD datasets.

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Table 3 Expand

Table 4.

The regulatory activities of the shared TFs in two different BC datasets.

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Table 4 Expand

Fig 5.

The inversely associated TFs in Table 2 and their related genes, pathways and biological processes.

This figure shows the inverse regulatory activities of the common TFs and pathways between AD and BC. From the biological analysis we can know that they are closely related to innate and adaptive immune response.

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Fig 5 Expand

Table 5.

The regulatory activities of the 17 TFs in the additional AD datasets.

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Table 5 Expand

Table 6.

The regulatory activities of the 17 TFs in the additional BC datasets.

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Table 7.

The TFs with inverse activities of incipient AD and BC in grade Ⅰ.

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Table 8.

The TFs with inverse activities of moderate AD and BC in grade Ⅱ.

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Table 9.

The TFs with inverse activities of severe AD and BC in grade Ⅲ.

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Table 9 Expand